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Bouman PM, van Dam MA, Jonkman LE, Steenwijk MD, Schoonheim MM, Geurts JJG, Hulst HE. Isolated cognitive impairment in people with multiple sclerosis: frequency, MRI patterns and its development over time. J Neurol 2024; 271:2159-2168. [PMID: 38286843 PMCID: PMC11055711 DOI: 10.1007/s00415-024-12185-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/25/2023] [Accepted: 01/02/2024] [Indexed: 01/31/2024]
Abstract
OBJECTIVES To study the frequency of isolated (i.e., single-domain) cognitive impairments, domain specific MRI correlates, and its longitudinal development in people with multiple sclerosis (PwMS). METHODS 348 PwMS (mean age 48 ± 11 years, 67% female, 244RR/52SP/38PP) underwent neuropsychological testing (extended BRB-N) at baseline and at five-year follow-up. At baseline, structural MRI was acquired. Isolated cognitive impairment was defined as a Z-score of at least 1.5 SD below normative data in one domain only (processing speed, memory, executive functioning/working memory, and attention). Multi-domain cognitive impairment was defined as being affected in ≥ 2 domains, and cognitively preserved otherwise. For PwMS with isolated cognitive impairment, MRI correlates were explored using linear regression. Development of isolated cognitive impairment over time was evaluated based on reliable change index. RESULTS At baseline, 108 (31%) PwMS displayed isolated cognitive impairment, 148 (43%) PwMS displayed multi-domain cognitive impairment. Most PwMS with isolated cognitive impairment were impaired on executive functioning/working memory (EF/WM; N = 37), followed by processing speed (IPS; N = 25), memory (N = 23), and attention (N = 23). Isolated IPS impairment was explained by a model of cortical volume and fractional anisotropy (adj. R2 = 0.539, p < 0.001); memory by a model with cortical volume and hippocampal volume (adj. R2 = 0.493, p = 0.002); EF/WM and attention were not associated with any MRI measure. At follow-up, cognitive decline was present in 11/16 (69%) of PwMS with isolated IPS impairment at baseline. This percentage varied between 18 and 31% of PwMS with isolated cognitive impairment in domains other than IPS at baseline. CONCLUSION Isolated cognitive impairment is frequently present in PwMS and can serve as a proxy for further decline, particularly when it concerns processing speed. Cortical and deep grey matter atrophy seem to play a pivotal role in isolated cognitive impairment. Timely detection and patient-tailored intervention, predominantly for IPS, may help to postpone further cognitive decline.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC VUmc, De Boelelaan 1117, Amsterdam, The Netherlands.
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.
| | - Maureen A van Dam
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC VUmc, De Boelelaan 1117, Amsterdam, The Netherlands
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Laura E Jonkman
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging and Neurodegeneration, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC VUmc, De Boelelaan 1117, Amsterdam, The Netherlands
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC VUmc, De Boelelaan 1117, Amsterdam, The Netherlands
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC VUmc, De Boelelaan 1117, Amsterdam, The Netherlands
- Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
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Luchicchi A, Muñoz‐Gonzalez G, Halperin ST, Strijbis E, van Dijk LHM, Foutiadou C, Uriac F, Bouman PM, Schouten MAN, Plemel J, 't Hart BA, Geurts JJG, Schenk GJ. Micro-diffusely abnormal white matter: An early multiple sclerosis lesion phase with intensified myelin blistering. Ann Clin Transl Neurol 2024; 11:973-988. [PMID: 38425098 PMCID: PMC11021636 DOI: 10.1002/acn3.52015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/03/2024] [Accepted: 01/25/2024] [Indexed: 03/02/2024] Open
Abstract
OBJECTIVE Multiple sclerosis (MS) is a chronic central nervous system disease whose white matter lesion origin remains debated. Recently, we reported subtle changes in the MS normal appearing white matter (NAWM), presenting with an increase in myelin blisters and myelin protein citrullination, which may recapitulate some of the prodromal degenerative processes involved in MS pathogenesis. Here, to clarify the relevance of these changes for subsequent MS myelin degeneration we explored their prevalence in WM regions characterized by subtly reduced myelination (dubbed as micro-diffusely abnormal white matter, mDAWM). METHODS We used an in-depth (immuno)histochemistry approach in 27 MS donors with histological presence of mDAWM and 5 controls. An antibody panel against degenerative markers was combined and the presence of myelin/axonal aberrations was analyzed and compared with the NAWM from the same cases/slices/regions. RESULTS mDAWM-defined areas exhibit ill-defined borders, no signs of Wallerian degeneration, and they associate with visible veins. Remarkably, such areas present with augmented myelin blister frequency, enhanced prevalence of polar myelin phospholipids, citrullination, and degradation of myelin basic protein (MBP) when compared with the NAWM. Furthermore, enhanced reactivity of microglia/macrophages against citrullinated MBP was also observed in this tissue. INTERPRETATION We report a new histologically defined early phase in MS lesion formation, namely mDAWM, which lacks signs of Wallerian pathology. These results support the prelesional nature of the mDAWM. We conceptualize that evolution to pathologically evident lesions comprises the previously documented imbalance of axo-myelinic units (myelin blistering) leading to their degeneration and immune system activation by released myelin components.
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Affiliation(s)
- Antonio Luchicchi
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Gema Muñoz‐Gonzalez
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Saar T. Halperin
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Eva Strijbis
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
- Department of NeurologyAmsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Laura H. M. van Dijk
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Chrisa Foutiadou
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Florence Uriac
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
| | - Piet M. Bouman
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Maxime A. N. Schouten
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Jason Plemel
- Department of NeuroscienceUniversity of AlbertaEdmontonAlbertaCanada
| | - Bert A. 't Hart
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Jeroen J. G. Geurts
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
| | - Geert J. Schenk
- Department of Anatomy and NeurosciencesAmsterdam University Medical Centers, location VU Medical Center, Amsterdam NeuroscienceAmsterdamthe Netherlands
- MS Centrum Amsterdam, Amsterdam University Medical Centers, location VU Medical CenterAmsterdamthe Netherlands
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Koubiyr I, Krijnen EA, Eijlers AJC, Dekker I, Hulst HE, Uitdehaag BMJ, Barkhof F, Geurts JJG, Schoonheim MM. Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis. Brain Commun 2024; 6:fcae018. [PMID: 38344654 PMCID: PMC10853982 DOI: 10.1093/braincomms/fcae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 12/21/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.
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Affiliation(s)
- Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Eva A Krijnen
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States
| | - Anand J C Eijlers
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Iris Dekker
- MS Center Amsterdam, Rehabilitation, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Hanneke E Hulst
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden 2333 AK, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Frederik Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
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van Lingen MR, Breedt LC, Geurts JJG, Hillebrand A, Klein M, Kouwenhoven MCM, Kulik SD, Reijneveld JC, Stam CJ, De Witt Hamer PC, Zimmermann MLM, Santos FAN, Douw L. The longitudinal relation between executive functioning and multilayer network topology in glioma patients. Brain Imaging Behav 2023; 17:425-435. [PMID: 37067658 PMCID: PMC10435610 DOI: 10.1007/s11682-023-00770-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2023] [Indexed: 04/18/2023]
Abstract
Many patients with glioma, primary brain tumors, suffer from poorly understood executive functioning deficits before and/or after tumor resection. We aimed to test whether frontoparietal network centrality of multilayer networks, allowing for integration across multiple frequencies, relates to and predicts executive functioning in glioma. Patients with glioma (n = 37) underwent resting-state magnetoencephalography and neuropsychological tests assessing word fluency, inhibition, and set shifting before (T1) and one year after tumor resection (T2). We constructed binary multilayer networks comprising six layers, with each layer representing frequency-specific functional connectivity between source-localized time series of 78 cortical regions. Average frontoparietal network multilayer eigenvector centrality, a measure for network integration, was calculated at both time points. Regression analyses were used to investigate associations with executive functioning. At T1, lower multilayer integration (p = 0.017) and epilepsy (p = 0.006) associated with poorer set shifting (adj. R2 = 0.269). Decreasing multilayer integration (p = 0.022) and not undergoing chemotherapy at T2 (p = 0.004) related to deteriorating set shifting over time (adj. R2 = 0.283). No significant associations were found for word fluency or inhibition, nor did T1 multilayer integration predict changes in executive functioning. As expected, our results establish multilayer integration of the frontoparietal network as a cross-sectional and longitudinal correlate of executive functioning in glioma patients. However, multilayer integration did not predict postoperative changes in executive functioning, which together with the fact that this correlate is also found in health and other diseases, limits its specific clinical relevance in glioma.
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Affiliation(s)
- Marike R van Lingen
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands.
- Cancer Center Amsterdam, Amsterdam, the Netherlands.
| | - Lucas C Breedt
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Mathilde C M Kouwenhoven
- Department of Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Shanna D Kulik
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
| | - Jaap C Reijneveld
- Department of Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands
- Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Philip C De Witt Hamer
- Department of Neurosurgery, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Mona L M Zimmermann
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
- Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Fernando A N Santos
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands
- Institute of Advanced Studies, University of Amsterdam, Amsterdam, the Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, de Boelelaan 1108, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Systems & Network Neurosciences, Amsterdam, the Netherlands.
- Cancer Center Amsterdam, Amsterdam, the Netherlands.
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van Dam M, de Jong BA, Willemse EAJ, Nauta IM, Huiskamp M, Klein M, Moraal B, de Geus-Driessen S, Geurts JJG, Uitdehaag BMJ, Teunissen CE, Hulst HE. A multimodal marker for cognitive functioning in multiple sclerosis: the role of NfL, GFAP and conventional MRI in predicting cognitive functioning in a prospective clinical cohort. J Neurol 2023:10.1007/s00415-023-11676-4. [PMID: 37101095 DOI: 10.1007/s00415-023-11676-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 04/28/2023]
Abstract
BACKGROUND Cognitive impairment in people with MS (PwMS) has primarily been investigated using conventional imaging markers or fluid biomarkers of neurodegeneration separately. However, the single use of these markers do only partially explain the large heterogeneity found in PwMS. OBJECTIVE To investigate the use of multimodal (bio)markers: i.e., serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and conventional imaging markers in predicting cognitive functioning in PwMS. METHODS Eighty-two PwMS (56 females, disease duration = 14 ± 9 years) underwent neuropsychological and neurological examination, structural magnetic resonance imaging, blood sampling and lumbar puncture. PwMS were classified as cognitively impaired (CI) if scoring ≥ 1.5SD below normative scores on ≥ 20% of test scores. Otherwise, PwMS were defined as cognitively preserved (CP). Association between fluid and imaging (bio)markers were investigated, as well as binary logistics regression to predict cognitive status. Finally, a multimodal marker was calculated using statistically important predictors of cognitive status. RESULTS Only higher NfL levels (in serum and CSF) correlated with worse processing speed (r = - 0.286, p = 0.012 and r = - 0.364, p = 0.007, respectively). sNfL added unique variance in the prediction of cognitive status on top of grey matter volume (NGMV), p = 0.002). A multimodal marker of NGMV and sNfL yielded most promising results in predicting cognitive status (sensitivity = 85%, specificity = 58%). CONCLUSION Fluid and imaging (bio)markers reflect different aspects of neurodegeneration and cannot be used interchangeably as markers for cognitive functioning in PwMS. The use of a multimodal marker, i.e., the combination of grey matter volume and sNfL, seems most promising for detecting cognitive deficits in MS.
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Affiliation(s)
- Maureen van Dam
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Brigit A de Jong
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Eline A J Willemse
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
- Neurology Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Biomedicine and Clinical Research, Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ilse M Nauta
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Marijn Huiskamp
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Sanne de Geus-Driessen
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Institute of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Wassenaarseweg 52, Leiden, The Netherlands
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6
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Bouman PM, Noteboom S, Nobrega Santos FA, Beck ES, Bliault G, Castellaro M, Calabrese M, Chard DT, Eichinger P, Filippi M, Inglese M, Lapucci C, Marciniak A, Moraal B, Morales Pinzon A, Mühlau M, Preziosa P, Reich DS, Rocca MA, Schoonheim MM, Twisk JWR, Wiestler B, Jonkman LE, Guttmann CRG, Geurts JJG, Steenwijk MD. Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection. Radiology 2023; 307:e221425. [PMID: 36749211 PMCID: PMC10102645 DOI: 10.1148/radiol.221425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/18/2022] [Accepted: 11/28/2022] [Indexed: 02/08/2023]
Abstract
Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.
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Affiliation(s)
- Piet M. Bouman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Samantha Noteboom
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Fernando A. Nobrega Santos
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Erin S. Beck
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Gregory Bliault
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Marco Castellaro
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimiliano Calabrese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Declan T. Chard
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paul Eichinger
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimo Filippi
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Matilde Inglese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Caterina Lapucci
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Andrzej Marciniak
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Bastiaan Moraal
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Alfredo Morales Pinzon
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Mark Mühlau
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paolo Preziosa
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Daniel S. Reich
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Maria A. Rocca
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Menno M. Schoonheim
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jos W. R. Twisk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Benedict Wiestler
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Laura E. Jonkman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Charles R. G. Guttmann
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jeroen J. G. Geurts
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Martijn D. Steenwijk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
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7
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Huiskamp M, Yaqub M, van Lingen MR, Pouwels PJW, de Ruiter LRJ, Killestein J, Schwarte LA, Golla SSV, van Berckel BNM, Boellaard R, Geurts JJG, Hulst HE. Cognitive performance in multiple sclerosis: what is the role of the gamma-aminobutyric acid system? Brain Commun 2023; 5:fcad140. [PMID: 37180993 PMCID: PMC10174207 DOI: 10.1093/braincomms/fcad140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 01/26/2023] [Accepted: 04/28/2023] [Indexed: 05/16/2023] Open
Abstract
Cognitive impairment occurs in 40-65% of persons with multiple sclerosis and may be related to alterations in glutamatergic and GABAergic neurotransmission. Therefore, the aim of this study was to determine how glutamatergic and GABAergic changes relate to cognitive functioning in multiple sclerosis in vivo. Sixty persons with multiple sclerosis (mean age 45.5 ± 9.6 years, 48 females, 51 relapsing-remitting multiple sclerosis) and 22 age-matched healthy controls (45.6 ± 22.0 years, 17 females) underwent neuropsychological testing and MRI. Persons with multiple sclerosis were classified as cognitively impaired when scoring at least 1.5 standard deviations below normative scores on ≥30% of tests. Glutamate and GABA concentrations were determined in the right hippocampus and bilateral thalamus using magnetic resonance spectroscopy. GABA-receptor density was assessed using quantitative [11C]flumazenil positron emission tomography in a subset of participants. Positron emission tomography outcome measures were the influx rate constant (a measure predominantly reflecting perfusion) and volume of distribution, which is a measure of GABA-receptor density. Twenty persons with multiple sclerosis (33%) fulfilled the criteria for cognitive impairment. No differences were observed in glutamate or GABA concentrations between persons with multiple sclerosis and healthy controls, or between cognitively preserved, impaired and healthy control groups. Twenty-two persons with multiple sclerosis (12 cognitively preserved and 10 impaired) and 10 healthy controls successfully underwent [11C]flumazenil positron emission tomography. Persons with multiple sclerosis showed a lower influx rate constant in the thalamus, indicating lower perfusion. For the volume of distribution, persons with multiple sclerosis showed higher values than controls in deep grey matter, reflecting increased GABA-receptor density. When comparing cognitively impaired and preserved patients to controls, the preserved group showed a significantly higher volume of distribution in cortical and deep grey matter and hippocampus. Positive correlations were observed between both positron emission tomography measures and information processing speed in the multiple sclerosis group only. Whereas concentrations of glutamate and GABA did not differ between multiple sclerosis and control nor between cognitively impaired, preserved and control groups, increased GABA-receptor density was observed in preserved persons with multiple sclerosis that was not seen in cognitively impaired patients. In addition, GABA-receptor density correlated to cognition, in particular with information processing speed. This could indicate that GABA-receptor density is upregulated in the cognitively preserved phase of multiple sclerosis as a means to regulate neurotransmission and potentially preserve cognitive functioning.
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Affiliation(s)
- Marijn Huiskamp
- Correspondence to: M. Huiskamp Department of Anatomy & Neurosciences Amsterdam UMC, Location Vrije Universiteit PO Box 7057, 1007 MB Amsterdam, The Netherlands E-mail:
| | - Maqsood Yaqub
- Department of Radiology and nuclear medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Marike R van Lingen
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and nuclear medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Lodewijk R J de Ruiter
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Joep Killestein
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Lothar A Schwarte
- Department of Anesthesiology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Sandeep S V Golla
- Department of Radiology and nuclear medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and nuclear medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Ronald Boellaard
- Department of Radiology and nuclear medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Hanneke E Hulst
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
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8
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Breedt LC, Santos FAN, Hillebrand A, Reneman L, van Rootselaar AF, Schoonheim MM, Stam CJ, Ticheler A, Tijms BM, Veltman DJ, Vriend C, Wagenmakers MJ, van Wingen GA, Geurts JJG, Schrantee A, Douw L. Multimodal multilayer network centrality relates to executive functioning. Netw Neurosci 2023; 7:299-321. [PMID: 37339322 PMCID: PMC10275212 DOI: 10.1162/netn_a_00284] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 10/07/2022] [Indexed: 02/18/2024] Open
Abstract
Executive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one 'network of networks.' We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.
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Affiliation(s)
- Lucas C. Breedt
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Fernando A. N. Santos
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
- Institute of Advanced Studies, University of Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Anne-Fleur van Rootselaar
- Department of Neurology and Clinical Neurophysiology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Menno M. Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Cornelis J. Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Anouk Ticheler
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Chris Vriend
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Margot J. Wagenmakers
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
- GGZ in Geest Specialized Mental Health Care, Amsterdam, The Netherlands
| | - Guido A. van Wingen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Jeroen J. G. Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, The Netherlands
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9
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Numan T, Breedt LC, Maciel BDAPC, Kulik SD, Derks J, Schoonheim MM, Klein M, de Witt Hamer PC, Miller JJ, Gerstner ER, Stufflebeam SM, Hillebrand A, Stam CJ, Geurts JJG, Reijneveld JC, Douw L. Regional healthy brain activity, glioma occurrence and symptomatology. Brain 2022; 145:3654-3665. [PMID: 36130310 PMCID: PMC9586543 DOI: 10.1093/brain/awac180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/22/2022] [Accepted: 05/04/2022] [Indexed: 11/24/2022] Open
Abstract
It is unclear why exactly gliomas show preferential occurrence in certain brain areas. Increased spiking activity around gliomas leads to faster tumour growth in animal models, while higher non-invasively measured brain activity is related to shorter survival in patients. However, it is unknown how regional intrinsic brain activity, as measured in healthy controls, relates to glioma occurrence. We first investigated whether gliomas occur more frequently in regions with intrinsically higher brain activity. Second, we explored whether intrinsic cortical activity at individual patients’ tumour locations relates to tumour and patient characteristics. Across three cross-sectional cohorts, 413 patients were included. Individual tumour masks were created. Intrinsic regional brain activity was assessed through resting-state magnetoencephalography acquired in healthy controls and source-localized to 210 cortical brain regions. Brain activity was operationalized as: (i) broadband power; and (ii) offset of the aperiodic component of the power spectrum, which both reflect neuronal spiking of the underlying neuronal population. We additionally assessed (iii) the slope of the aperiodic component of the power spectrum, which is thought to reflect the neuronal excitation/inhibition ratio. First, correlation coefficients were calculated between group-level regional glioma occurrence, as obtained by concatenating tumour masks across patients, and group-averaged regional intrinsic brain activity. Second, intrinsic brain activity at specific tumour locations was calculated by overlaying patients’ individual tumour masks with regional intrinsic brain activity of the controls and was associated with tumour and patient characteristics. As proposed, glioma preferentially occurred in brain regions characterized by higher intrinsic brain activity in controls as reflected by higher offset. Second, intrinsic brain activity at patients’ individual tumour locations differed according to glioma subtype and performance status: the most malignant isocitrate dehydrogenase-wild-type glioblastoma patients had the lowest excitation/inhibition ratio at their individual tumour locations as compared to isocitrate dehydrogenase-mutant, 1p/19q-codeleted glioma patients, while a lower excitation/inhibition ratio related to poorer Karnofsky Performance Status, particularly in codeleted glioma patients. In conclusion, gliomas more frequently occur in cortical brain regions with intrinsically higher activity levels, suggesting that more active regions are more vulnerable to glioma development. Moreover, indices of healthy, intrinsic excitation/inhibition ratio at patients’ individual tumour locations may capture both tumour biology and patients’ performance status. These findings contribute to our understanding of the complex and bidirectional relationship between normal brain functioning and glioma growth, which is at the core of the relatively new field of ‘cancer neuroscience’.
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Affiliation(s)
- Tianne Numan
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Lucas C Breedt
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Bernardo de A P C Maciel
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Shanna D Kulik
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Jolanda Derks
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Martin Klein
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Medical Psychology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Philip C de Witt Hamer
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurosurgery, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Julie J Miller
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Elizabeth R Gerstner
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Jaap C Reijneveld
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurology, Stichting Epilepsie Instellingen Nederland, Heemstede 2103 SW, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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10
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Schoonheim MM, Broeders TAA, Geurts JJG. The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics. Neuroimage Clin 2022; 35:103108. [PMID: 35917719 PMCID: PMC9421449 DOI: 10.1016/j.nicl.2022.103108] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/01/2022] [Accepted: 07/10/2022] [Indexed: 11/16/2022]
Abstract
Multiple sclerosis (MS) can be considered as a network disorder. This review discusses network concepts in order to understand progression in MS. Damage is hypothesized to lead to a “network collapse” and clinical progression. New concepts are discussed that will likely influence the field in the near future. These include brain wiring, how regions communicate and robustness to damage.
Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a “network collapse”. After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.
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Affiliation(s)
- Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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11
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Rocca MA, Schoonheim MM, Valsasina P, Geurts JJG, Filippi M. Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective. Neuroimage Clin 2022; 35:103076. [PMID: 35691253 PMCID: PMC9194954 DOI: 10.1016/j.nicl.2022.103076] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 01/12/2023]
Abstract
Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages. Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease. Collapse of long-range connections and impaired hub integration characterize MS network reorganization. Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity. New perspectives might be the use of multimodal MRI and artificial intelligence.
Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
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12
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Bouman PM, Steenwijk MD, Geurts JJG, Jonkman LE. Artificial double inversion recovery images can substitute conventionally acquired images: an MRI-histology study. Sci Rep 2022; 12:2620. [PMID: 35173226 PMCID: PMC8850613 DOI: 10.1038/s41598-022-06546-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/28/2022] [Indexed: 11/09/2022] Open
Abstract
Cortical multiple sclerosis lesions are disease-specific, yet inconspicuous on magnetic resonance images (MRI). Double inversion recovery (DIR) images are sensitive, but often unavailable in clinical routine and clinical trials. Artificially generated images can mitigate this issue, but lack histopathological validation. In this work, artificial DIR images were generated from postmortem 3D-T1 and proton-density (PD)/T2 or 3D-T1 and 3D fluid-inversion recovery (FLAIR) images, using a generative adversarial network. All sequences were scored for cortical lesions, blinded to histopathology. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesions type I-IV (leukocortical, intracortical, subpial and cortex-spanning, respectively). Histopathological scorings were then (unblinded) compared to MRI using linear mixed models. Images from 38 patients (26 female, mean age 64.3 ± 10.7) were included. A total of 142 cortical lesions were detected, predominantly subpial. Histopathology-blinded/unblinded sensitivity was 13.4/35.2% for artificial DIR generated from T1-PD/T2, 14.1/41.5% for artificial DIR from T1-FLAIR, 17.6/49.3% for conventional DIR and 10.6/34.5% for 3D-T1. When blinded to histopathology, there were no differences; with histopathological feedback at hand, conventional DIR and artificial DIR from T1-FLAIR outperformed the other sequences. Differences between histopathology-blinded/unblinded sensitivity could be minified through adjustment of the scoring criteria. In conclusion, artificial DIR images, particularly generated from T1-FLAIR could potentially substitute conventional DIR images when these are unavailable.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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13
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Kulik SD, Nauta IM, Tewarie P, Koubiyr I, van Dellen E, Ruet A, Meijer KA, de Jong BA, Stam CJ, Hillebrand A, Geurts JJG, Douw L, Schoonheim MM. Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis. Netw Neurosci 2021; 6:339-356. [PMID: 35733434 PMCID: PMC9208024 DOI: 10.1162/netn_a_00226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 12/21/2021] [Indexed: 11/04/2022] Open
Abstract
Abstract
Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear.
This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1 and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. ROC analyses were performed on coupling values to identify biomarker potential.
Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = −0.26, p = 0.023, only in MS). Long-range structure-function coupling was higher in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range AUC = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095).
Long-range structure-function coupling was higher in CI-MS compared to HC, but more research is needed to further explore this measure as biomarkers in MS.
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Affiliation(s)
- Shanna D. Kulik
- Departments of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Ilse M. Nauta
- Department of Neurology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Prejaas Tewarie
- Department of Neurology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Clinical Neurophysiology and MEG Center, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Ismail Koubiyr
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France
| | - Edwin van Dellen
- University Medical Center Utrecht, Psychiatry, Brain Center Rudolf Magnus, Utrecht, Netherlands
| | - Aurelie Ruet
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France
- CHU de Bordeaux, Service de Neurologie, Bordeaux, France
| | - Kim A. Meijer
- Departments of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Brigit A. de Jong
- Department of Neurology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Cornelis J. Stam
- Department of Neurology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Clinical Neurophysiology and MEG Center, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Arjan Hillebrand
- Clinical Neurophysiology and MEG Center, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeroen J. G. Geurts
- Departments of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Linda Douw
- Departments of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Menno M. Schoonheim
- Departments of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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14
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Huitema MJD, Strijbis EMM, Luchicchi A, Bol JGJM, Plemel JR, Geurts JJG, Schenk GJ. Myelin Quantification in White Matter Pathology of Progressive Multiple Sclerosis Post-Mortem Brain Samples: A New Approach for Quantifying Remyelination. Int J Mol Sci 2021; 22:ijms222312634. [PMID: 34884445 PMCID: PMC8657470 DOI: 10.3390/ijms222312634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/16/2021] [Accepted: 11/18/2021] [Indexed: 01/14/2023] Open
Abstract
Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system (CNS). Repair through remyelination can be extensive, but quantification of remyelination remains challenging. To date, no method for standardized digital quantification of remyelination of MS lesions exists. This methodological study aims to present and validate a novel standardized method for myelin quantification in progressive MS brains to study myelin content more precisely. Fifty-five MS lesions in 32 tissue blocks from 14 progressive MS cases and five tissue blocks from 5 non-neurological controls were sampled. MS lesions were selected by macroscopic investigation of WM by standard histopathological methods. Tissue sections were stained for myelin with luxol fast blue (LFB) and histological assessment of de- or remyelination was performed by light microscopy. The myelin quantity was estimated with a novel myelin quantification method (MQM) in ImageJ. Three independent raters applied the MQM and the inter-rater reliability was calculated. We extended the method to diffusely appearing white matter (DAWM) and encephalitis to test potential wider applicability of the method. Inter-rater agreement was excellent (ICC = 0.96) and there was a high reliability with a lower- and upper limit of agreement up to −5.93% to 18.43% variation in myelin quantity. This study builds on the established concepts of histopathological semi-quantitative assessment of myelin and adds a novel, reliable and accurate quantitative measurement tool for the assessment of myelination in human post-mortem samples.
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Affiliation(s)
- Marije J. D. Huitema
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands; (M.J.D.H.); (A.L.); (J.G.J.M.B.); (J.J.G.G.)
| | - Eva M. M. Strijbis
- Department of Neurology, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, 1081 HZ Amsterdam, The Netherlands;
| | - Antonio Luchicchi
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands; (M.J.D.H.); (A.L.); (J.G.J.M.B.); (J.J.G.G.)
| | - John G. J. M. Bol
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands; (M.J.D.H.); (A.L.); (J.G.J.M.B.); (J.J.G.G.)
| | - Jason R. Plemel
- Department of Medicine, Division of Neurology, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB T6G 2S2, Canada;
- Department of Medical Microbiology & Immunology, University of Alberta, Edmonton, AB T6G 2S2, Canada
| | - Jeroen J. G. Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands; (M.J.D.H.); (A.L.); (J.G.J.M.B.); (J.J.G.G.)
| | - Geert J. Schenk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands; (M.J.D.H.); (A.L.); (J.G.J.M.B.); (J.J.G.G.)
- Correspondence:
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15
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Fuchs TA, Schoonheim MM, Broeders TAA, Hulst HE, Weinstock-Guttman B, Jakimovski D, Silver J, Zivadinov R, Geurts JJG, Dwyer MG, Benedict RHB. Functional network dynamics and decreased conscientiousness in multiple sclerosis. J Neurol 2021; 269:2696-2706. [PMID: 34713325 DOI: 10.1007/s00415-021-10860-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 10/15/2021] [Accepted: 10/17/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Conscientiousness is a personality trait that declines in people with multiple sclerosis (PwMS) and its decline predicts worse clinical outcomes. This study aims to investigate the neural underpinnings of lower Conscientiousness in PwMS by examining MRI anomalies in functional network dynamics. METHODS 70 PwMS and 50 healthy controls underwent personality assessment and resting-state MRI. Associations with dynamic functional network properties (i.e., eigenvector centrality) were evaluated, using a dynamic sliding-window approach. RESULTS In PwMS, lower Conscientiousness was associated with increased variability of centrality in the left insula (tmax = 4.21) and right inferior parietal lobule (tmax = 3.79); a relationship also observed in regressions accounting for handedness, disease duration, disability, and tract disruption in relevant structural networks (ΔR2 = 0.071, p = 0.003; ΔR2 = 0.094, p = 0.004). Centrality dynamics of the observed regions were not associated with Neuroticism (R2 < 0.001, p = 0.956; R2 < 0.001, p = 0.945). As well, higher Conscientiousness was associated with greater variability in connectivity for the left insula with the default-mode network (F = 3.92, p = 0.023) and limbic network (F = 5.66, p = 0.005). CONCLUSION Lower Conscientiousness in PwMS was associated with increased variability in network centrality, most prominently for the left insula and right inferior parietal cortex. This effect, specific to Conscientiousness and significant after accounting for disability and structural network damage, could indicate that overall stable network centrality is lost in patients with low Conscientiousness, especially for the insula and right parietal cortex. The positive relationship between Conscientiousness and variability of connectivity between left insula and default-mode network potentially affirms that dynamics between the salience and default-mode networks is related to the regulation of behavior.
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Affiliation(s)
- Tom A Fuchs
- Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.,Jacobs Multiple Sclerosis Center for Treatment and Research, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bianca Weinstock-Guttman
- Jacobs Multiple Sclerosis Center for Treatment and Research, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Jacob Silver
- Department of Orthopedics, School of Medicine, University of Connecticut, Farmington, CT, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.,Jacobs Multiple Sclerosis Center for Treatment and Research, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.,Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.,Jacobs Multiple Sclerosis Center for Treatment and Research, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.,Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Ralph H B Benedict
- Jacobs Multiple Sclerosis Center for Treatment and Research, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
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16
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Nij Bijvank JA, Strijbis EMM, Nauta IM, Kulik SD, Balk LJ, Stam CJ, Hillebrand A, Geurts JJG, Uitdehaag BMJ, van Rijn LJ, Petzold A, Schoonheim MM. Impaired saccadic eye movements in multiple sclerosis are related to altered functional connectivity of the oculomotor brain network. Neuroimage Clin 2021; 32:102848. [PMID: 34624635 PMCID: PMC8503580 DOI: 10.1016/j.nicl.2021.102848] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 09/17/2021] [Accepted: 09/28/2021] [Indexed: 11/28/2022]
Abstract
Impaired eye movements in multiple sclerosis (MS) and functional connectivity (FC) Eye movements related to altered FC of the oculomotor brain network. Lower (beta band) and higher (theta/delta band) FC related to abnormal eye movements. Regional changes were more informative than whole-network measures. Eye movement parameters also related to disability and cognitive dysfunction.
Background Impaired eye movements in multiple sclerosis (MS) are common and could represent a non-invasive and accurate measure of (dys)functioning of interconnected areas within the complex brain network. The aim of this study was to test whether altered saccadic eye movements are related to changes in functional connectivity (FC) in patients with MS. Methods Cross-sectional eye movement (pro-saccades and anti-saccades) and magnetoencephalography (MEG) data from the Amsterdam MS cohort were included from 176 MS patients and 33 healthy controls. FC was calculated between all regions of the Brainnetome atlas in six conventional frequency bands. Cognitive function and disability were evaluated by previously validated measures. The relationships between saccadic parameters and both FC and clinical scores in MS patients were analysed using multivariate linear regression models. Results In MS pro- and anti-saccades were abnormal compared to healthy controls A relationship of saccadic eye movements was found with FC of the oculomotor network, which was stronger for regional than global FC. In general, abnormal eye movements were related to higher delta and theta FC but lower beta FC. Strongest associations were found for pro-saccadic latency and FC of the precuneus (beta band β = -0.23, p = .006), peak velocity and FC of the parietal eye field (theta band β = -0.25, p = .005) and gain and FC of the inferior frontal eye field (theta band β = -0.25, p = .003). Pro-saccadic latency was also strongly associated with disability scores and cognitive dysfunction. Conclusions Impaired saccadic eye movements were related to functional connectivity of the oculomotor network and clinical performance in MS. This study also showed that, in addition to global network connectivity, studying regional changes in MEG studies could yield stronger correlations.
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Affiliation(s)
- J A Nij Bijvank
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Ophthalmology, Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - E M M Strijbis
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - I M Nauta
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - S D Kulik
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, the Netherlands
| | - L J Balk
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - C J Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - A Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - J J G Geurts
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, the Netherlands
| | - B M J Uitdehaag
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - L J van Rijn
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Ophthalmology, Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands; Onze Lieve Vrouwe Gasthuis, Department of Ophthalmology, Amsterdam, the Netherlands
| | - A Petzold
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, MS Center and Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Ophthalmology, Neuro-ophthalmology Expertise Center, Amsterdam Neuroscience, Amsterdam, the Netherlands; Moorfields Eye Hospital, The National Hospital for Neurology and Neurosurgery and the UCL Queen Square Institute of Neurology, London, United Kingdom
| | - M M Schoonheim
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, the Netherlands
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17
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Douw L, Nissen IA, Fitzsimmons SMDD, Santos FAN, Hillebrand A, van Straaten ECW, Stam CJ, De Witt Hamer PC, Baayen JC, Klein M, Reijneveld JC, Heyer DB, Verhoog MB, Wilbers R, Hunt S, Mansvelder HD, Geurts JJG, de Kock CPJ, Goriounova NA. Cellular Substrates of Functional Network Integration and Memory in Temporal Lobe Epilepsy. Cereb Cortex 2021; 32:2424-2436. [PMID: 34564728 PMCID: PMC9157285 DOI: 10.1093/cercor/bhab349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/19/2021] [Accepted: 08/22/2021] [Indexed: 11/12/2022] Open
Abstract
Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.
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Affiliation(s)
- Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands.,Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 02129 MA, Charlestown, USA
| | - Ida A Nissen
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Sophie M D D Fitzsimmons
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Fernando A N Santos
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Philip C De Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Jaap C Reijneveld
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands.,Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede 2103 SW, Heemstede, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Matthijs B Verhoog
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands.,Department of Human Biology, Division of Cell Biology, Neuroscience Institute, University of Cape Town, 7935, Cape Town, South Africa
| | - René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Sarah Hunt
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
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18
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Elliott C, Momayyezsiahkal P, Arnold DL, Liu D, Ke J, Zhu L, Zhu B, George IC, Bradley DP, Fisher E, Cahir-McFarland E, Stys PK, Geurts JJG, Franchimont N, Gafson A, Belachew S. Abnormalities in normal-appearing white matter from which multiple sclerosis lesions arise. Brain Commun 2021; 3:fcab176. [PMID: 34557664 PMCID: PMC8453433 DOI: 10.1093/braincomms/fcab176] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 11/24/2022] Open
Abstract
Normal-appearing white matter is far from normal in multiple sclerosis; little is known about the precise pathology or spatial pattern of this alteration and its relation to subsequent lesion formation. This study was undertaken to evaluate normal-appearing white matter abnormalities in brain areas where multiple sclerosis lesions subsequently form, and to investigate the spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis. Brain MRIs of pre-lesion normal-appearing white matter were analysed in participants with new T2 lesions, pooled from three clinical trials: SYNERGY (NCT01864148; n = 85 with relapsing multiple sclerosis) was the test data set; ASCEND (NCT01416181; n = 154 with secondary progressive multiple sclerosis) and ADVANCE (NCT00906399; n = 261 with relapsing-remitting multiple sclerosis) were used as validation data sets. Focal normal-appearing white matter tissue state was analysed prior to lesion formation in areas where new T2 lesions later formed (pre-lesion normal-appearing white matter) using normalized magnetization transfer ratio and T2-weighted (nT2) intensities, and compared with overall normal-appearing white matter and spatially matched contralateral normal-appearing white matter. Each outcome was analysed using linear mixed-effects models. Follow-up time (as a categorical variable), patient-level characteristics (including treatment group) and other baseline variables were treated as fixed effects. In SYNERGY, nT2 intensity was significantly higher, and normalized magnetization transfer ratio was lower in pre-lesion normal-appearing white matter versus overall and contralateral normal-appearing white matter at all time points up to 24 weeks before new T2 lesion onset. In ASCEND and ADVANCE (for which normalized magnetization transfer ratio was not available), nT2 intensity in pre-lesion normal-appearing white matter was significantly higher compared to both overall and contralateral normal-appearing white matter at all pre-lesion time points extending up to 2 years prior to lesion formation. In all trials, nT2 intensity in the contralateral normal-appearing white matter was also significantly higher at all pre-lesion time points compared to overall normal-appearing white matter. Brain atlases of normal-appearing white matter abnormalities were generated using measures of voxel-wise differences in normalized magnetization transfer ratio of normal-appearing white matter in persons with multiple sclerosis compared to scanner-matched healthy controls. We observed that overall spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis largely recapitulated the anatomical distribution of probabilities of T2 hyperintense lesions. Overall, these findings suggest that intrinsic spatial properties and/or longstanding precursory abnormalities of normal-appearing white matter tissue may contribute to the risk of autoimmune acute demyelination in multiple sclerosis.
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Affiliation(s)
| | - Parya Momayyezsiahkal
- NeuroRx Research, Montreal, QC H2X 3P9, Canada.,McGill University, Montreal, QC H3A 0G4, Canada
| | - Douglas L Arnold
- NeuroRx Research, Montreal, QC H2X 3P9, Canada.,McGill University, Montreal, QC H3A 0G4, Canada
| | - Dawei Liu
- Biogen Digital Health, Biogen, Cambridge, MA 02142, USA
| | - Jun Ke
- Biogen, Cambridge, MA 02142, USA
| | - Li Zhu
- Biogen, Cambridge, MA 02142, USA
| | - Bing Zhu
- Biogen, Cambridge, MA 02142, USA
| | - Ilena C George
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | | | | | - Peter K Stys
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, 1081 HV Amsterdam, Netherlands
| | | | - Arie Gafson
- Biogen Digital Health, Biogen, Cambridge, MA 02142, USA
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19
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Numan T, Kulik SD, Moraal B, Reijneveld JC, Stam CJ, de Witt Hamer PC, Derks J, Bruynzeel AME, van Linde ME, Wesseling P, Kouwenhoven MCM, Klein M, Würdinger T, Barkhof F, Geurts JJG, Hillebrand A, Douw L. Non-invasively measured brain activity and radiological progression in diffuse glioma. Sci Rep 2021; 11:18990. [PMID: 34556701 PMCID: PMC8460818 DOI: 10.1038/s41598-021-97818-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 08/20/2021] [Indexed: 01/25/2023] Open
Abstract
Non-invasively measured brain activity is related to progression-free survival in glioma patients, suggesting its potential as a marker of glioma progression. We therefore assessed the relationship between brain activity and increasing tumor volumes on routine clinical magnetic resonance imaging (MRI) in glioma patients. Postoperative magnetoencephalography (MEG) was recorded in 45 diffuse glioma patients. Brain activity was estimated using three measures (absolute broadband power, offset and slope) calculated at three spatial levels: global average, averaged across the peritumoral areas, and averaged across the homologues of these peritumoral areas in the contralateral hemisphere. Tumors were segmented on MRI. Changes in tumor volume between the two scans surrounding the MEG were calculated and correlated with brain activity. Brain activity was compared between patient groups classified into having increasing or stable tumor volume. Results show that brain activity was significantly increased in the tumor hemisphere in general, and in peritumoral regions specifically. However, none of the measures and spatial levels of brain activity correlated with changes in tumor volume, nor did they differ between patients with increasing versus stable tumor volumes. Longitudinal studies in more homogeneous subgroups of glioma patients are necessary to further explore the clinical potential of non-invasively measured brain activity.
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Affiliation(s)
- T Numan
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, O
- 2 building 13W09, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - S D Kulik
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, O
- 2 building 13W09, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - B Moraal
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J C Reijneveld
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - C J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - P C de Witt Hamer
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J Derks
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, O
- 2 building 13W09, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - A M E Bruynzeel
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Radiotherapy, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M E van Linde
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - P Wesseling
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Pathology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M C M Kouwenhoven
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M Klein
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - T Würdinger
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - F Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - J J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, O
- 2 building 13W09, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands
| | - A Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - L Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, O
- 2 building 13W09, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands. .,Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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20
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Moors TE, Maat CA, Niedieker D, Mona D, Petersen D, Timmermans-Huisman E, Kole J, El-Mashtoly SF, Spycher L, Zago W, Barbour R, Mundigl O, Kaluza K, Huber S, Hug MN, Kremer T, Ritter M, Dziadek S, Geurts JJG, Gerwert K, Britschgi M, van de Berg WDJ. The subcellular arrangement of alpha-synuclein proteoforms in the Parkinson's disease brain as revealed by multicolor STED microscopy. Acta Neuropathol 2021; 142:423-448. [PMID: 34115198 PMCID: PMC8357756 DOI: 10.1007/s00401-021-02329-9] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 05/11/2021] [Accepted: 05/12/2021] [Indexed: 12/18/2022]
Abstract
Various post-translationally modified (PTM) proteoforms of alpha-synuclein (aSyn)-including C-terminally truncated (CTT) and Serine 129 phosphorylated (Ser129-p) aSyn-accumulate in Lewy bodies (LBs) in different regions of the Parkinson's disease (PD) brain. Insight into the distribution of these proteoforms within LBs and subcellular compartments may aid in understanding the orchestration of Lewy pathology in PD. We applied epitope-specific antibodies against CTT and Ser129-p aSyn proteoforms and different aSyn domains in immunohistochemical multiple labelings on post-mortem brain tissue from PD patients and non-neurological, aged controls, which were scanned using high-resolution 3D multicolor confocal and stimulated emission depletion (STED) microscopy. Our multiple labeling setup highlighted a consistent onion skin-type 3D architecture in mature nigral LBs in which an intricate and structured-appearing framework of Ser129-p aSyn and cytoskeletal elements encapsulates a core enriched in CTT aSyn species. By label-free CARS microscopy we found that enrichments of proteins and lipids were mainly localized to the central portion of nigral aSyn-immunopositive (aSyn+) inclusions. Outside LBs, we observed that 122CTT aSyn+ punctae localized at mitochondrial membranes in the cytoplasm of neurons in PD and control brains, suggesting a physiological role for 122CTT aSyn outside of LBs. In contrast, very limited to no Ser129-p aSyn immunoreactivity was observed in brains of non-neurological controls, while the alignment of Ser129-p aSyn in a neuronal cytoplasmic network was characteristic for brains with (incidental) LB disease. Interestingly, Ser129-p aSyn+ network profiles were not only observed in neurons containing LBs but also in neurons without LBs particularly in donors at early disease stage, pointing towards a possible subcellular pathological phenotype preceding LB formation. Together, our high-resolution and 3D multicolor microscopy observations in the post-mortem human brain provide insights into potential mechanisms underlying a regulated LB morphogenesis.
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21
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Huiskamp M, Eijlers AJC, Broeders TAA, Pasteuning J, Dekker I, Uitdehaag BMJ, Barkhof F, Wink AM, Geurts JJG, Hulst HE, Schoonheim MM. Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis. Neurology 2021; 97:e794-e802. [PMID: 34099528 PMCID: PMC8397585 DOI: 10.1212/wnl.0000000000012341] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 05/17/2021] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE To characterize functional network changes related to conversion to cognitive impairment in a large sample of patients with multiple sclerosis (MS) over a period of 5 years. METHODS Two hundred twenty-seven patients with MS and 59 healthy controls of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at 2 time points (time interval 4.9 ± 0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP; n = 123), mildly impaired (MCI; z < -1.5 on ≥2 cognitive tests, n = 32), or impaired (CI; z < -2 on ≥2 tests, n = 72), and longitudinal conversion between groups was determined. Network function was quantified with eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time points. RESULTS Over time, 18.9% of patients converted to a worse phenotype; 22 of 123 patients who were CP (17.9%) converted from CP to MCI, 10 of 123 from CP to CI (8.1%), and 12 of 32 patients with MCI converted to CI (37.5%). At baseline, default-mode network (DMN) centrality was higher in CI individuals compared to controls (p = 0.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (p < 0.05). CONCLUSIONS Of all patients, 19% worsened in their cognitive status over 5 years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting toward DMN dysfunction in CI. Because the VAN normally relays information to the DMN, these results could indicate that in MS normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress.
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Affiliation(s)
- Marijn Huiskamp
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK.
| | - Anand J C Eijlers
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Tommy A A Broeders
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jasmin Pasteuning
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Iris Dekker
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Bernard M J Uitdehaag
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Frederik Barkhof
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Alle-Meije Wink
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jeroen J G Geurts
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Hanneke E Hulst
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Menno M Schoonheim
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
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22
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Preziosa P, Bouman PM, Kiljan S, Steenwijk MD, Meani A, Pouwels PJ, Rocca MA, Filippi M, Geurts JJG, Jonkman LE. Neurite density explains cortical T1-weighted/T2-weighted ratio in multiple sclerosis. J Neurol Neurosurg Psychiatry 2021; 92:790-792. [PMID: 33436500 DOI: 10.1136/jnnp-2020-324391] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 11/16/2020] [Accepted: 12/16/2020] [Indexed: 11/03/2022]
Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Piet M Bouman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Svenja Kiljan
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Petra J Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
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23
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't Hart BA, Luchicchi A, Schenk GJ, Stys PK, Geurts JJG. Mechanistic underpinning of an inside-out concept for autoimmunity in multiple sclerosis. Ann Clin Transl Neurol 2021; 8:1709-1719. [PMID: 34156169 PMCID: PMC8351380 DOI: 10.1002/acn3.51401] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 04/27/2021] [Accepted: 05/20/2021] [Indexed: 12/16/2022] Open
Abstract
The neuroinflammatory disease multiple sclerosis is driven by autoimmune pathology in the central nervous system. However, the trigger of the autoimmune pathogenic process is unknown. MS models in immunologically naïve, specific‐pathogen‐free bred rodents support an exogenous trigger, such as an infection. The validity of this outside–in pathogenic concept for MS has been frequently challenged by the difficulty to translate pathogenic concepts developed in these models into effective therapies for the MS patient. Studies in well‐validated non‐human primate multiple sclerosis models where, just like in humans, the autoimmune pathogenic process develops from an experienced immune system trained by prior infections, rather support an endogenous trigger. Data reviewed here corroborate the validity of this inside–out pathogenic concept for multiple sclerosis. They also provide a plausible sequence of events reminiscent of Wilkin’s primary lesion theory: (i) that autoimmunity is a physiological response of the immune system against excess antigen turnover in diseased tissue (the primary lesion) and (ii) that individuals developing autoimmune disease are (genetically predisposed) high responders against critical antigens. Data obtained in multiple sclerosis brains reveal the presence in normally appearing white matter of myelinated axons where myelin sheaths have locally dissociated from their enwrapped axon (i.e., blistering). The ensuing disintegration of axon–myelin units potentially causes the excess systemic release of post‐translationally modified myelin. Data obtained in a unique primate multiple sclerosis model revealed a core pathogenic role of T cells present in the normal repertoire, which hyper‐react to post‐translationally modified (citrullinated) myelin–oligodendrocyte glycoprotein and evoke clinical and pathological aspects of multiple sclerosis.
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Affiliation(s)
- Bert A 't Hart
- Department Anatomy and Neuroscience, University Medical Center Amsterdam, Amsterdam, The Netherlands.,Department Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center, Groningen, The Netherlands
| | - Antonio Luchicchi
- Department Anatomy and Neuroscience, University Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department Anatomy and Neuroscience, University Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Peter K Stys
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, Canada
| | - Jeroen J G Geurts
- Department Anatomy and Neuroscience, University Medical Center Amsterdam, Amsterdam, The Netherlands
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24
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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25
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Derks J, Kulik SD, Numan T, de Witt Hamer PC, Noske DP, Klein M, Geurts JJG, Reijneveld JC, Stam CJ, Schoonheim MM, Hillebrand A, Douw L. Understanding Global Brain Network Alterations in Glioma Patients. Brain Connect 2021; 11:865-874. [PMID: 33947274 DOI: 10.1089/brain.2020.0801] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Introduction: Glioma patients show increased global brain network clustering related to poorer cognition and epilepsy. However, it is unclear whether this increase is spatially widespread, localized in the (peri)tumor region only, or decreases with distance from the tumor. Materials and Methods: Weighted global and local brain network clustering was determined in 71 glioma patients and 53 controls by using magnetoencephalography. Tumor clustering was determined by averaging local clustering of regions overlapping with the tumor, and vice versa for non-tumor regions. Euclidean distance was determined from the tumor centroid to the centroids of other regions. Results: Patients showed higher global clustering compared with controls. Clustering of tumor and non-tumor regions did not differ, and local clustering was not associated with distance from the tumor. Post hoc analyses revealed that in the patient group, tumors were located more often in regions with higher clustering in controls, but it seemed that tumors of patients with high global clustering were located more often in regions with lower clustering in controls. Conclusions: Glioma patients show non-local network disturbances. Tumors of patients with high global clustering may have a preferred localization, namely regions with lower clustering in controls, suggesting that tumor localization relates to the extent of network disruption. Impact statement This work uses the innovative framework of network neuroscience to investigate functional connectivity patterns associated with brain tumors. Glioma (primary brain tumor) patients experience cognitive deficits and epileptic seizures, which have been related to brain network alterations. This study shows that glioma patients have a spatially widespread increase in global network clustering, which cannot be attributed to local effects of the tumor. Moreover, tumors occur more often in brain regions with higher network clustering in controls. This study emphasizes the global character of network alterations in glioma patients and suggests that preferred tumor locations are characterized by particular network profiles.
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Affiliation(s)
- Jolanda Derks
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Shanna D Kulik
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Tianne Numan
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip C de Witt Hamer
- Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurosurgery, Overarching Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - David P Noske
- Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurosurgery, Overarching Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Martin Klein
- Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Medical Psychology, and Overarching Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jaap C Reijneveld
- Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Overarching Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging/Massachusetts General Hospital, Charlestown, Massachusetts, USA
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26
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Broeders TAA, Schoonheim MM, Vink M, Douw L, Geurts JJG, van Leeuwen JMC, Vinkers CH. Dorsal attention network centrality increases during recovery from acute stress exposure. Neuroimage Clin 2021; 31:102721. [PMID: 34134017 PMCID: PMC8214139 DOI: 10.1016/j.nicl.2021.102721] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 05/19/2021] [Accepted: 06/04/2021] [Indexed: 12/17/2022]
Abstract
Stress is a major risk factor for the development of almost all psychiatric disorders. In addition to the acute stress response, an efficient recovery in the aftermath of stress is important for optimal resilience. Increased stress vulnerability across psychiatric disorders may therefore be related to altered trajectories during the recovery phase following stress. Such recovery trajectories can be quantified by changes in functional brain networks. This study therefore evaluated longitudinal functional network changes related to stress in healthy individuals (N = 80), individuals at risk for psychiatric disorders (healthy siblings of schizophrenia patients) (N = 39), and euthymic bipolar I disorder (BD) patients (N = 36). Network changes were evaluated before and at 20 and 90 min after onset of an experimental acute stress task (Trier Social Stress Test) or a control condition. Whole-brain functional networks were analyzed using eigenvector centrality as a proxy for network importance, centrality change over time was related to the acute stress response and recovery for each group. In healthy individuals, centrality of the dorsal attention network (DAN; p = 0.007) changed over time in relation to stress. More specifically, DAN centrality increased during the recovery phase after acute stress exposure (p = 0.020), while no DAN centrality change was observed during the initial stress response (p = 0.626). Such increasing DAN centrality during stress recovery was also found in healthy siblings (p = 0.016), but not in BD patients (p = 0.554). This study highlights that temporally complex and precise changes in network configuration are vital to understand the response to and recovery from stress.
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Affiliation(s)
- T A A Broeders
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - M M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M Vink
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Experimental, Utrecht University, Utrecht, The Netherlands; Department Developmental Psychology, Utrecht University, Utrecht, The Netherlands
| | - L Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J M C van Leeuwen
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - C H Vinkers
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
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27
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van Olst L, Rodriguez-Mogeda C, Picon C, Kiljan S, James RE, Kamermans A, van der Pol SMA, Knoop L, Michailidou I, Drost E, Franssen M, Schenk GJ, Geurts JJG, Amor S, Mazarakis ND, van Horssen J, de Vries HE, Reynolds R, Witte ME. Meningeal inflammation in multiple sclerosis induces phenotypic changes in cortical microglia that differentially associate with neurodegeneration. Acta Neuropathol 2021; 141:881-899. [PMID: 33779783 PMCID: PMC8113309 DOI: 10.1007/s00401-021-02293-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/15/2021] [Accepted: 03/03/2021] [Indexed: 12/21/2022]
Abstract
Meningeal inflammation strongly associates with demyelination and neuronal loss in the underlying cortex of progressive MS patients, thereby contributing significantly to clinical disability. However, the pathological mechanisms of meningeal inflammation-induced cortical pathology are still largely elusive. By extensive analysis of cortical microglia in post-mortem progressive MS tissue, we identified cortical areas with two MS-specific microglial populations, termed MS1 and MS2 cortex. The microglial population in MS1 cortex was characterized by a higher density and increased expression of the activation markers HLA class II and CD68, whereas microglia in MS2 cortex showed increased morphological complexity and loss of P2Y12 and TMEM119 expression. Interestingly, both populations associated with inflammation of the overlying meninges and were time-dependently replicated in an in vivo rat model for progressive MS-like chronic meningeal inflammation. In this recently developed animal model, cortical microglia at 1-month post-induction of experimental meningeal inflammation resembled microglia in MS1 cortex, and microglia at 2 months post-induction acquired a MS2-like phenotype. Furthermore, we observed that MS1 microglia in both MS cortex and the animal model were found closely apposing neuronal cell bodies and to mediate pre-synaptic displacement and phagocytosis, which coincided with a relative sparing of neurons. In contrast, microglia in MS2 cortex were not involved in these synaptic alterations, but instead associated with substantial neuronal loss. Taken together, our results show that in response to meningeal inflammation, microglia acquire two distinct phenotypes that differentially associate with neurodegeneration in the progressive MS cortex. Furthermore, our in vivo data suggests that microglia initially protect neurons from meningeal inflammation-induced cell death by removing pre-synapses from the neuronal soma, but eventually lose these protective properties contributing to neuronal loss.
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Affiliation(s)
- Lynn van Olst
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Carla Rodriguez-Mogeda
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Carmen Picon
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Rachel E James
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Alwin Kamermans
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Susanne M A van der Pol
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Lydian Knoop
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Iliana Michailidou
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Evelien Drost
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Marc Franssen
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Sandra Amor
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Nicholas D Mazarakis
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Jack van Horssen
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Helga E de Vries
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
- Department of Medical Biochemistry, Amsterdam UMC, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - Richard Reynolds
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK.
- Centre for Molecular Neuropathology, LKC School of Medicine, Nanyang Technological University, Singapore, Singapore.
| | - Maarten E Witte
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.
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28
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Strik M, Cofré Lizama LE, Shanahan CJ, van der Walt A, Boonstra FMC, Glarin R, Kilpatrick TJ, Geurts JJG, Cleary JO, Schoonheim MM, Galea MP, Kolbe SC. Axonal loss in major sensorimotor tracts is associated with impaired motor performance in minimally disabled multiple sclerosis patients. Brain Commun 2021; 3:fcab032. [PMID: 34222866 PMCID: PMC8244644 DOI: 10.1093/braincomms/fcab032] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/15/2020] [Accepted: 01/11/2021] [Indexed: 12/13/2022] Open
Abstract
Multiple sclerosis is a neuroinflammatory disease of the CNS that is associated with significant irreversible neuro-axonal loss, leading to permanent disability. There is thus an urgent need for in vivo markers of axonal loss for use in patient monitoring or as end-points for trials of neuroprotective agents. Advanced diffusion MRI can provide markers of diffuse loss of axonal fibre density or atrophy within specific white matter pathways. These markers can be interrogated in specific white matter tracts that underpin important functional domains such as sensorimotor function. This study aimed to evaluate advanced diffusion MRI markers of axonal loss within the major sensorimotor tracts of the brain, and to correlate the degree of axonal loss in these tracts to precise kinematic measures of hand and foot motor control and gait in minimally disabled people with multiple sclerosis. Twenty-eight patients (Expanded Disability Status Scale < 4, and Kurtzke Functional System Scores for pyramidal and cerebellar function ≤ 2) and 18 healthy subjects underwent ultra-high field 7 Tesla diffusion MRI for calculation of fibre-specific measures of axonal loss (fibre density, reflecting diffuse axonal loss and fibre cross-section reflecting tract atrophy) within three tracts: cortico-spinal tract, interhemispheric sensorimotor tract and cerebello-thalamic tracts. A visually guided force-matching task involving either the hand or foot was used to assess visuomotor control, and three-dimensional marker-based video tracking was used to assess gait. Fibre-specific axonal markers for each tract were compared between groups and correlated with visuomotor task performance (force error and lag) and gait parameters (stance, stride length, step width, single and double support) in patients. Patients displayed significant regional loss of fibre cross-section with minimal loss of fibre density in all tracts of interest compared to healthy subjects (family-wise error corrected p-value < 0.05), despite relatively few focal lesions within these tracts. In patients, reduced axonal fibre density and cross-section within the corticospinal tracts and interhemispheric sensorimotor tracts were associated with larger force tracking error and gait impairments (shorter stance, smaller step width and longer double support) (family-wise error corrected p-value < 0.05). In conclusion, significant gait and motor control impairments can be detected in minimally disabled people with multiple sclerosis that correlated with axonal loss in major sensorimotor pathways of the brain. Given that axonal loss is irreversible, the combined use of advanced imaging and kinematic markers could be used to identify patients at risk of more severe motor impairments as they emerge for more aggressive therapeutic interventions.
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Affiliation(s)
- Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - L Eduardo Cofré Lizama
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- School of Allied Health, Human Services and Sports, La Trobe University, Victoria 3086, Australia
| | - Camille J Shanahan
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Anneke van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Frederique M C Boonstra
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Rebecca Glarin
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Trevor J Kilpatrick
- Florey Institute of Neuroscience and Mental Health, Parkville 3052, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville 3050, Australia
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Jon O Cleary
- Department of Radiology, Guy’s and St. Thomas’ NHS Foundation Trust, London SE1 7EH, UK
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Mary P Galea
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Scott C Kolbe
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
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29
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Strik M, Shanahan CJ, van der Walt A, Boonstra FMC, Glarin R, Galea MP, Kilpatrick TJ, Geurts JJG, Cleary JO, Schoonheim MM, Kolbe SC. Functional correlates of motor control impairments in multiple sclerosis: A 7 Tesla task functional MRI study. Hum Brain Mapp 2021; 42:2569-2582. [PMID: 33666314 PMCID: PMC8090767 DOI: 10.1002/hbm.25389] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/10/2021] [Accepted: 02/16/2021] [Indexed: 02/01/2023] Open
Abstract
Upper and lower limb impairments are common in people with multiple sclerosis (pwMS), yet difficult to clinically identify in early stages of disease progression. Tasks involving complex motor control can potentially reveal more subtle deficits in early stages, and can be performed during functional MRI (fMRI) acquisition, to investigate underlying neural mechanisms, providing markers for early motor progression. We investigated brain activation during visually guided force matching of hand or foot in 28 minimally disabled pwMS (Expanded Disability Status Scale (EDSS) < 4 and pyramidal and cerebellar Kurtzke Functional Systems Scores ≤ 2) and 17 healthy controls (HC) using ultra‐high field 7‐Tesla fMRI, allowing us to visualise sensorimotor network activity in high detail. Task activations and performance (tracking lag and error) were compared between groups, and correlations were performed. PwMS showed delayed (+124 s, p = .002) and more erroneous (+0.15 N, p = .001) lower limb tracking, together with lower cerebellar, occipital and superior parietal cortical activation compared to HC. Lower activity within these regions correlated with worse EDSS (p = .034), lower force error (p = .006) and higher lesion load (p < .05). Despite no differences in upper limb task performance, pwMS displayed lower inferior occipital cortical activation. These results demonstrate that ultra‐high field fMRI during complex hand and foot tracking can identify subtle impairments in lower limb movements and upper and lower limb brain activity, and differentiates upper and lower limb impairments in minimally disabled pwMS.
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Affiliation(s)
- Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia.,Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Camille J Shanahan
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Anneke van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
| | - Frederique M C Boonstra
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
| | - Rebecca Glarin
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Mary P Galea
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Trevor J Kilpatrick
- Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia.,Department of Neurology, Royal Melbourne Hospital, Parkville, Australia
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jon O Cleary
- Department of Radiology, Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Scott C Kolbe
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia.,Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
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30
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de Boer NS, de Bruin LC, Geurts JJG, Glas G. The Network Theory of Psychiatric Disorders: A Critical Assessment of the Inclusion of Environmental Factors. Front Psychol 2021; 12:623970. [PMID: 33613399 PMCID: PMC7890010 DOI: 10.3389/fpsyg.2021.623970] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/18/2021] [Indexed: 11/13/2022] Open
Abstract
Borsboom and colleagues have recently proposed a "network theory" of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an "extended" network theory provide? The aim of this article is to critically examine what explanatory strategies the network theory that includes both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward's interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations.
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Affiliation(s)
- Nina S de Boer
- Department of Philosophy, Radboud University, Nijmegen, Netherlands
| | - Leon C de Bruin
- Department of Philosophy, Radboud University, Nijmegen, Netherlands.,Department of Philosophy, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam University Medical Centers (Location VUmc), Amsterdam, Netherlands
| | - Gerrit Glas
- Department of Philosophy, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Department of Anatomy and Neurosciences, Amsterdam University Medical Centers (Location VUmc), Amsterdam, Netherlands
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31
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Teo W, Caprariello AV, Morgan ML, Luchicchi A, Schenk GJ, Joseph JT, Geurts JJG, Stys PK. Nile Red fluorescence spectroscopy reports early physicochemical changes in myelin with high sensitivity. Proc Natl Acad Sci U S A 2021; 118:e2016897118. [PMID: 33593907 PMCID: PMC7923366 DOI: 10.1073/pnas.2016897118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The molecular composition of myelin membranes determines their structure and function. Even minute changes to the biochemical balance can have profound consequences for axonal conduction and the synchronicity of neural networks. Hypothesizing that the earliest indication of myelin injury involves changes in the composition and/or polarity of its constituent lipids, we developed a sensitive spectroscopic technique for defining the chemical polarity of myelin lipids in fixed frozen tissue sections from rodent and human. The method uses a simple staining procedure involving the lipophilic dye Nile Red, whose fluorescence spectrum varies according to the chemical polarity of the microenvironment into which the dye embeds. Nile Red spectroscopy identified histologically intact yet biochemically altered myelin in prelesioned tissues, including mouse white matter following subdemyelinating cuprizone intoxication, as well as normal-appearing white matter in multiple sclerosis brain. Nile Red spectroscopy offers a relatively simple yet highly sensitive technique for detecting subtle myelin changes.
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Affiliation(s)
- Wulin Teo
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada
| | - Andrew V Caprariello
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada
| | - Megan L Morgan
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada
| | - Antonio Luchicchi
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, 1081 HZ Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, 1081 HZ Amsterdam, The Netherlands
| | - Jeffrey T Joseph
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, 1081 HZ Amsterdam, The Netherlands
| | - Peter K Stys
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada;
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Bouman PM, Steenwijk MD, Pouwels PJW, Schoonheim MM, Barkhof F, Jonkman LE, Geurts JJG. Histopathology-validated recommendations for cortical lesion imaging in multiple sclerosis. Brain 2021; 143:2988-2997. [PMID: 32889535 PMCID: PMC7586087 DOI: 10.1093/brain/awaa233] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/10/2020] [Accepted: 06/01/2020] [Indexed: 11/30/2022] Open
Abstract
Cortical demyelinating lesions are clinically important in multiple sclerosis, but notoriously difficult to visualize with MRI. At clinical field strengths, double inversion recovery MRI is most sensitive, but still only detects 18% of all histopathologically validated cortical lesions. More recently, phase-sensitive inversion recovery was suggested to have a higher sensitivity than double inversion recovery, although this claim was not histopathologically validated. Therefore, this retrospective study aimed to provide clarity on this matter by identifying which MRI sequence best detects histopathologically-validated cortical lesions at clinical field strength, by comparing sensitivity and specificity of the thus far most commonly used MRI sequences, which are T2, fluid-attenuated inversion recovery (FLAIR), double inversion recovery and phase-sensitive inversion recovery. Post-mortem MRI was performed on non-fixed coronal hemispheric brain slices of 23 patients with progressive multiple sclerosis directly after autopsy, at 3 T, using T1 and proton-density/T2-weighted, as well as FLAIR, double inversion recovery and phase-sensitive inversion recovery sequences. A total of 93 cortical tissue blocks were sampled from these slices. Blinded to histopathology, all MRI sequences were consensus scored for cortical lesions. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesion types I–IV (mixed grey matter/white matter, intracortical, subpial and cortex-spanning lesions, respectively). MRI scores were compared to histopathological scores to calculate sensitivity and specificity per sequence. Next, a retrospective (unblinded) scoring was performed to explore maximum scoring potential per sequence. Histopathologically, 224 cortical lesions were detected, of which the majority were subpial. In a mixed model, sensitivity of T1, proton-density/T2, FLAIR, double inversion recovery and phase-sensitive inversion recovery was 8.9%, 5.4%, 5.4%, 22.8% and 23.7%, respectively (20, 12, 12, 51 and 53 cortical lesions). Specificity of the prospective scoring was 80.0%, 75.0%, 80.0%, 91.1% and 88.3%. Sensitivity and specificity did not significantly differ between double inversion recovery and phase-sensitive inversion recovery, while phase-sensitive inversion recovery identified more lesions than double inversion recovery upon retrospective analysis (126 versus 95; P < 0.001). We conclude that, at 3 T, double inversion recovery and phase-sensitive inversion recovery sequences outperform conventional sequences T1, proton-density/T2 and FLAIR. While their overall sensitivity does not exceed 25%, double inversion recovery and phase-sensitive inversion recovery are highly pathologically specific when using existing scoring criteria and their use is recommended for optimal cortical lesion assessment in multiple sclerosis.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.,UCL Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
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Luchicchi A, Hart B, Frigerio I, van Dam AM, Perna L, Offerhaus HL, Stys PK, Schenk GJ, Geurts JJG. Axon-Myelin Unit Blistering as Early Event in MS Normal Appearing White Matter. Ann Neurol 2021; 89:711-725. [PMID: 33410190 PMCID: PMC8048993 DOI: 10.1002/ana.26014] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 12/19/2020] [Accepted: 01/03/2021] [Indexed: 02/04/2023]
Abstract
Objective Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease of unknown etiology. Although the prevalent view regards a CD4+‐lymphocyte autoimmune reaction against myelin at the root of the disease, recent studies propose autoimmunity as a secondary reaction to idiopathic brain damage. To gain knowledge about this possibility we investigated the presence of axonal and myelinic morphological alterations, which could implicate imbalance of axon‐myelin units as primary event in MS pathogenesis. Methods Using high resolution imaging histological brain specimens from patients with MS and non‐neurological/non‐MS controls, we explored molecular changes underpinning imbalanced interaction between axon and myelin in normal appearing white matter (NAWM), a region characterized by normal myelination and absent inflammatory activity. Results In MS brains, we detected blister‐like swellings formed by myelin detachment from axons, which were substantially less frequently retrieved in non‐neurological/non‐MS controls. Swellings in MS NAWM presented altered glutamate receptor expression, myelin associated glycoprotein (MAG) distribution, and lipid biochemical composition of myelin sheaths. Changes in tethering protein expression, widening of nodes of Ranvier and altered distribution of sodium channels in nodal regions of otherwise normally myelinated axons were also present in MS NAWM. Finally, we demonstrate a significant increase, compared with controls, in citrullinated proteins in myelin of MS cases, pointing toward biochemical modifications that may amplify the immunogenicity of MS myelin. Interpretation Collectively, the impaired interaction of myelin and axons potentially leads to myelin disintegration. Conceptually, the ensuing release of (post‐translationally modified) myelin antigens may elicit a subsequent immune attack in MS. ANN NEUROL 2021;89:711–725
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Affiliation(s)
- Antonio Luchicchi
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Bert't Hart
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands.,Department Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, The Netherlands
| | - Irene Frigerio
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Anne-Marie van Dam
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Laura Perna
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Herman L Offerhaus
- Faculty of Science and Technology, University of Twente, Enschede, The Netherlands
| | - Peter K Stys
- Cummings School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Geert J Schenk
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
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Preziosa P, Bouman PM, Kiljan S, Steenwijk MD, Meani A, Pouwels PJ, Rocca MA, Filippi M, Geurts JJG, Jonkman LE. Neurite density explains cortical T1-weighted/T2-weighted ratio in multiple sclerosis. J Neurol Neurosurg Psychiatry 2021. [PMID: 33436500 DOI: 10.1136/jnnp-2020-324391.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Piet M Bouman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Svenja Kiljan
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Petra J Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
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35
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Dekker I, Schoonheim MM, Venkatraghavan V, Eijlers AJC, Brouwer I, Bron EE, Klein S, Wattjes MP, Wink AM, Geurts JJG, Uitdehaag BMJ, Oxtoby NP, Alexander DC, Vrenken H, Killestein J, Barkhof F, Wottschel V. The sequence of structural, functional and cognitive changes in multiple sclerosis. Neuroimage Clin 2020; 29:102550. [PMID: 33418173 PMCID: PMC7804841 DOI: 10.1016/j.nicl.2020.102550] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/09/2020] [Accepted: 12/20/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND As disease progression remains poorly understood in multiple sclerosis (MS), we aim to investigate the sequence in which different disease milestones occur using a novel data-driven approach. METHODS We analysed a cohort of 295 relapse-onset MS patients and 96 healthy controls, and considered 28 features, capturing information on T2-lesion load, regional brain and spinal cord volumes, resting-state functional centrality ("hubness"), microstructural tissue integrity of major white matter (WM) tracts and performance on multiple cognitive tests. We used a discriminative event-based model to estimate the sequence of biomarker abnormality in MS progression in general, as well as specific models for worsening physical disability and cognitive impairment. RESULTS We demonstrated that grey matter (GM) atrophy of the cerebellum, thalamus, and changes in corticospinal tracts are early events in MS pathology, whereas other WM tracts as well as the cognitive domains of working memory, attention, and executive function are consistently late events. The models for disability and cognition show early functional changes of the default-mode network and earlier changes in spinal cord volume compared to the general MS population. Overall, GM atrophy seems crucial due to its early involvement in the disease course, whereas WM tract integrity appears to be affected relatively late despite the early onset of WM lesions. CONCLUSION Data-driven modelling revealed the relative occurrence of both imaging and non-imaging events as MS progresses, providing insights into disease propagation mechanisms, and allowing fine-grained staging of patients for monitoring purposes.
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Affiliation(s)
- Iris Dekker
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands; Neurology, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Vikram Venkatraghavan
- Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anand J C Eijlers
- Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Iman Brouwer
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Esther E Bron
- Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Mike P Wattjes
- Dept. of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Alle Meije Wink
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Bernard M J Uitdehaag
- Neurology, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK
| | - Hugo Vrenken
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Joep Killestein
- Neurology, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands; Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK; Institute of Neurology, UCL, London, UK
| | - Viktor Wottschel
- Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands.
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36
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Poerwoatmodjo A, Schenk GJ, Geurts JJG, Luchicchi A. Cysteine Proteases and Mitochondrial Instability: A Possible Vicious Cycle in MS Myelin? Front Cell Neurosci 2020; 14:612383. [PMID: 33335477 PMCID: PMC7736044 DOI: 10.3389/fncel.2020.612383] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/12/2020] [Indexed: 12/15/2022] Open
Affiliation(s)
- Anthony Poerwoatmodjo
- Division Clinical Neurosciences, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam Universitair Medische Centra (UMC), Location Vrije Universiteit (VU) Medical Center, MS Center Amsterdam, Amsterdam, Netherlands
| | - Geert J Schenk
- Division Clinical Neurosciences, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam Universitair Medische Centra (UMC), Location Vrije Universiteit (VU) Medical Center, MS Center Amsterdam, Amsterdam, Netherlands
| | - Jeroen J G Geurts
- Division Clinical Neurosciences, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam Universitair Medische Centra (UMC), Location Vrije Universiteit (VU) Medical Center, MS Center Amsterdam, Amsterdam, Netherlands
| | - Antonio Luchicchi
- Division Clinical Neurosciences, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam Universitair Medische Centra (UMC), Location Vrije Universiteit (VU) Medical Center, MS Center Amsterdam, Amsterdam, Netherlands
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37
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Oudejans E, Luchicchi A, Strijbis EMM, Geurts JJG, van Dam AM. Is MS affecting the CNS only? Lessons from clinic to myelin pathophysiology. Neurol Neuroimmunol Neuroinflamm 2020; 8:8/1/e914. [PMID: 33234720 PMCID: PMC7803330 DOI: 10.1212/nxi.0000000000000914] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 09/23/2020] [Indexed: 01/27/2023]
Abstract
MS is regarded as a disease of the CNS where a combination of demyelination, inflammation, and axonal degeneration results in neurologic disability. However, various studies have also shown that the peripheral nervous system (PNS) can be involved in MS, expanding the consequences of this disorder outside the brain and spinal cord, and providing food for thought to the still unanswered questions about MS origin and treatment. Here, we review the emerging concept of PNS involvement in MS by looking at it from a clinical, molecular, and biochemical point of view. Clinical, pathologic, electrophysiologic, and imaging studies give evidence that the PNS is functionally affected during MS and suggest that the disease might be part of a spectrum of demyelinating disorders instead of being a distinct entity. At the molecular level, similarities between the anatomic structure of the myelin and its interaction with axons in CNS and PNS are evident. In addition, a number of biochemical alterations that affect the myelin during MS can be assumed to be shared between CNS and PNS. Involvement of the PNS as a relevant disease target in MS pathology may have consequences for reaching the diagnosis and for therapeutic approaches of patients with MS. Hence, future MS studies should pay attention to the involvement of the PNS, i.e., its myelin, in MS pathogenesis, which could advance MS research.
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Affiliation(s)
- Ellen Oudejans
- From the Department of Anatomy and Neurosciences (E.O., A.L., J.J.G.G., A.-M.v.D.), Department of Neurology (E.M.M.S.), and Department of Child Neurology (E.O.), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, the Netherlands
| | - Antonio Luchicchi
- From the Department of Anatomy and Neurosciences (E.O., A.L., J.J.G.G., A.-M.v.D.), Department of Neurology (E.M.M.S.), and Department of Child Neurology (E.O.), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, the Netherlands
| | - Eva M M Strijbis
- From the Department of Anatomy and Neurosciences (E.O., A.L., J.J.G.G., A.-M.v.D.), Department of Neurology (E.M.M.S.), and Department of Child Neurology (E.O.), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, the Netherlands
| | - Jeroen J G Geurts
- From the Department of Anatomy and Neurosciences (E.O., A.L., J.J.G.G., A.-M.v.D.), Department of Neurology (E.M.M.S.), and Department of Child Neurology (E.O.), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, the Netherlands
| | - Anne-Marie van Dam
- From the Department of Anatomy and Neurosciences (E.O., A.L., J.J.G.G., A.-M.v.D.), Department of Neurology (E.M.M.S.), and Department of Child Neurology (E.O.), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, the Netherlands.
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Benedict RHB, Amato MP, DeLuca J, Geurts JJG. Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues. Lancet Neurol 2020; 19:860-871. [PMID: 32949546 PMCID: PMC10011205 DOI: 10.1016/s1474-4422(20)30277-5] [Citation(s) in RCA: 260] [Impact Index Per Article: 65.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/14/2020] [Accepted: 07/21/2020] [Indexed: 12/15/2022]
Abstract
Multiple sclerosis is a chronic, demyelinating disease of the CNS. Cognitive impairment is a sometimes neglected, yet common, sign and symptom with a profound effect on instrumental activities of daily living. The prevalence of cognitive impairment in multiple sclerosis varies across the lifespan and might be difficult to distinguish from other causes in older age. MRI studies show that widespread changes to brain networks contribute to cognitive dysfunction, and grey matter atrophy is an early sign of potential future cognitive decline. Neuropsychological research suggests that cognitive processing speed and episodic memory are the most frequently affected cognitive domains. Narrowing evaluation to these core areas permits brief, routine assessment in the clinical setting. Owing to its brevity, reliability, and sensitivity, the Symbol Digit Modalities Test, or its computer-based analogues, can be used to monitor episodes of acute disease activity. The Symbol Digit Modalities Test can also be used in clinical trials, and data increasingly show that cognitive processing speed and memory are amenable to cognitive training interventions.
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Affiliation(s)
- Ralph H B Benedict
- Department of Neurology and Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
| | - Maria Pia Amato
- Department of Neurology, University of Florence, IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | | | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Section Clinical Neuroscience, Amsterdam UMC, Location VUmc, Vrije Universiteit, Amsterdam, Netherlands
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39
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Meijer KA, Steenwijk MD, Douw L, Schoonheim MM, Geurts JJG. Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis. Brain 2020; 143:150-160. [PMID: 31730165 PMCID: PMC6938033 DOI: 10.1093/brain/awz355] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 08/06/2019] [Accepted: 09/21/2019] [Indexed: 02/04/2023] Open
Abstract
An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length < quartile 1) and long-range (length > quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P < 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P < 0.001) and total number of fibres (z = −0.44, P < 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P < 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.
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Affiliation(s)
- Kim A Meijer
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC location VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC location VU University Medical Center, Amsterdam, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC location VU University Medical Center, Amsterdam, The Netherlands.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC location VU University Medical Center, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC location VU University Medical Center, Amsterdam, The Netherlands
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40
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van Emden MW, Geurts JJG, Schober P, Schwarte LA. Suitability and realism of the novel Fix for Life cadaver model for videolaryngoscopy and fibreoptic tracheoscopy in airway management training. BMC Anesthesiol 2020; 20:203. [PMID: 32799813 PMCID: PMC7429731 DOI: 10.1186/s12871-020-01121-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 08/06/2020] [Indexed: 11/13/2022] Open
Abstract
Background Videolaryngoscopy is increasingly advocated as the standard intubation technique, while fibreoptic intubation is broadly regarded as the ‘gold standard’ for difficult airways. Traditionally, the training of these techniques is on patients, though manikins, simulators and cadavers are also used, with their respective limitations. In this study, we investigated whether the novel ‘Fix for Life’ (F4L) cadaver model is a suitable and realistic model for the teaching of these two intubation techniques to novices in airway management. Methods Forty consultant anaesthetists and senior trainees were instructed to perform tracheal intubation with videolaryngoscopy and fibreoptic tracheoscopy in four F4L cadaver models. The primary outcome measure was the verbal rating scores (scale 1–10, higher scores indicate a better rating) for suitability and for realism of the F4L cadavers as training model for these techniques. Secondary outcomes included success rates of the procedures and the time to successful completion of the procedures. Results The mean verbal rating scores for suitability and realism for videolaryngoscopy was 8.3 (95% CI, 7.9–8.6) and 7.2 (95% CI, 6.7–7.6), respectively. For fibreoptic tracheoscopy, suitability was 8.2 (95% CI, 7.9–8.5) and realism 7.5 (95% CI, 7.1–7.8). In videolaryngoscopy, 100% of the procedures were successful. The mean (SD) time until successful tracheal intubation was 34.8 (30.9) s. For fibreoptic tracheoscopy, the success rate was 96.3%, with a mean time of 89.4 (80.1) s. Conclusions We conclude that the F4L cadaver model is a suitable and realistic model to train and teach tracheal intubation with videolaryngoscopy and fibreoptic tracheoscopy to novices in airway management training.
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Affiliation(s)
- Michael W van Emden
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081, HV, Amsterdam, The Netherlands.
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081, HV, Amsterdam, The Netherlands
| | - Patrick Schober
- Department of Anaesthesiology, Amsterdam UMC, Vrije Universiteit, De Boelelaan 1117, 1081, HV, Amsterdam, The Netherlands
| | - Lothar A Schwarte
- Department of Anaesthesiology, Amsterdam UMC, Vrije Universiteit, De Boelelaan 1117, 1081, HV, Amsterdam, The Netherlands
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Fathy YY, Hepp DH, de Jong FJ, Geurts JJG, Foncke EMJ, Berendse HW, van de Berg WDJ, Schoonheim MM. Anterior insular network disconnection and cognitive impairment in Parkinson's disease. Neuroimage Clin 2020; 28:102364. [PMID: 32781423 PMCID: PMC7417948 DOI: 10.1016/j.nicl.2020.102364] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/20/2020] [Accepted: 07/23/2020] [Indexed: 11/30/2022]
Abstract
Cognitive dysfunction in PD is related to FC of the dorsal anterior insula (dAI) In PD only, FC between the dAI and DMN was most strongly related to cognition. FC of dAI with anterior cingulate was reduced and related to cognition in PD. Increased DMN and FPN centrality is related to dAI-ACC disconnection in PD. Altered interplay between dAI, DMN, and FPN underlies poor cognition in PD.
Background The insula is a central brain hub involved in cognition and affected in Parkinson’s disease (PD). The aim of this study was to assess functional connectivity (FC) and betweenness centrality (BC) of insular sub-regions and their relationship with cognitive impairment in PD. Methods Whole-brain 3D-T1, resting-state functional MRI and a battery of cognitive tests (CAMCOG) were included for 53 PD patients and 15 controls. The insular cortex was segmented into ventral (vAI) and dorsal (dAI) anterior and posterior sub-regions. Connectivity between insular sub-regions and resting-state networks was assessed and related to cognition; BC was used to further explore nodes associated with cognition. Results Cognitive performance was significantly lower in PD patients compared to controls (p < 0.01) and was associated with FC of the dAI with default mode network (DMN) (adjusted R2 = 0.37, p < 0.001). In controls, cognitive performance was positively related to FC of the dAI with the fronto-parietal network (FPN) only (adjusted R2 = 0.5, p = 0.003). Regionally, FC of the dAI with the anterior cingulate cortex (ACC) was significantly reduced in PD (F(1,65) = 11, p = 0.002) and correlated with CAMCOG (r = 0.4, p = 0.001). DMN and FPN showed increased BC in PD which correlated with cognition and reduced connectivity of dAI with the ACC (rs = −0.33, p = 0.014 and rs = −0.44, p = 0.001 respectively). Conclusions These results highlight the relevance of the insula in cognitive dysfunction in PD. Disconnection of the dAI with ACC was related to altered centrality in the DMN and FPN only in patients. Disturbance in this network triad appears to be particularly relevant for cognitive impairment in PD.
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Affiliation(s)
- Yasmine Y Fathy
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Neurology, Erasmus Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands.
| | - Dagmar H Hepp
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Frank J de Jong
- Department of Neurology, Erasmus Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands.
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Elisabeth M J Foncke
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Henk W Berendse
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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Jonkman LE, Steenwijk MD, Boesen N, Rozemuller AJM, Barkhof F, Geurts JJG, Douw L, van de Berg WDJ. Relationship between β-amyloid and structural network topology in decedents without dementia. Neurology 2020; 95:e532-e544. [PMID: 32661099 PMCID: PMC7455348 DOI: 10.1212/wnl.0000000000009910] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 01/14/2020] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE To investigate the association between β-amyloid (Aβ) load and postmortem structural network topology in decedents without dementia. METHODS Fourteen decedents (mean age at death 72.6 ± 7.2 years) without known clinical diagnosis of neurodegenerative disease and meeting pathology criteria only for no or low Alzheimer disease (AD) pathologic change were selected from the Normal Aging Brain Collection Amsterdam database. In situ brain MRI included 3D T1-weighted images for anatomical registration and diffusion tensor imaging for probabilistic tractography with subsequent structural network construction. Network topologic measures of centrality (degree), integration (global efficiency), and segregation (clustering and local efficiency) were calculated. Tissue sections from 12 cortical regions were sampled and immunostained for Aβ and hyperphosphorylated tau (p-tau), and histopathologic burden was determined. Linear mixed effect models were used to assess the relationship between Aβ and p-tau load and network topologic measures. RESULTS Aβ was present in 79% of cases and predominantly consisted of diffuse plaques; p-tau was sparsely present. Linear mixed effect models showed independent negative associations between Aβ load and global efficiency (β = -0.83 × 10-3, p = 0.014), degree (β = -0.47, p = 0.034), and clustering (β = -0.55 × 10-2, p = 0.043). A positive association was present between Aβ load and local efficiency (β = 3.16 × 10-3, p = 0.035). Regionally, these results were significant in the posterior cingulate cortex (PCC) for degree (β = -2.22, p < 0.001) and local efficiency (β = 1.01 × 10-2, p = 0.014) and precuneus for clustering (β = -0.91 × 10-2, p = 0.017). There was no relationship between p-tau and network topology. CONCLUSION This study in deceased adults with AD-related pathologic change provides evidence for a relationship among early Aβ accumulation, predominantly of the diffuse type, and structural network topology, specifically of the PCC and precuneus.
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Affiliation(s)
- Laura E Jonkman
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK.
| | - Martijn D Steenwijk
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Nicky Boesen
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Annemieke J M Rozemuller
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Frederik Barkhof
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Jeroen J G Geurts
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Linda Douw
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
| | - Wilma D J van de Berg
- From the Departments of Anatomy and Neurosciences (L.E.J., M.D.S., N.B., J.J.G.G., L.D., W.D.J.v.d.B.), Pathology (A.J.M.R.), and Radiology and Nuclear Medicine (F.B.), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK
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Filippi M, Preziosa P, Banwell BL, Barkhof F, Ciccarelli O, De Stefano N, Geurts JJG, Paul F, Reich DS, Toosy AT, Traboulsee A, Wattjes MP, Yousry TA, Gass A, Lubetzki C, Weinshenker BG, Rocca MA. Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 2020; 142:1858-1875. [PMID: 31209474 PMCID: PMC6598631 DOI: 10.1093/brain/awz144] [Citation(s) in RCA: 267] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/19/2022] Open
Abstract
MRI has improved the diagnostic work-up of multiple sclerosis, but inappropriate image interpretation and application of MRI diagnostic criteria contribute to misdiagnosis. Some diseases, now recognized as conditions distinct from multiple sclerosis, may satisfy the MRI criteria for multiple sclerosis (e.g. neuromyelitis optica spectrum disorders, Susac syndrome), thus making the diagnosis of multiple sclerosis more challenging, especially if biomarker testing (such as serum anti-AQP4 antibodies) is not informative. Improvements in MRI technology contribute and promise to better define the typical features of multiple sclerosis lesions (e.g. juxtacortical and periventricular location, cortical involvement). Greater understanding of some key aspects of multiple sclerosis pathobiology has allowed the identification of characteristics more specific to multiple sclerosis (e.g. central vein sign, subpial demyelination and lesional rims), which are not included in the current multiple sclerosis diagnostic criteria. In this review, we provide the clinicians and researchers with a practical guide to enhance the proper recognition of multiple sclerosis lesions, including a thorough definition and illustration of typical MRI features, as well as a discussion of red flags suggestive of alternative diagnoses. We also discuss the possible place of emerging qualitative features of lesions which may become important in the near future.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Brenda L Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK.,National Institute for Health Research University College London Hospitals Biomedical Research Center, National Institute for Health Research, London, UK
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité -Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ahmed T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK
| | - Anthony Traboulsee
- MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada.,Faculty of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mike P Wattjes
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Tarek A Yousry
- Division of Neuroradiology and Neurophysics, UCL Institute of Neurology, London, UK.,Lysholm Department of Neuroradiology, London, UK
| | - Achim Gass
- Department of Neurology, Universitätsmedizin Mannheim, University of Heidelberg, Mannheim, Germany
| | - Catherine Lubetzki
- Sorbonne University, AP-HP Pitié-Salpétriére Hospital, Department of Neurology, 75013 Paris, France
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Preziosa P, Kiljan S, Steenwijk MD, Meani A, van de Berg WDJ, Schenk GJ, Rocca MA, Filippi M, Geurts JJG, Jonkman LE. Axonal degeneration as substrate of fractional anisotropy abnormalities in multiple sclerosis cortex. Brain 2020; 142:1921-1937. [PMID: 31168614 DOI: 10.1093/brain/awz143] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 03/14/2019] [Accepted: 04/09/2019] [Indexed: 12/11/2022] Open
Abstract
Cortical microstructural abnormalities are associated with clinical and cognitive deterioration in multiple sclerosis. Using diffusion tensor MRI, a higher fractional anisotropy has been found in cortical lesions versus normal-appearing cortex in multiple sclerosis. The pathological substrates of this finding have yet to be definitively elucidated. By performing a combined post-mortem diffusion tensor MRI and histopathology study, we aimed to define the histopathological substrates of diffusivity abnormalities in multiple sclerosis cortex. Sixteen subjects with multiple sclerosis and 10 age- and sex-matched non-neurological control donors underwent post-mortem in situ at 3 T MRI, followed by brain dissection. One hundred and ten paraffin-embedded tissue blocks (54 from multiple sclerosis patients, 56 from non-neurological controls) were matched to the diffusion tensor sequence to obtain regional diffusivity measures. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, astrocytes and axons, and density and volume of neurons and glial cells were evaluated. Correlates of diffusivity abnormalities with histological markers were assessed through linear mixed-effects models. Cortical lesions (77% subpial) were found in 27/54 (50%) multiple sclerosis cortical regions. Multiple sclerosis normal-appearing cortex had a significantly lower fractional anisotropy compared to cortex from non-neurological controls (P = 0.047), whereas fractional anisotropy in demyelinated cortex was significantly higher than in multiple sclerosis normal-appearing cortex (P = 0.012) but not different from non-neurological control cortex (P = 0.420). Compared to non-neurological control cortex, both multiple sclerosis normal-appearing and demyelinated cortices showed a lower density of axons perpendicular to the cortical surface (P = 0.012 for both) and of total axons (parallel and perpendicular to cortical surface) (P = 0.028 and 0.012). In multiple sclerosis, demyelinated cortex had a lower density of myelin (P = 0.004), parallel (P = 0.018) and total axons (P = 0.029) versus normal-appearing cortex. Regarding the pathological substrate, in non-neurological controls, cortical fractional anisotropy was positively associated with density of perpendicular, parallel, and total axons (P = 0.031 for all). In multiple sclerosis, normal-appearing cortex fractional anisotropy was positively associated with perpendicular and total axon density (P = 0.031 for both), while associations with myelin, glial and total cells and parallel axons did not survive multiple comparison correction. Demyelinated cortex fractional anisotropy was positively associated with density of neurons, and total cells and negatively with microglia density, without surviving multiple comparison correction. Our results suggest that a reduction of perpendicular axons in normal-appearing cortex and of both perpendicular and parallel axons in demyelinated cortex may underlie the substrate influencing cortical microstructural coherence and being responsible for the different patterns of fractional anisotropy changes occurring in multiple sclerosis cortex.
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Affiliation(s)
- Paolo Preziosa
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Alessandro Meani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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van Emden MW, Geurts JJG, Craenen AMC, Schwarte LA, Schober P. Cricothyroid membrane identification with ultrasonography and palpation in cadavers with a novel fixation technique (Fix for Life): A laboratory investigation. Eur J Anaesthesiol 2020; 37:510-512. [PMID: 32379151 PMCID: PMC7259383 DOI: 10.1097/eja.0000000000001230] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Michael W van Emden
- From the Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam (MWvE, JJGG), Department of Anaesthesiology, UMC Utrecht, Utrecht (AMCC) and Department of Anaesthesiology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands (LAS, PS)
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Belgers V, Numan T, Kulik SD, Hillebrand A, de Witt Hamer PC, Geurts JJG, Reijneveld JC, Wesseling P, Klein M, Derks J, Douw L. Postoperative oscillatory brain activity as an add-on prognostic marker in diffuse glioma. J Neurooncol 2020; 147:49-58. [PMID: 31953611 PMCID: PMC7075827 DOI: 10.1007/s11060-019-03386-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 12/27/2019] [Indexed: 12/13/2022]
Abstract
Introduction Progression-free survival (PFS) in glioma patients varies widely, even when stratifying for known predictors (i.e. age, molecular tumor subtype, presence of epilepsy, tumor grade and Karnofsky performance status). Neuronal activity has been shown to accelerate tumor growth in an animal model, suggesting that brain activity may be valuable as a PFS predictor. We investigated whether postoperative oscillatory brain activity, assessed by resting-state magnetoencephalography is of additional value when predicting PFS in glioma patients. Methods We included 27 patients with grade II–IV gliomas. Each patient’s oscillatory brain activity was estimated by calculating broadband power (0.5–48 Hz) in 56 epochs of 3.27 s and averaged over 78 cortical regions of the Automated Anatomical Labeling atlas. Cox proportional hazard analysis was performed to test the predictive value of broadband power towards PFS, adjusting for known predictors by backward elimination. Results Higher broadband power predicted shorter PFS after adjusting for known prognostic factors (n = 27; HR 2.56 (95% confidence interval (CI) 1.15–5.70); p = 0.022). Post-hoc univariate analysis showed that higher broadband power also predicted shorter overall survival (OS; n = 38; HR 1.88 (95% CI 1.00–3.54); p = 0.038). Conclusions Our findings suggest that postoperative broadband power is of additional value in predicting PFS beyond already known predictors. Electronic supplementary material The online version of this article (10.1007/s11060-019-03386-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vera Belgers
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Tianne Numan
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Shanna D Kulik
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Arjan Hillebrand
- Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Philip C de Witt Hamer
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Jeroen J G Geurts
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Jaap C Reijneveld
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Pieter Wesseling
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Pathology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Martin Klein
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Medical Psychology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Jolanda Derks
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands
| | - Linda Douw
- Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands.
- Brain Tumor Center, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, Netherlands.
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th street, Charlestown, MA, USA.
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van Wageningen TA, Vlaar E, Kooij G, Jongenelen CAM, Geurts JJG, van Dam AM. Regulation of microglial TMEM119 and P2RY12 immunoreactivity in multiple sclerosis white and grey matter lesions is dependent on their inflammatory environment. Acta Neuropathol Commun 2019; 7:206. [PMID: 31829283 PMCID: PMC6907356 DOI: 10.1186/s40478-019-0850-z] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 11/14/2019] [Indexed: 12/23/2022] Open
Abstract
Multiple Sclerosis (MS) is the most common cause of acquired neurological disability in young adults, pathologically characterized by leukocyte infiltration of the central nervous system, demyelination of the white and grey matter, and subsequent axonal loss. Microglia are proposed to play a role in MS lesion formation, however previous literature has not been able to distinguish infiltrated macrophages from microglia. Therefore, in this study we utilize the microglia-specific, homeostatic markers TMEM119 and P2RY12 to characterize their immunoreactivity in MS grey matter lesions in comparison to white matter lesions. Furthermore, we assessed the immunological status of the white and grey matter lesions, as well as the responsivity of human white and grey matter derived microglia to inflammatory mediators. We are the first to show that white and grey matter lesions in post-mortem human material differ in their immunoreactivity for the homeostatic microglia-specific markers TMEM119 and P2RY12. In particular, whereas immunoreactivity for TMEM119 and P2RY12 is decreased in the center of WMLs, immunoreactivity for both markers is not altered in GMLs. Based on data from post-mortem human microglia cultures, treated with IL-4 or IFNγ+LPS and on counts of CD3+ or CD20+ lymphocytes in lesions, we show that downregulation of TMEM119 and P2RY12 immunoreactivity in MS lesions corresponds with the presence of lymphocytes and lymphocyte-derived cytokines within the parenchyma but not in the meninges. Furthermore, the presence of TMEM119+ and partly P2RY12+ microglia in pre-active lesions as well as in the rim of active white and grey matter lesions, in addition to TMEM119+ and P2RY12+ rod-like microglia in subpial grey matter lesions suggest that blocking the entrance of lymphocytes into the CNS of MS patients may not interfere with all possible effects of TMEM119+ and P2RY12+ microglia in both white and grey matter MS lesions.
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van Dongen L, Westerik B, van der Hiele K, Visser LH, Schoonheim MM, Douw L, Twisk JWR, de Jong BA, Geurts JJG, Hulst HE. Introducing Multiple Screener: An unsupervised digital screening tool for cognitive deficits in MS. Mult Scler Relat Disord 2019; 38:101479. [PMID: 31760365 DOI: 10.1016/j.msard.2019.101479] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 08/06/2019] [Accepted: 10/25/2019] [Indexed: 10/25/2022]
Abstract
BACKGROUND Cognitive deficits affect up to 70% of all patients with Multiple Sclerosis (MS) and have a significant impact on quality of life. Cognitive assessments need to be performed by a neuropsychologist and are often time-consuming, hampering timely identification and adequate monitoring of cognitive decline in MS. OBJECTIVE To develop a time-efficient, unsupervised, digital tool to screen for cognitive deficits in MS. METHODS A digital (adjusted) version of the Brief International Cognitive Assessment for MS, including the Symbol Digit Modalities Test (SDMT, information processing speed), the California Verbal Learning Test (CVLT-II, verbal memory) and the Spatial Recall Test (SPART, visuospatial memory) was developed: Multiple Screener (intellectual property of Sanofi Genzyme). Firstly, the clarity and feasibility of the tool was confirmed by 16 patients with MS (mean age 50.9 years (SD 9.4, range 37-68). Next, in 60 healthy controls (HCs, mean age 44.5 years (SD 14.0, range 18-67), intraclass correlation coefficients (ICC) were calculated to describe how strongly the digital version resembled the paper and pencil-based assessment. Finally, 236 HCs (mean age 42.8 years (SD 12.8, range 18-69) were included to obtain norm scores for each test. RESULTS ICCs between digital and paper and pencil-based assessment were excellent to good (SDMT (ICC 0.79, confidence interval (CI) 0.67-0.87); CVLT-II (ICC 0.77, CI 0.64-0.85); SPART (ICC 0.61, CI 0.42-0.75)). For each test, a regression-based correction for the effect of age was applied on the raw scores before converting them to norm Z-scores. Additionally, the SDMT scores needed correction for education and the CVLT-II for education and sex (subgroups were created). CONCLUSIONS Performance on an adjusted, digital version of the BICAMS correlates highly with the standard paper-and-pencil based test scores in HCs. Multiple Screener is an unsupervised, digital tool, with available norm scores, ultimately allowing for easy monitoring of cognitive decline in patients with MS.
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Affiliation(s)
- L van Dongen
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - B Westerik
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - K van der Hiele
- Department of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Leiden, the Netherlands
| | - L H Visser
- Department of Neurology, Elisabeth-Tweesteden Hospital, Tilburg, the Netherlands; Department of Care Ethics, University of Humanistic Studies, Utrecht, the Netherlands
| | - M M Schoonheim
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - L Douw
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - J W R Twisk
- Department of Epidemiology and Biostatistics, Amsterdam Public Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - B A de Jong
- Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - J J G Geurts
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - H E Hulst
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
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Boon BDC, Pouwels PJW, Jonkman LE, Keijzer MJ, Preziosa P, van de Berg WDJ, Geurts JJG, Scheltens P, Barkhof F, Rozemuller AJM, Bouwman FH, Steenwijk MD. Can post-mortem MRI be used as a proxy for in vivo? A case study. Brain Commun 2019; 1:fcz030. [PMID: 32954270 PMCID: PMC7425311 DOI: 10.1093/braincomms/fcz030] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 09/30/2019] [Accepted: 10/03/2019] [Indexed: 12/19/2022] Open
Abstract
Post-mortem in situ MRI has been used as an intermediate between brain histo(patho)logy and in vivo imaging. However, it is not known how comparable post-mortem in situ is to ante-mortem imaging. We report the unique situation of a patient with familial early-onset Alzheimer's disease due to a PSEN1 mutation, who underwent ante-mortem brain MRI and post-mortem in situ imaging only 4 days apart. T1-weighted and diffusion MRI was performed at 3-Tesla at both time points. Visual atrophy rating scales, brain volume, cortical thickness and diffusion measures were derived from both scans and compared. Post-mortem visual atrophy scores decreased 0.5-1 point compared with ante-mortem, indicating an increase in brain volume. This was confirmed by quantitative analysis; showing a 27% decrease of ventricular and 7% increase of whole-brain volume. This increase was more pronounced in the cerebellum and supratentorial white matter than in grey matter. Furthermore, axial and radial diffusivity decreased up to 60% post-mortem whereas average fractional anisotropy of white matter increased approximately 10%. This unique case study shows that the process of dying affects several imaging markers. These changes need to be taken into account when interpreting post-mortem MRI to make inferences on the in vivo situation.
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Affiliation(s)
- Baayla D C Boon
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands.,Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Matthijs J Keijzer
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, Gower Street, WC1E 6BT London, UK
| | - Annemieke J M Rozemuller
- Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Femke H Bouwman
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HZ, Amsterdam, The Netherlands
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Kulik SD, Derks J, Numan T, Hillebrand A, de Witt Hamer PC, Klein M, Geurts JJG, Reijneveld JC, Stam CJ, Schoonheim MM, Douw L. P14.53 Deconstructing pathologically increased MEG network clustering in glioma patients. Neuro Oncol 2019. [DOI: 10.1093/neuonc/noz126.288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Introduction
Functional brain networks in glioma patients are characterized by higher global clustering than healthy controls, indicating stronger connectivity in triads of brain regions when averaging across the entire brain. However, this could be due to either primary increased local clustering of (peri)tumor regions or higher local clustering throughout the entire brain.
METHODS
Magnetoencephalography recordings of 71 glioma patients and 53 HCs were analyzed by calculating functional connectivity with the phase lag index between source-localized time series of 78 cortical regions of the automated anatomical labelling atlas. Per participant, we calculated (1) global average clustering, (2) local clustering of tumor and non-tumor regions, and (3) Euclidean distance between tumor centroids and of all other region centroids.
RESULTS
Glioma patients had higher global average clustering (p=0.002) than HCs. This increase was indeed global: there was no difference between tumor and non-tumor regions (p=0.154) and no association between distance and local clustering (p=0.759). When splitting patients into high (top 25%, n=18) and normal global clustering (other 75%, n=53) to more specifically pick up on the determinants of pathological global average clustering, again no localized or distance-dependent effects were found. High clustering patients were younger than patients with normal global clustering (p=0.027). Posthoc analysis into tumor localization preference for particular network regions in the entire patient cohort revealed greater tumor occurrence in regions with high clustering in HC (p<0.001), while patients with high global clustering showed tumors localized in regions with lower clustering in HC (p=0.032).
CONCLUSION
The functional brain network of a subset of (relatively young) glioma patients is disturbed on a global level, suggesting that treatment thereof might benefit patients. Moreover, our exploratory analyses suggest that gliomas occur more often in normally highly clustered regions, but that tumors occurring in less clustered regions are associated with more extensive global network alterations. These findings may speculatively indicate that patients with and without such pathologically altered global clustering represent distinct phenotypes (both in terms of age and tumor localization) and may also need to be treated as such.
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Affiliation(s)
| | - J Derks
- VUmc, Amsterdam, Netherlands
| | - T Numan
- VUmc, Amsterdam, Netherlands
| | | | | | - M Klein
- VUmc, Amsterdam, Netherlands
| | | | | | | | | | - L Douw
- VUmc, Amsterdam, Netherlands
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