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Murley AG, Rua C, Biggs H, Rodgers CT, Matys T, van den Ameele J, Horvath R, Chinnery PF. 7T MRI detects widespread brain iron deposition in neuroferritinopathy. Ann Clin Transl Neurol 2024; 11:1359-1364. [PMID: 38561955 DOI: 10.1002/acn3.52053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/10/2024] [Accepted: 03/15/2024] [Indexed: 04/04/2024] Open
Abstract
Neuroferritinopathy is a disorder of neurodegeneration with brain iron accumulation that has no proven disease-modifying treatments. Clinical trials require biomarkers of iron deposition. We examined brain iron accumulation in one presymptomatic FTL mutation carrier, two individuals with neuroferritinopathy and one healthy control using ultra-high-field 7T MRI. There was increased magnetic susceptibility, suggestive of iron deposition, in superficial and deep gray matter in both presymptomatic and symptomatic neuroferritinopathy. Cavitation of the putamen and globus pallidus increased with disease stage and at follow up. The widespread brain iron deposition in presymptomatic and early disease provides an opportunity for monitoring disease-modifying intervention.
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Affiliation(s)
- Alexander G Murley
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Catarina Rua
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
- Invicro, London, UK
| | - Heather Biggs
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Christopher T Rodgers
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Jelle van den Ameele
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Rita Horvath
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Patrick F Chinnery
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
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Roberts AG, Romano DJ, Şişman M, Dimov AV, Nguyen TD, Kovanlikaya I, Gauthier SA, Wang Y, Spincemaille P. Maximum spherical mean value filtering for whole-brain QSM. Magn Reson Med 2024; 91:1586-1597. [PMID: 38169132 DOI: 10.1002/mrm.29963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 10/30/2023] [Accepted: 11/19/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To develop a tissue field-filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain-tissue erosion. THEORY AND METHODS Residual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field-magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients. RESULTS Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis. CONCLUSION The mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV-filtered dipole inversion without eroding the volume of interest.
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Affiliation(s)
- Alexandra G Roberts
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Dominick J Romano
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Mert Şişman
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Alexey V Dimov
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Susan A Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Yi Wang
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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Varga Z, Keller J, Robinson SD, Serranova T, Nepozitek J, Zogala D, Trnka J, Ruzicka E, Sonka K, Dusek P. Whole brain pattern of iron accumulation in REM sleep behavior disorder. Hum Brain Mapp 2024; 45:e26675. [PMID: 38590155 PMCID: PMC11002348 DOI: 10.1002/hbm.26675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/10/2024] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
Isolated REM sleep behavior disorder (iRBD) is an early stage of synucleinopathy with most patients progressing to Parkinson's disease (PD) or related conditions. Quantitative susceptibility mapping (QSM) in PD has identified pathological iron accumulation in the substantia nigra (SN) and variably also in basal ganglia and cortex. Analyzing whole-brain QSM across iRBD, PD, and healthy controls (HC) may help to ascertain the extent of neurodegeneration in prodromal synucleinopathy. 70 de novo PD patients, 70 iRBD patients, and 60 HCs underwent 3 T MRI. T1 and susceptibility-weighted images were acquired and processed to space standardized QSM. Voxel-based analyses of grey matter magnetic susceptibility differences comparing all groups were performed on the whole brain and upper brainstem levels with the statistical threshold set at family-wise error-corrected p-values <.05. Whole-brain analysis showed increased susceptibility in the bilateral fronto-parietal cortex of iRBD patients compared to both PD and HC. This was not associated with cortical thinning according to the cortical thickness analysis. Compared to iRBD, PD patients had increased susceptibility in the left amygdala and hippocampal region. Upper brainstem analysis revealed increased susceptibility within the bilateral SN for both PD and iRBD compared to HC; changes were located predominantly in nigrosome 1 in the former and nigrosome 2 in the latter group. In the iRBD group, abnormal dopamine transporter SPECT was associated with increased susceptibility in nigrosome 1. iRBD patients display greater fronto-parietal cortex involvement than incidental early-stage PD cohort indicating more widespread subclinical neuropathology. Dopaminergic degeneration in the substantia nigra is paralleled by susceptibility increase, mainly in nigrosome 1.
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Affiliation(s)
- Zsoka Varga
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Jiri Keller
- Radiodiagnostic DepartmentNa Homolce HospitalPragueCzech Republic
| | - Simon Daniel Robinson
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaAustria
| | - Tereza Serranova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Jiri Nepozitek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - David Zogala
- Department of Nuclear Medicine, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Jiri Trnka
- Department of Nuclear Medicine, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Evzen Ruzicka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Karel Sonka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
| | - Petr Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
- Department of Radiology, First Faculty of MedicineCharles University and General University Hospital in PragueCzech Republic
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Thomas GEC, Hannaway N, Zarkali A, Shmueli K, Weil RS. Longitudinal Associations of Magnetic Susceptibility with Clinical Severity in Parkinson's Disease. Mov Disord 2024; 39:546-559. [PMID: 38173297 DOI: 10.1002/mds.29702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/29/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Dementia is common in Parkinson's disease (PD), but there is wide variation in its timing. A critical gap in PD research is the lack of quantifiable markers of progression, and methods to identify early stages of dementia. Atrophy-based magnetic resonance imaging (MRI) has limited sensitivity in detecting or tracking changes relating to PD dementia, but quantitative susceptibility mapping (QSM), sensitive to brain tissue iron, shows potential for these purposes. OBJECTIVE The objective of the paper is to study, for the first time, the longitudinal relationship between cognition and QSM in PD in detail. METHODS We present a longitudinal study of clinical severity in PD using QSM, including 59 PD patients (without dementia at study onset), and 22 controls over 3 years. RESULTS In PD, increased baseline susceptibility in the right temporal cortex, nucleus basalis of Meynert, and putamen was associated with greater cognitive severity after 3 years; and increased baseline susceptibility in basal ganglia, substantia nigra, red nucleus, insular cortex, and dentate nucleus was associated with greater motor severity after 3 years. Increased follow-up susceptibility in these regions was associated with increased follow-up cognitive and motor severity, with further involvement of hippocampus relating to cognitive severity. However, there were no consistent increases in susceptibility over 3 years. CONCLUSIONS Our study suggests that QSM may predict changes in cognitive severity many months prior to overt cognitive involvement in PD. However, we did not find robust longitudinal changes in QSM over the course of the study. Additional tissue metrics may be required together with QSM for it to monitor progression in clinical practice and therapeutic trials. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Naomi Hannaway
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Angelika Zarkali
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Rimona S Weil
- Dementia Research Centre, UCL Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Movement Disorders Consortium, University College London, London, UK
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Northall A, Doehler J, Weber M, Tellez I, Petri S, Prudlo J, Vielhaber S, Schreiber S, Kuehn E. Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis. Brain 2024; 147:1087-1099. [PMID: 37815224 PMCID: PMC10907094 DOI: 10.1093/brain/awad351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 09/01/2023] [Accepted: 09/24/2023] [Indexed: 10/11/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Igor Tellez
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
| | - Susanne Petri
- Department of Neurology, Hannover Medical School (MHH), Hanover 30625, Germany
| | - Johannes Prudlo
- Department of Neurology, Rostock University Medical Centre, Rostock 18147, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock 18147, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen 72076, Germany
- Hertie Institute for Clinical Brain Research (HIH), Tübingen 72076, Germany
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Alushaj E, Handfield-Jones N, Kuurstra A, Morava A, Menon RS, Owen AM, Sharma M, Khan AR, MacDonald PA. Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson'sdisease: A 3T and 7T MRI study. Neuroimage Clin 2024; 41:103577. [PMID: 38377722 PMCID: PMC10944193 DOI: 10.1016/j.nicl.2024.103577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/19/2023] [Accepted: 02/07/2024] [Indexed: 02/22/2024]
Abstract
Degeneration in the substantia nigra (SN) pars compacta (SNc) underlies motor symptoms in Parkinson's disease (PD). Currently, there are no neuroimaging biomarkers that are sufficiently sensitive, specific, reproducible, and accessible for routine diagnosis or staging of PD. Although iron is essential for cellular processes, it also mediates neurodegeneration. MRI can localize and quantify brain iron using magnetic susceptibility, which could potentially provide biomarkers of PD. We measured iron in the SNc, SN pars reticulata (SNr), total SN, and ventral tegmental area (VTA), using quantitative susceptibility mapping (QSM) and R2* relaxometry, in PD patients and age-matched healthy controls (HCs). PD patients, diagnosed within five years of participation and HCs were scanned at 3T (22 PD and 23 HCs) and 7T (17 PD and 21 HCs) MRI. Midbrain nuclei were segmented using a probabilistic subcortical atlas. QSM and R2* values were measured in midbrain subregions. For each measure, groups were contrasted, with Age and Sex as covariates, and receiver operating characteristic (ROC) curve analyses were performed with repeated k-fold cross-validation to test the potential of our measures to classify PD patients and HCs. Statistical differences of area under the curves (AUCs) were compared using the Hanley-MacNeil method (QSM versus R2*; 3T versus 7T MRI). PD patients had higher QSM values in the SNc at both 3T (padj = 0.001) and 7T (padj = 0.01), but not in SNr, total SN, or VTA, at either field strength. No significant group differences were revealed using R2* in any midbrain region at 3T, though increased R2* values in SNc at 7T MRI were marginally significant in PDs compared to HCs (padj = 0.052). ROC curve analyses showed that SNc iron measured with QSM, distinguished early PD patients from HCs at the single-subject level with good diagnostic accuracy, using 3T (mean AUC = 0.83, 95 % CI = 0.82-0.84) and 7T (mean AUC = 0.80, 95 % CI = 0.79-0.81) MRI. Mean AUCs reported here are from averages of tests in the hold-out fold of cross-validated samples. The Hanley-MacNeil method demonstrated that QSM outperforms R2* in discriminating PD patients from HCs at 3T, but not 7T. There were no significant differences between 3T and 7T in diagnostic accuracy of QSM values in SNc. This study highlights the importance of segmenting midbrain subregions, performed here using a standardized atlas, and demonstrates high accuracy of SNc iron measured with QSM at 3T MRI in identifying early PD patients. QSM measures of SNc show potential for inclusion in neuroimaging diagnostic biomarkers of early PD. An MRI diagnostic biomarker of PD would represent a significant clinical advance.
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Affiliation(s)
- Erind Alushaj
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Nicholas Handfield-Jones
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Alan Kuurstra
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Anisa Morava
- School of Kinesiology, Faculty of Health Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ravi S Menon
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
| | - Manas Sharma
- Department of Radiology, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ali R Khan
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Penny A MacDonald
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada.
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Gan Y, Su D, Zhang Z, Zhang Z, Yan R, Liu Z, Wang Z, Zhou J, Lam JST, Wu T, Jing J, Feng T. Microstructural and functional alterations of the ventral pallidum are associated with levodopa-induced dyskinesia in Parkinson's disease. Eur J Neurol 2024; 31:e16147. [PMID: 37975786 DOI: 10.1111/ene.16147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND AND PURPOSE The ventral pallidum (VP) regulates involuntary movements, but it is unclear whether the VP regulates the abnormal involuntary movements in Parkinson's disease (PD) patients who have levodopa-induced dyskinesia (LID). To further understand the role of the VP in PD patients with LID (PD-LID), we explored the structural and functional characteristics of the VP in such patients using multimodal magnetic resonance imaging (MRI). METHODS Thirty-one PD-LID patients, 39 PD patients without LID (PD-nLID), and 28 healthy controls (HCs) underwent T1-weighted MRI, quantitative susceptibility mapping, multi-shell diffusion MRI, and resting-state functional MRI (rs-fMRI). Different measures characterizing the VP were obtained using a region-of-interest-based approach. RESULTS The left VP in the PD-LID group showed significantly higher intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) compared with the PD-nLID and HC groups. Rs-MRI revealed that, compared with the PD-nLID group, the PD-LID group in the medication 'off' state had higher functional connectivity (FC) between the left VP and the left anterior caudate, left middle frontal gyrus and left precentral gyrus, as well as between the right VP and the right posterior ventral putamen and right mediodorsal thalamus. In addition, the ICVF values of the left VP, the FC between the left VP and the left anterior caudate and left middle frontal gyrus were positively correlated with Unified Dyskinesia Rating Scale scores. CONCLUSION Our multimodal imaging findings show that the microstructural changes of the VP (i.e., the higher ICVF and IsoVF) and the functional change in the ventral striatum-VP-mediodorsal thalamus-cortex network may be associated with pathophysiological mechanisms of PD-LID.
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Affiliation(s)
- Yawen Gan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Dongning Su
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhijin Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Rui Yan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhu Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhan Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Joyce S T Lam
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tao Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Feng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
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Nepozitek J, Varga Z, Dostalova S, Perinova P, Keller J, Robinson S, Ibarburu V, Prihodova I, Bezdicek O, Ruzicka E, Sonka K, Dusek P. Magnetic susceptibility changes in the brainstem reflect REM sleep without atonia severity in isolated REM sleep behavior disorder. NPJ Parkinsons Dis 2023; 9:112. [PMID: 37452075 PMCID: PMC10349141 DOI: 10.1038/s41531-023-00557-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023] Open
Abstract
REM sleep without atonia (RWA) is the hallmark of isolated REM sleep behavior disorder (iRBD) and is caused by neurodegeneration of brainstem structures. Previously, quantitative susceptibility mapping (QSM) was shown to detect microstructural tissue changes in neurodegenerative diseases. The goal of the study was to compare brainstem magnetic susceptibility (MS) in iRBD and controls using the voxel-based QSM approach and to examine the association between brainstem MS and severity of RWA in iRBD. Sixty iRBD patients and 41 healthy controls were included in the study. Phasic, tonic, mixed RWA and SINBAR score was quantified. QSM maps were reconstructed with QSMbox software from a multi-gradient-echo sequence acquired at 3T MRI system and normalized using a custom T1 template. Voxel-based analysis with age and gender as covariates was performed using a two-sample t-test model for between-group comparison and using a linear regression model for association with the RWA parameters. Statistical maps were generated using threshold free cluster enhancement with p-value p < 0.05, corrected for family wise error. Compared to controls, the iRBD group had higher MS in bilateral substantia nigra (SN), red nucleus and the ventral tegmental area. MS positively correlated with iRBD duration in the right pedunculotegmental nucleus and white matter of caudal mesencephalic and pontine tegmentum and with phasic RWA in bilateral SN. QSM was able to detect MS abnormalities in several brainstem structures in iRBD. Association of MS levels in the brainstem with the intensity of RWA suggests that increased iron content in SN is related to RWA severity.
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Affiliation(s)
- Jiri Nepozitek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
| | - Zsoka Varga
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Simona Dostalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Pavla Perinova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Jiri Keller
- Radiodiagnostic Department, Na Homolce Hospital, Prague, Czech Republic
| | - Simon Robinson
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Centre of Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Veronika Ibarburu
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Iva Prihodova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Ondrej Bezdicek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Evzen Ruzicka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Karel Sonka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Petr Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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Xie F, Mao T, Tang J, Zhao L, Guo J, Lin H, Wang D, Zhou G. Evaluation of iron deposition in the motor CSTC loop of a Chinese family with paroxysmal kinesigenic dyskinesia using quantitative susceptibility mapping. Front Neurol 2023; 14:1164600. [PMID: 37483438 PMCID: PMC10358764 DOI: 10.3389/fneur.2023.1164600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023] Open
Abstract
Introduction Previous studies have revealed structural, functional, and metabolic changes in brain regions inside the cortico-striatal-thalamo-cortical (CSTC) loop in patients with paroxysmal kinesigenic dyskinesia (PKD), whereas no quantitative susceptibility mapping (QSM)-related studies have explored brain iron deposition in these areas. Methods A total of eight familial PKD patients and 10 of their healthy family members (normal controls) were recruited and underwent QSM on a 3T magnetic resonance imaging system. Magnetic susceptibility maps were reconstructed using a multi-scale dipole inversion algorithm. Thereafter, we specifically analyzed changes in local mean susceptibility values in cortical regions and subcortical nuclei inside the motor CSTC loop. Results Compared with normal controls, PKD patients had altered brain iron levels. In the cortical gray matter area involved with the motor CSTC loop, susceptibility values were generally elevated, especially in the bilateral M1 and PMv regions. In the subcortical nuclei regions involved with the motor CSTC loop, susceptibility values were generally lower, especially in the bilateral substantia nigra regions. Conclusion Our results provide new evidence for the neuropathogenesis of PKD and suggest that an imbalance in brain iron levels may play a role in PKD.
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Affiliation(s)
- Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Ting Mao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Jingyi Tang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Linmei Zhao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Jiuqing Guo
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Huashan Lin
- Department of Pharmaceutical Diagnosis, GE Healthcare, Changsha, China
| | - Dongcui Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Gaofeng Zhou
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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10
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Burgetova A, Dusek P, Uher T, Vaneckova M, Vejrazka M, Burgetova R, Horakova D, Srpova B, Kalousova M, Noskova L, Levova K, Krasensky J, Lambert L. CSF Markers of Oxidative Stress Are Associated with Brain Atrophy and Iron Accumulation in a 2-Year Longitudinal Cohort of Early MS. Int J Mol Sci 2023; 24:10048. [PMID: 37373196 DOI: 10.3390/ijms241210048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 05/27/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
In this prospective longitudinal study, we quantified regional brain volume and susceptibility changes during the first two years after the diagnosis of multiple sclerosis (MS) and identified their association with cerebrospinal fluid (CSF) markers at baseline. Seventy patients underwent MRI (T1 and susceptibility weighted images processed to quantitative susceptibility maps, QSM) with neurological examination at the diagnosis and after two years. In CSF obtained at baseline, the levels of oxidative stress, products of lipid peroxidation, and neurofilaments light chain (NfL) were determined. Brain volumetry and QSM were compared with a group of 58 healthy controls. In MS patients, regional atrophy was identified in the striatum, thalamus, and substantia nigra. Magnetic susceptibility increased in the striatum, globus pallidus, and dentate and decreased in the thalamus. Compared to controls, MS patients developed greater atrophy of the thalamus, and a greater increase in susceptibility in the caudate, putamen, globus pallidus and a decrease in the thalamus. Of the multiple calculated correlations, only the decrease in brain parenchymal fraction, total white matter, and thalamic volume in MS patients negatively correlated with increased NfL in CSF. Additionally, negative correlation was found between QSM value in the substantia nigra and peroxiredoxin-2, and QSM value in the dentate and lipid peroxidation levels.
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Affiliation(s)
- Andrea Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Petr Dusek
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Martin Vejrazka
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Romana Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
- Department of Radiology, Third Faculty of Medicine, Charles University, 100 34 Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Marta Kalousova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Libuse Noskova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Katerina Levova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
| | - Lukas Lambert
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic
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11
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Doehler J, Northall A, Liu P, Fracasso A, Chrysidou A, Speck O, Lohmann G, Wolbers T, Kuehn E. The 3D Structural Architecture of the Human Hand Area Is Nontopographic. J Neurosci 2023; 43:3456-3476. [PMID: 37001994 PMCID: PMC10184749 DOI: 10.1523/jneurosci.1692-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 02/15/2023] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
The functional topography of the human primary somatosensory cortex hand area is a widely studied model system to understand sensory organization and plasticity. It is so far unclear whether the underlying 3D structural architecture also shows a topographic organization. We used 7 Tesla (7T) magnetic resonance imaging (MRI) data to quantify layer-specific myelin, iron, and mineralization in relation to population receptive field maps of individual finger representations in Brodman area 3b (BA 3b) of human S1 in female and male younger adults. This 3D description allowed us to identify a characteristic profile of layer-specific myelin and iron deposition in the BA 3b hand area, but revealed an absence of structural differences, an absence of low-myelin borders, and high similarity of 3D microstructure profiles between individual fingers. However, structural differences and borders were detected between the hand and face areas. We conclude that the 3D structural architecture of the human hand area is nontopographic, unlike in some monkey species, which suggests a high degree of flexibility for functional finger organization and a new perspective on human topographic plasticity.SIGNIFICANCE STATEMENT Using ultra-high-field MRI, we provide the first comprehensive in vivo description of the 3D structural architecture of the human BA 3b hand area in relation to functional population receptive field maps. High similarity of precise finger-specific 3D profiles, together with an absence of structural differences and an absence of low-myelin borders between individual fingers, reveals the 3D structural architecture of the human hand area to be nontopographic. This suggests reduced structural limitations to cortical plasticity and reorganization and allows for shared representational features across fingers.
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Affiliation(s)
- Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research, Medical Faculty, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Alicia Northall
- Institute for Cognitive Neurology and Dementia Research, Medical Faculty, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Peng Liu
- Institute for Cognitive Neurology and Dementia Research, Medical Faculty, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Alessio Fracasso
- Institute of Neuroscience and Psychology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom
| | - Anastasia Chrysidou
- Institute for Cognitive Neurology and Dementia Research, Medical Faculty, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Oliver Speck
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Biomedical Magnetic Resonance, Otto-von-Guericke-University Magdeburg, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences, 39120 Magdeburg, Germany
- Leibniz Institute for Neurobiology, 39120 Magdeburg, Germany
| | - Gabriele Lohmann
- Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
| | - Thomas Wolbers
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences, 39120 Magdeburg, Germany
| | - Esther Kuehn
- Hertie Institute for Clinical Brain Research, 72076 Tübingen, Germany
- Institute for Cognitive Neurology and Dementia Research, Medical Faculty, Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences, 39120 Magdeburg, Germany
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12
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Northall A, Doehler J, Weber M, Vielhaber S, Schreiber S, Kuehn E. Layer-specific vulnerability is a mechanism of topographic map aging. Neurobiol Aging 2023; 128:17-32. [PMID: 37141729 DOI: 10.1016/j.neurobiolaging.2023.04.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/29/2023] [Accepted: 04/02/2023] [Indexed: 05/06/2023]
Abstract
Topographic maps form a critical feature of cortical organization, yet are poorly described with respect to their microstructure in the living aging brain. We acquired quantitative structural and functional 7T-MRI data from younger and older adults to characterize layer-wise topographic maps of the primary motor cortex (M1). Using parcellation-inspired techniques, we show that quantitative T1 and Quantitative Susceptibility Maps values of the hand, face, and foot areas differ significantly, revealing microstructurally distinct cortical fields in M1. We show that these fields are distinct in older adults and that myelin borders between them do not degenerate. We further show that the output layer 5 of M1 shows a particular vulnerability to age-related increased iron, while layer 5 and the superficial layer show increased diamagnetic substance, likely reflecting calcifications. Taken together, we provide a novel 3D model of M1 microstructure, where body parts form distinct structural units, but layers show specific vulnerability toward increased iron and calcium in older adults. Our findings have implications for understanding sensorimotor organization and aging, in addition to topographic disease spread.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany.
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany; Hertie Institute for Clinical Brain Research, Tübingen, Germany
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13
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Perosa V, Rotta J, Yakupov R, Kuijf HJ, Schreiber F, Oltmer JT, Mattern H, Heinze HJ, Düzel E, Schreiber S. Implications of quantitative susceptibility mapping at 7 Tesla MRI for microbleeds detection in cerebral small vessel disease. Front Neurol 2023; 14:1112312. [PMID: 37006483 PMCID: PMC10050564 DOI: 10.3389/fneur.2023.1112312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/20/2023] [Indexed: 03/17/2023] Open
Abstract
BackgroundCerebral microbleeds (MBs) are a hallmark of cerebral small vessel disease (CSVD) and can be found on T2*-weighted sequences on MRI. Quantitative susceptibility mapping (QSM) is a postprocessing method that also enables MBs identification and furthermore allows to differentiate them from calcifications.AimsWe explored the implications of using QSM at submillimeter resolution for MBs detection in CSVD.MethodsBoth 3 and 7 Tesla (T) MRI were performed in elderly participants without MBs and patients with CSVD. MBs were quantified on T2*-weighted imaging and QSM. Differences in the number of MBs were assessed, and subjects were classified in CSVD subgroups or controls both on 3T T2*-weighted imaging and 7T QSM.Results48 participants [mean age (SD) 70.9 (8.8) years, 48% females] were included: 31 were healthy controls, 6 probable cerebral amyloid angiopathy (CAA), 9 mixed CSVD, and 2 were hypertensive arteriopathy [HA] patients. After accounting for the higher number of MBs detected at 7T QSM (Median = Mdn; Mdn7T−QSM = 2.5; Mdn3T−T2 = 0; z = 4.90; p < 0.001) and false positive MBs (6.1% calcifications), most healthy controls (80.6%) demonstrated at least one MB and more MBs were discovered in the CSVD group.ConclusionsOur observations suggest that QSM at submillimeter resolution improves the detection of MBs in the elderly human brain. A higher prevalence of MBs than so far known in healthy elderly was revealed.
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Affiliation(s)
- Valentina Perosa
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, United States
- *Correspondence: Valentina Perosa
| | - Johanna Rotta
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Renat Yakupov
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - Frank Schreiber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jan T. Oltmer
- Athinoula A. Martinos Center, Massachusetts General Hospital, Department of Radiology, Boston, MA, United States
| | - Hendrik Mattern
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Physics, Otto-von-Guericke University, Magdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
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14
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Su D, Gan Y, Zhang Z, Cui Y, Zhang Z, Liu Z, Wang Z, Zhou J, Sossi V, Stoessl AJ, Wu T, Jing J, Feng T. Multimodal Imaging of Substantia Nigra in Parkinson's Disease with Levodopa-Induced Dyskinesia. Mov Disord 2023; 38:616-625. [PMID: 36799459 DOI: 10.1002/mds.29320] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/01/2022] [Accepted: 12/20/2022] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear. OBJECTIVE To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI). METHODS Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach. RESULTS Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P = 0.049 and P = 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P = 0.012 and P = 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P = 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P = 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R = 0.427, P = 0.042). CONCLUSIONS Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dongning Su
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yawen Gan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yusha Cui
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhijin Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhu Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhan Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Vesna Sossi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada
| | - A Jon Stoessl
- Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tao Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Feng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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15
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Su D, Zhang Z, Zhang Z, Gan Y, Zhang Y, Liu X, Bi J, Ma L, Zhao H, Wang X, Wang Z, Ma H, Sifat S, Zhou J, Li W, Wu T, Jing J, Feng T. Microstructural and functional impairment of the basal ganglia in Wilson's disease: a multimodal neuroimaging study. Front Neurosci 2023; 17:1146644. [PMID: 37152597 PMCID: PMC10157043 DOI: 10.3389/fnins.2023.1146644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/27/2023] [Indexed: 05/09/2023] Open
Abstract
Objectives Magnetic susceptibility changes in brain MRI of Wilson's disease (WD) patients have been described in subcortical nuclei especially the basal ganglia. The objectives of this study were to investigate its relationship with other microstructural and functional alterations of the subcortical nuclei and the diagnostic utility of these MRI-related metrics. Methods A total of 22 WD patients and 20 healthy controls (HCs) underwent 3.0T multimodal MRI scanning. Susceptibility, volume, diffusion microstructural indices and whole-brain functional connectivity of the putamen (PU), globus pallidus (GP), caudate nucleus (CN), and thalamus (TH) were analyzed. Receiver operating curve (ROC) was applied to evaluate the diagnostic value of the imaging data. Correlation analysis was performed to explore the connection between susceptibility change and microstructure and functional impairment of WD and screen for neuroimaging biomarkers of disease severity. Results Wilson's disease patients demonstrated increased susceptibility in the PU, GP, and TH, and widespread atrophy and microstructural impairments in the PU, GP, CN, and TH. Functional connectivity decreased within the basal ganglia and increased between the PU and cortex. The ROC model showed higher diagnostic value of isotropic volume fraction (ISOVF, in the neurite orientation dispersion and density imaging model) compared with susceptibility. Severity of neurological symptoms was correlated with volume and ISOVF. Susceptibility was positively correlated with ISOVF in GP. Conclusion Microstructural impairment of the basal ganglia is related to excessive metal accumulation in WD. Brain atrophy and microstructural impairments are useful neuroimaging biomarkers for the neurological impairment of WD.
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Affiliation(s)
- Dongning Su
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhijin Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yawen Gan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yingkui Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xinyao Liu
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jingfeng Bi
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lingyan Ma
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huiqing Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuemei Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhan Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huizi Ma
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shairy Sifat
- Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson’s Research Centre, University of British Columbia and Vancouver Coastal Health, Vancouver, BC, Canada
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Wei Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tao Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Jing Jing,
| | - Tao Feng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tao Feng,
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16
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Dadarwal R, Ortiz-Rios M, Boretius S. Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates. Neuroimage 2022; 264:119730. [PMID: 36332851 DOI: 10.1016/j.neuroimage.2022.119730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 10/12/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022] Open
Abstract
Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans.
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Affiliation(s)
- Rakshit Dadarwal
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Georg-August University of Göttingen, Göttingen, Germany.
| | - Michael Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Georg-August University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
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17
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Uchida Y, Kan H, Sakurai K, Oishi K, Matsukawa N. Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations. Front Neurosci 2022; 16:938092. [PMID: 35992906 PMCID: PMC9389285 DOI: 10.3389/fnins.2022.938092] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/14/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.
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Affiliation(s)
- Yuto Uchida
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- *Correspondence: Yuto Uchida,
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Ōbu, Japan
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Noriyuki Matsukawa,
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18
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Shribman S, Burrows M, Convery R, Bocchetta M, Sudre CH, Acosta-Cabronero J, Thomas DL, Gillett GT, Tsochatzis EA, Bandmann O, Rohrer JD, Warner TT. Neuroimaging Correlates of Cognitive Deficits in Wilson's Disease. Mov Disord 2022; 37:1728-1738. [PMID: 35723521 PMCID: PMC9542291 DOI: 10.1002/mds.29123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 05/19/2022] [Accepted: 05/23/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Cognitive impairment is common in neurological presentations of Wilson's disease (WD). Various domains can be affected, and subclinical deficits have been reported in patients with hepatic presentations. Associations with imaging abnormalities have not been systematically tested. OBJECTIVE The aim was to determine the neuroanatomical basis for cognitive deficits in WD. METHODS We performed a 16-item neuropsychological test battery and magnetic resonance brain imaging in 40 patients with WD. The scores for each test were compared between patients with neurological and hepatic presentations and with normative data. Associations with Unified Wilson's Disease Rating Scale neurological examination subscores were examined. Quantitative, whole-brain, multimodal imaging analyses were used to identify associations with neuroimaging abnormalities in chronically treated stable patients. RESULTS Abstract reasoning, executive function, processing speed, calculation, and visuospatial function scores were lower in patients with neurological presentations than in those with hepatic presentations and correlated with neurological examination subscores. Deficits in abstract reasoning and phonemic fluency were associated with lower putamen volumes even after controlling for neurological severity. About half of patients with hepatic presentations had poor performance in memory for faces, cognitive flexibility, or associative learning relative to normative data. These deficits were associated with widespread cortical atrophy and/or white matter diffusion abnormalities. CONCLUSIONS Subtle cognitive deficits in patients with seemingly hepatic presentations represent a distinct neurological phenotype associated with diffuse cortical and white matter pathology. This may precede the classical neurological phenotype characterized by movement disorders and executive dysfunction and be associated with basal ganglia damage. A binary phenotypic classification for WD may no longer be appropriate. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Samuel Shribman
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
| | - Maggie Burrows
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
| | - Rhian Convery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Martina Bocchetta
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom.,Centre for Medical Image Computing, University College London, London, United Kingdom.,Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | | | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Godfrey T Gillett
- Department of Clinical Chemistry, Northern General Hospital, Sheffield, United Kingdom
| | - Emmanuel A Tsochatzis
- UCL Institute of Liver and Digestive Health and Royal Free Hospital, London, United Kingdom
| | - Oliver Bandmann
- Sheffield Institute of Translational Neuroscience, Sheffield, United Kingdom
| | - Jonathan D Rohrer
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Thomas T Warner
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
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19
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Yuan L, Li H, Fu S, Zhang Z. Learning Behavior Evaluation Model and Teaching Strategy Innovation by Social Media Network Following Learning Psychology. Front Psychol 2022; 13:843428. [PMID: 35936300 PMCID: PMC9355304 DOI: 10.3389/fpsyg.2022.843428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 06/13/2022] [Indexed: 12/02/2022] Open
Abstract
With the development of various network technologies and the spread of coronavirus disease 2019, many online learning platforms have been built. However, some of them may negatively impact student learning outcomes. Therefore, this study aims to improve the online learning effect of students by comprehensively evaluating their learning behavior by using deep learning algorithms. On this basis, new teaching strategies are proposed. According to the structured deep network embedding model, a network representation learning algorithm is proposed with the help of auto-encoders under deep learning. This study elaborates the concept and structure of the encoder model and tests its performance. After the node labels and dataset are trained, the applicable parameter λ2 of the model is 0.3. During the teaching process, the model's reliability in distinguishing users is examined. Therefore, this model can be applied to network teaching, is an innovative teaching strategy, and provides a theoretical basis for improving teaching methods.
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Affiliation(s)
- Lijuan Yuan
- College of Journalism and Communications, Zhoukou Normal University, Zhoukou, China
| | - Hongming Li
- Southampton Education School, University of Southampton, Southampton, United Kingdom
| | - Shiman Fu
- Southampton Education School, University of Southampton, Southampton, United Kingdom
| | - Zizai Zhang
- Hangzhou Preschool Teachers College, Zhejiang Normal University, Hangzhou, China
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20
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Biondetti E, Karsa A, Grussu F, Battiston M, Yiannakas MC, Thomas DL, Shmueli K. Multi-echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla. Magn Reson Med 2022; 88:2101-2116. [PMID: 35766450 PMCID: PMC9545116 DOI: 10.1002/mrm.29365] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/29/2022] [Accepted: 05/27/2022] [Indexed: 12/04/2022]
Abstract
Purpose To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal. Methods Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests). Results Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of χ and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions. Conclusion For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs. Click here for author‐reader discussions
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Affiliation(s)
- Emma Biondetti
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy.,Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Francesco Grussu
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Radiomics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - Marco Battiston
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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21
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Shribman S, Bocchetta M, Sudre CH, Acosta-Cabronero J, Burrows M, Cook P, Thomas DL, Gillett GT, Tsochatzis EA, Bandmann O, Rohrer JD, Warner TT. Neuroimaging correlates of brain injury in Wilson's disease: a multimodal, whole-brain MRI study. Brain 2022; 145:263-275. [PMID: 34289020 PMCID: PMC8967100 DOI: 10.1093/brain/awab274] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 06/25/2021] [Accepted: 07/04/2021] [Indexed: 11/23/2022] Open
Abstract
Wilson's disease is an autosomal-recessive disorder of copper metabolism with neurological and hepatic presentations. Chelation therapy is used to 'de-copper' patients but neurological outcomes remain unpredictable. A range of neuroimaging abnormalities have been described and may provide insights into disease mechanisms, in addition to prognostic and monitoring biomarkers. Previous quantitative MRI analyses have focused on specific sequences or regions of interest, often stratifying chronically treated patients according to persisting symptoms as opposed to initial presentation. In this cross-sectional study, we performed a combination of unbiased, whole-brain analyses on T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and susceptibility-weighted imaging data from 40 prospectively recruited patients with Wilson's disease (age range 16-68). We compared patients with neurological (n = 23) and hepatic (n = 17) presentations to determine the neuroradiological sequelae of the initial brain injury. We also subcategorized patients according to recent neurological status, classifying those with neurological presentations or deterioration in the preceding 6 months as having 'active' disease. This allowed us to compare patients with active (n = 5) and stable (n = 35) disease and identify imaging correlates for persistent neurological deficits and copper indices in chronically treated, stable patients. Using a combination of voxel-based morphometry and region-of-interest volumetric analyses, we demonstrate that grey matter volumes are lower in the basal ganglia, thalamus, brainstem, cerebellum, anterior insula and orbitofrontal cortex when comparing patients with neurological and hepatic presentations. In chronically treated, stable patients, the severity of neurological deficits correlated with grey matter volumes in similar, predominantly subcortical regions. In contrast, the severity of neurological deficits did not correlate with the volume of white matter hyperintensities, calculated using an automated lesion segmentation algorithm. Using tract-based spatial statistics, increasing neurological severity in chronically treated patients was associated with decreasing axial diffusivity in white matter tracts whereas increasing serum non-caeruloplasmin-bound ('free') copper and active disease were associated with distinct patterns of increasing mean, axial and radial diffusivity. Whole-brain quantitative susceptibility mapping identified increased iron deposition in the putamen, cingulate and medial frontal cortices of patients with neurological presentations relative to those with hepatic presentations and neurological severity was associated with iron deposition in widespread cortical regions in chronically treated patients. Our data indicate that composite measures of subcortical atrophy provide useful prognostic biomarkers, whereas abnormal mean, axial and radial diffusivity are promising monitoring biomarkers. Finally, deposition of brain iron in response to copper accumulation may directly contribute to neurodegeneration in Wilson's disease.
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Affiliation(s)
- Samuel Shribman
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
| | - Martina Bocchetta
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, University College London, London WC1E 7HB, UK
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
- Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | | | - Maggie Burrows
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
| | - Paul Cook
- Department of Clinical Biochemistry, Southampton General Hospital, Southampton SO16 6YD, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Godfrey T Gillett
- Department of Clinical Chemistry, Northern General Hospital, Sheffield S5 7AU, UK
| | - Emmanuel A Tsochatzis
- UCL Institute of Liver and Digestive Health and Royal Free Hospital, London NW3 2PF, UK
| | - Oliver Bandmann
- Sheffield Institute of Translational Neuroscience, Sheffield S10 2HQ, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Thomas T Warner
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
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22
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Milovic C, Lambert M, Langkammer C, Bredies K, Irarrazaval P, Tejos C. Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM). Magn Reson Med 2022; 87:457-473. [PMID: 34350634 DOI: 10.1002/mrm.28957] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 07/15/2021] [Accepted: 07/17/2021] [Indexed: 01/05/2023]
Abstract
PURPOSE The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts. METHODS QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages. RESULTS The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups. CONCLUSION The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Mathias Lambert
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Christian Langkammer
- Department of Neurology, Medical University of Graz, Graz, Austria
- BioTechMed Graz, Graz, Austria
| | - Kristian Bredies
- BioTechMed Graz, Graz, Austria
- Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Pablo Irarrazaval
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
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23
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Burgetova R, Dusek P, Burgetova A, Pudlac A, Vaneckova M, Horakova D, Krasensky J, Varga Z, Lambert L. Age-related magnetic susceptibility changes in deep grey matter and cerebral cortex of normal young and middle-aged adults depicted by whole brain analysis. Quant Imaging Med Surg 2021; 11:3906-3919. [PMID: 34476177 DOI: 10.21037/qims-21-87] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 04/19/2021] [Indexed: 12/31/2022]
Abstract
Background Iron accumulates in brain tissue in healthy subjects during aging. Our goal was to conduct a detailed analysis of iron deposition patterns in the cerebral deep grey matter and cortex using region-based and whole-brain analyses of brain magnetic susceptibility. Methods Brain MRI was performed in 95 healthy individuals aged between 21 and 58 years on a 3T scanner. MRI protocol included T1-weighted (T1W) magnetization-prepared rapid acquisition with gradient echo images and 3D flow-compensated multi-echo gradient-echo images for quantitative susceptibility mapping (QSM). In the region-based analysis, QSM and T1W images entered an automated multi-atlas segmentation pipeline and regional mean bulk susceptibility values were calculated. The whole-brain analysis included a non-linear transformation of QSM images to the standard MNI template. For the whole-brain analysis voxel-wise maps of linear regression slopes β and P values were calculated. Regional masks of cortical voxels with a significant association between susceptibility and age were created and further analyzed. Results In cortical regions, the highest increase of susceptibility values with age was found in areas involved in motor functions (precentral and postcentral areas, premotor cortex), in cognitive processing (prefrontal cortex, superior temporal gyrus, insula, precuneus), and visual processing (occipital gyri, cuneus, posterior cingulum, fusiform, calcarine and lingual gyrus). Thalamic susceptibility increased until the fourth decade and decreased thereafter with the exception of the pulvinar where susceptibility increase was observed throughout the adult lifespan. Deep grey matter structures with the highest increase of susceptibility values with age included the red nucleus, putamen, substantia nigra, dentate nucleus, external globus pallidus, caudate nucleus, and the subthalamic nucleus in decreasing order. Conclusions Accumulation of iron in basal ganglia follows a linear pattern whereas in the thalamus, pulvinar, precentral cortex, and precuneus, it follows a quadratic or exponential pattern. Age-related changes of iron content are different in the pulvinar and the rest of the thalamus as well as in internal and external globus pallidus. In the cortex, areas involved in motor and cognitive functions and visual processing show the highest iron increase with aging. We suggest that the departure from normal patterns of regional brain iron trajectories during aging may be helpful in the detection of subtle neurodegenerative and neuroinflammatory processes.
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Affiliation(s)
- Romana Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.,Department of Radiology, Third Faculty of Medicine, Charles University and University Hospital Královské Vinohrady, Prague, Czech Republic
| | - Petr Dusek
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.,Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Andrea Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Adam Pudlac
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Zsoka Varga
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Lukas Lambert
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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24
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Bilgic B, Langkammer C, Marques JP, Meineke J, Milovic C, Schweser F. QSM reconstruction challenge 2.0: Design and report of results. Magn Reson Med 2021; 86:1241-1255. [PMID: 33783037 DOI: 10.1002/mrm.28754] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/25/2021] [Accepted: 02/08/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE The aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data. METHODS A two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground truth data available to mimic the clinical setting. At the second stage, ground truth data were provided for parameter optimization. Submissions were evaluated using eight numerical metrics and visual ratings. RESULTS A total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and total variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art. CONCLUSION The synthetic data provide a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithms produced the best results among all metrics. Future QSM challenges should assess whether this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.
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Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA
| | | | - José P Marques
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands
| | | | - Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, New York, USA
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25
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Thomas GEC, Zarkali A, Ryten M, Shmueli K, Gil-Martinez AL, Leyland LA, McColgan P, Acosta-Cabronero J, Lees AJ, Weil RS. Regional brain iron and gene expression provide insights into neurodegeneration in Parkinson's disease. Brain 2021; 144:1787-1798. [PMID: 33704443 PMCID: PMC8320305 DOI: 10.1093/brain/awab084] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 11/20/2020] [Accepted: 12/14/2020] [Indexed: 12/11/2022] Open
Abstract
The mechanisms responsible for the selective vulnerability of specific neuronal populations in Parkinson's disease are poorly understood. Oxidative stress secondary to brain iron accumulation is one postulated mechanism. We measured iron deposition in 180 cortical regions of 96 patients with Parkinson's disease and 35 control subjects using quantitative susceptibility mapping. We estimated the expression of 15 745 genes in the same regions using transcriptomic data from the Allen Human Brain Atlas. Using partial least squares regression, we then identified the profile of gene transcription in the healthy brain that underlies increased cortical iron in patients with Parkinson's disease relative to controls. Applying gene ontological tools, we investigated the biological processes and cell types associated with this transcriptomic profile and identified the sets of genes with spatial expression profiles in control brains that correlated significantly with the spatial pattern of cortical iron deposition in Parkinson's disease. Gene ontological analyses revealed that these genes were enriched for biological processes relating to heavy metal detoxification, synaptic function and nervous system development and were predominantly expressed in astrocytes and glutamatergic neurons. Furthermore, we demonstrated that the genes differentially expressed in Parkinson's disease are associated with the pattern of cortical expression identified in this study. Our findings provide mechanistic insights into regional selective vulnerabilities in Parkinson's disease, particularly the processes involving iron accumulation.
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Affiliation(s)
| | | | - Mina Ryten
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1B 5EH, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, WC1N 1EH, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, WC1N 1EH, UK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, Malet Place Engineering Building, UCL, London, WC1E 6BT, UK
| | - Ana Luisa Gil-Martinez
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1B 5EH, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, WC1N 1EH, UK
| | | | - Peter McColgan
- Huntington’s Disease Centre, UCL Institute of Neurology, London, WC1B 5EH, UK
| | | | - Andrew J Lees
- Reta Lila Weston Institute of Neurological Studies, London, WC1N 1PJ, UK
| | - Rimona S Weil
- Dementia Research Centre, UCL, London, WC1N 3AR, UK
- Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK
- Movement Disorders Consortium, UCL, London, WC1N 3BG, UK
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26
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Chen L, Cai S, van Zijl PC, Li X. Single-step calculation of susceptibility through multiple orientation sampling. NMR IN BIOMEDICINE 2021; 34:e4517. [PMID: 33822416 PMCID: PMC8184590 DOI: 10.1002/nbm.4517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 03/06/2021] [Accepted: 03/14/2021] [Indexed: 06/12/2023]
Abstract
Quantitative susceptibility mapping (QSM) was developed to estimate the spatial distribution of magnetic susceptibility from MR signal phase acquired using a gradient echo (GRE) sequence. The field-to-susceptibility inversion in QSM is known to be ill-posed and needs numerical stabilization through either regularization or data oversampling. The calculation of susceptibility through the multiple orientation sampling (COSMOS) method uses phase data acquired at three or more head orientations to achieve a well-conditioned field-to-susceptibility inversion and is often considered the gold standard for in vivo QSM. However, the conventional COSMOS approach, here named multistep COSMOS (MSCOSMOS), solves the dipole inversion from the local field derived from raw GRE phase through multiple steps of phase preprocessing. Error propagations between these consecutive phase processing steps can thus affect the final susceptibility quantification. On the other hand, recently proposed single-step QSM (SSQSM) methods aim to solve an integrated inversion from unprocessed or total phase to mitigate such error propagations but have been limited to single orientation QSM. This study therefore aimed to test the feasibility of using single-step COSMOS (SSCOSMOS) to jointly perform background field removal and dipole inversion with multiple orientation sampling, which could serve as a better standard for gauging SSQSM methods. We incorporated multiple spherical mean value (SMV) kernels of various radii with the dipole inversion in SSCOSMOS. QSM reconstructions with SSCOSMOS and MSCOSMOS were compared using both simulations with a numerical head phantom and in vivo human brain data. SSCOSMOS permitted integrated background removal and dipole inversion without the need to adjust any regularization parameters. In addition, with sufficiently large SMV kernels, SSCOSMOS performed consistently better than MSCOSMOS in all the tested error metrics in our simulations, giving better susceptibility quantification and smaller reconstruction error. Consistent tissue susceptibility values were obtained between SSCOSMOS and MSCOSMOS.
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Affiliation(s)
- Lin Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Peter C.M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
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27
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Lüsebrink F, Mattern H, Yakupov R, Acosta-Cabronero J, Ashtarayeh M, Oeltze-Jafra S, Speck O. Comprehensive ultrahigh resolution whole brain in vivo MRI dataset as a human phantom. Sci Data 2021; 8:138. [PMID: 34035308 PMCID: PMC8149725 DOI: 10.1038/s41597-021-00923-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/13/2021] [Indexed: 11/09/2022] Open
Abstract
Here, we present an extension to our previously published structural ultrahigh resolution T1-weighted magnetic resonance imaging (MRI) dataset with an isotropic resolution of 250 µm, consisting of multiple additional ultrahigh resolution contrasts. Included are up to 150 µm Time-of-Flight angiography, an updated 250 µm structural T1-weighted reconstruction, 330 µm quantitative susceptibility mapping, up to 450 µm structural T2-weighted imaging, 700 µm T1-weighted back-to-back scans, 800 µm diffusion tensor imaging, one hour continuous resting-state functional MRI with an isotropic spatial resolution of 1.8 mm as well as more than 120 other structural T1-weighted volumes together with multiple corresponding proton density weighted acquisitions collected over ten years. All data are from the same participant and were acquired on the same 7 T scanner. The repository contains the unprocessed data as well as (pre-)processing results. The data were acquired in multiple studies with individual goals. This is a unique and comprehensive collection comprising a "human phantom" dataset. Therefore, we compiled, processed, and structured the data, making them publicly available for further investigation.
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Affiliation(s)
- Falk Lüsebrink
- Medicine and Digitalization, Department of Neurology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany.
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany.
| | - Hendrik Mattern
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany
| | - Renat Yakupov
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
| | | | - Mohammad Ashtarayeh
- Department of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Steffen Oeltze-Jafra
- Medicine and Digitalization, Department of Neurology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Oliver Speck
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
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28
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Oxtoby NP, Leyland LA, Aksman LM, Thomas GEC, Bunting EL, Wijeratne PA, Young AL, Zarkali A, Tan MMX, Bremner FD, Keane PA, Morris HR, Schrag AE, Alexander DC, Weil RS. Sequence of clinical and neurodegeneration events in Parkinson's disease progression. Brain 2021; 144:975-988. [PMID: 33543247 PMCID: PMC8041043 DOI: 10.1093/brain/awaa461] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/05/2020] [Accepted: 10/24/2020] [Indexed: 02/07/2023] Open
Abstract
Dementia is one of the most debilitating aspects of Parkinson's disease. There are no validated biomarkers that can track Parkinson's disease progression, nor accurately identify patients who will develop dementia and when. Understanding the sequence of observable changes in Parkinson's disease in people at elevated risk for developing dementia could provide an integrated biomarker for identifying and managing individuals who will develop Parkinson's dementia. We aimed to estimate the sequence of clinical and neurodegeneration events, and variability in this sequence, using data-driven statistical modelling in two separate Parkinson's cohorts, focusing on patients at elevated risk for dementia due to their age at symptom onset. We updated a novel version of an event-based model that has only recently been extended to cope naturally with clinical data, enabling its application in Parkinson's disease for the first time. The observational cohorts included healthy control subjects and patients with Parkinson's disease, of whom those diagnosed at age 65 or older were classified as having high risk of dementia. The model estimates that Parkinson's progression in patients at elevated risk for dementia starts with classic prodromal features of Parkinson's disease (olfaction, sleep), followed by early deficits in visual cognition and increased brain iron content, followed later by a less certain ordering of neurodegeneration in the substantia nigra and cortex, neuropsychological cognitive deficits, retinal thinning in dopamine layers, and further deficits in visual cognition. Importantly, we also characterize variation in the sequence. We found consistent, cross-validated results within cohorts, and agreement between cohorts on the subset of features available in both cohorts. Our sequencing results add powerful support to the increasing body of evidence suggesting that visual processing specifically is affected early in patients with Parkinson's disease at elevated risk of dementia. This opens a route to earlier and more precise detection, as well as a more detailed understanding of the pathological mechanisms underpinning Parkinson's dementia.
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Affiliation(s)
- Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science and Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | | | - Leon M Aksman
- Centre for Medical Image Computing, Department of Computer Science and Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - George E C Thomas
- Dementia Research Centre, UCL Institute of Neurology, UCL, London, UK
| | - Emma L Bunting
- Dementia Research Centre, UCL Institute of Neurology, UCL, London, UK
| | - Peter A Wijeratne
- Centre for Medical Image Computing, Department of Computer Science and Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science and Department of Medical Physics and Biomedical Engineering, UCL, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Angelika Zarkali
- Dementia Research Centre, UCL Institute of Neurology, UCL, London, UK
| | - Manuela M X Tan
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, UCL, London, UK
- Movement Disorders Consortium, UCL, London, UK
| | - Fion D Bremner
- Neuro-ophthalmology, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, UK
| | - Pearse A Keane
- Institute of Ophthalmology, UCL, London, UK
- Moorfields Eye Hospital, London, UK
| | - Huw R Morris
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, UCL, London, UK
- Movement Disorders Consortium, UCL, London, UK
| | - Anette E Schrag
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, UCL, London, UK
- Movement Disorders Consortium, UCL, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science and Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Rimona S Weil
- Dementia Research Centre, UCL Institute of Neurology, UCL, London, UK
- Movement Disorders Consortium, UCL, London, UK
- The Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, UCL, London, UK
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29
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Du J, Bydder GM. Brain Atrophy Is a Better Biomarker than Susceptibility for Evaluating Clinical Severity in Wilson Disease. Radiology 2021; 299:673-674. [PMID: 33759583 DOI: 10.1148/radiol.2021210106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Jiang Du
- From the Department of Radiology, University of California San Diego, 408 Dickinson St, San Diego, CA 92103-8226
| | - Graeme M Bydder
- From the Department of Radiology, University of California San Diego, 408 Dickinson St, San Diego, CA 92103-8226
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30
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Dusek P, Lescinskij A, Ruzicka F, Acosta-Cabronero J, Bruha R, Sieger T, Hajek M, Dezortova M. Associations of Brain Atrophy and Cerebral Iron Accumulation at MRI with Clinical Severity in Wilson Disease. Radiology 2021; 299:662-672. [PMID: 33754827 DOI: 10.1148/radiol.2021202846] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Abnormal findings at brain MRI in patients with neurologic Wilson disease (WD) are characterized by signal intensity changes and cerebral atrophy. T2 signal hypointensities and atrophy are largely irreversible with treatment; their relationship with permanent disability has not been systematically investigated. Purpose To investigate associations of regional brain atrophy and iron accumulation at MRI with clinical severity in participants with neurologic WD who are undergoing long-term anti-copper treatment. Materials and Methods Participants with WD and controls were compared in a prospective study performed from 2015 to 2019. MRI at 3.0 T included three-dimensional T1-weighted and six-echo multigradient-echo pulse sequences for morphometry and quantitative susceptibility mapping, respectively. Neurologic severity was assessed with the Unified WD Rating Scale (UWDRS). Automated multi-atlas segmentation pipeline with dual contrast (susceptibility and T1) was used for the calculation of volumes and mean susceptibilities in deep gray matter nuclei. Additionally, whole-brain analysis using deformation and surface-based morphometry was performed. Least absolute shrinkage and selection operator regression was used to assess the association of regional volumes and susceptibilities with the UWDRS score. Results Twenty-nine participants with WD (mean age, 47 years ± 9 [standard deviation]; 15 women) and 26 controls (mean age, 45 years ± 12; 14 women) were evaluated. Whole-brain analysis demonstrated atrophy of the deep gray matter nuclei, brainstem, internal capsule, motor cortex and corticospinal pathway, and visual cortex and optic radiation in participants with WD (P < .05 at voxel level, corrected for family-wise error). The UWDRS score was negatively correlated with volumes of putamen (r = -0.63, P < .001), red nucleus (r = -0.58, P = .001), globus pallidus (r = -0.53, P = .003), and substantia nigra (r = -0.50, P = .006) but not with susceptibilities. Only the putaminal volume was identified as a stable factor associated with the UWDRS score (R2 = 0.38, P < .001) using least absolute shrinkage and selection operator regression. Conclusion Individuals with Wilson disease (WD) had widespread brain atrophy most pronounced in the central structures. The putaminal volume was associated with the Unified WD Rating Scale score and can be used as a surrogate imaging marker of clinical severity. © RSNA, 2021 Supplemental material is available for this article. See also the editorial by Du and Bydder in this issue.
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Affiliation(s)
- Petr Dusek
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Artem Lescinskij
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Filip Ruzicka
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Julio Acosta-Cabronero
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Radan Bruha
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Tomas Sieger
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Milan Hajek
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Monika Dezortova
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
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31
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Rotta J, Perosa V, Yakupov R, Kuijf HJ, Schreiber F, Dobisch L, Oltmer J, Assmann A, Speck O, Heinze HJ, Acosta-Cabronero J, Duzel E, Schreiber S. Detection of Cerebral Microbleeds With Venous Connection at 7-Tesla MRI. Neurology 2021; 96:e2048-e2057. [PMID: 33653897 DOI: 10.1212/wnl.0000000000011790] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 01/28/2021] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Cerebral microbleeds (MBs) are a common finding in patients with cerebral small vessel disease (CSVD) and Alzheimer disease as well as in healthy elderly people, but their pathophysiology remains unclear. To investigate a possible role of veins in the development of MBs, we performed an exploratory study, assessing in vivo presence of MBs with a direct connection to a vein. METHODS 7-Tesla (7T) MRI was conducted and MBs were counted on quantitative susceptibility mapping (QSM). A submillimeter resolution QSM-based venogram allowed identification of MBs with a direct spatial connection to a vein. RESULTS A total of 51 people (mean age [SD] 70.5 [8.6] years, 37% female) participated in the study: 20 had CSVD (cerebral amyloid angiopathy [CAA] with strictly lobar MBs [n = 8], hypertensive arteriopathy [HA] with strictly deep MBs [n = 5], or mixed lobar and deep MBs [n = 7], 72.4 [6.1] years, 30% female) and 31 were healthy controls (69.4 [9.9] years, 42% female). In our cohort, we counted a total of 96 MBs with a venous connection, representing 14% of all detected MBs on 7T QSM. Most venous MBs (86%, n = 83) were observed in lobar locations and all of these were cortical. Patients with CAA showed the highest ratio of venous to total MBs (19%) (HA = 9%, mixed = 18%, controls = 5%). CONCLUSION Our findings establish a link between cerebral MBs and the venous vasculature, pointing towards a possible contribution of veins to CSVD in general and to CAA in particular. Pathologic studies are needed to confirm our observations.
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Affiliation(s)
- Johanna Rotta
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Valentina Perosa
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK.
| | - Renat Yakupov
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hugo J Kuijf
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Frank Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Laura Dobisch
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Jan Oltmer
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Anne Assmann
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Oliver Speck
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hans-Jochen Heinze
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Julio Acosta-Cabronero
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Emrah Duzel
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Stefanie Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
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Chary K, Nissi MJ, Nykänen O, Manninen E, Rey RI, Shmueli K, Sierra A, Gröhn O. Quantitative susceptibility mapping of the rat brain after traumatic brain injury. NMR IN BIOMEDICINE 2021; 34:e4438. [PMID: 33219598 DOI: 10.1002/nbm.4438] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Revised: 10/13/2020] [Accepted: 10/14/2020] [Indexed: 06/11/2023]
Abstract
The primary lesion arising from the initial insult after traumatic brain injury (TBI) triggers a cascade of secondary tissue damage, which may also progress to connected brain areas in the chronic phase. The aim of this study was, therefore, to investigate variations in the susceptibility distribution related to these secondary tissue changes in a rat model after severe lateral fluid percussion injury. We compared quantitative susceptibility mapping (QSM) and R2 * measurements with histological analyses in white and grey matter areas outside the primary lesion but connected to the lesion site. We demonstrate that susceptibility variations in white and grey matter areas could be attributed to reduction in myelin, accumulation of iron and calcium, and gliosis. QSM showed quantitative changes attributed to secondary damage in areas located rostral to the lesion site that appeared normal in R2 * maps. However, combination of QSM and R2 * was informative in disentangling the underlying tissue changes such as iron accumulation, demyelination, or calcifications. Therefore, combining QSM with R2 * measurement can provide a more detailed assessment of tissue changes and may pave the way for improved diagnosis of TBI, and several other complex neurodegenerative diseases.
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Affiliation(s)
- Karthik Chary
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mikko J Nissi
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Olli Nykänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Eppu Manninen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ramón I Rey
- Clinical Neurosciences Research Laboratory, Department of Neurology, Health Research Institute of Santiago de Compostela, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Alejandra Sierra
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Olli Gröhn
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
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Cooper G, Hirsch S, Scheel M, Brandt AU, Paul F, Finke C, Boehm-Sturm P, Hetzer S. Quantitative Multi-Parameter Mapping Optimized for the Clinical Routine. Front Neurosci 2020; 14:611194. [PMID: 33364921 PMCID: PMC7750476 DOI: 10.3389/fnins.2020.611194] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 11/16/2020] [Indexed: 12/12/2022] Open
Abstract
Using quantitative multi-parameter mapping (MPM), studies can investigate clinically relevant microstructural changes with high reliability over time and across subjects and sites. However, long acquisition times (20 min for the standard 1-mm isotropic protocol) limit its translational potential. This study aimed to evaluate the sensitivity gain of a fast 1.6-mm isotropic MPM protocol including post-processing optimized for longitudinal clinical studies. 6 healthy volunteers (35±7 years old; 3 female) were scanned at 3T to acquire the following whole-brain MPM maps with 1.6 mm isotropic resolution: proton density (PD), magnetization transfer saturation (MT), longitudinal relaxation rate (R1), and transverse relaxation rate (R2*). MPM maps were generated using two RF transmit field (B1+) correction methods: (1) using an acquired B1+ map and (2) using a data-driven approach. Maps were generated with and without Gibb's ringing correction. The intra-/inter-subject coefficient of variation (CoV) of all maps in the gray and white matter, as well as in all anatomical regions of a fine-grained brain atlas, were compared between the different post-processing methods using Student's t-test. The intra-subject stability of the 1.6-mm MPM protocol is 2–3 times higher than for the standard 1-mm sequence and can be achieved in less than half the scan duration. Intra-subject variability for all four maps in white matter ranged from 1.2–5.3% and in gray matter from 1.8 to 9.2%. Bias-field correction using an acquired B1+ map significantly improved intra-subject variability of PD and R1 in the gray (42%) and white matter (54%) and correcting the raw images for the effect of Gibb's ringing further improved intra-subject variability in all maps in the gray (11%) and white matter (10%). Combining Gibb's ringing correction and bias field correction using acquired B1+ maps provides excellent stability of the 7-min MPM sequence with 1.6 mm resolution suitable for the clinical routine.
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Affiliation(s)
- Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Experimental Neurology and Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sebastian Hirsch
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Department of Neuroradiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Philipp Boehm-Sturm
- Department of Experimental Neurology and Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,NeuroCure Cluster of Excellence and Charité Core Facility 7T Experimental MRIs, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
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Abstract
The habenula plays an important role in brain reward circuitry and psychiatric conditions. While much work has been done on the function and structure of the habenula in animal models, in vivo imaging studies of the human habenula have been relatively scarce due to its small size, deep brain location, and lack of clear biomarkers for its heterogeneous substructure. In this paper, we report high-resolution (0.5 × 0.5 × 0.8 mm3) MRI of the human habenula with quantitative susceptibility mapping (QSM) at 3 T. By analyzing 48 scan datasets collected from 21 healthy subjects, we found that magnetic susceptibility contrast is highly non-uniform within the habenula and across the subjects. In particular, we observed high prevalence of elevated susceptibility in the posterior subregion of the habenula. Correlation analysis between the susceptibility and the effective transverse relaxation rate (R2*) indicated that localized susceptibility enhancement in the habenula is more associated with increased paramagnetic (such as iron) rather than decreased diamagnetic (such as myelin) sources. Our results suggest that high-resolution QSM could make a potentially useful tool for substructure-resolved in vivo habenula imaging, and provide a groundwork for the future development of magnetic susceptibility as a quantitative biomarker for human habenula studies.
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Cogswell PM, Wiste HJ, Senjem ML, Gunter JL, Weigand SD, Schwarz CG, Arani A, Therneau TM, Lowe VJ, Knopman DS, Botha H, Graff-Radford J, Jones DT, Kantarci K, Vemuri P, Boeve BF, Mielke MM, Petersen RC, Jack CR. Associations of quantitative susceptibility mapping with Alzheimer's disease clinical and imaging markers. Neuroimage 2020; 224:117433. [PMID: 33035667 PMCID: PMC7860631 DOI: 10.1016/j.neuroimage.2020.117433] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 09/29/2020] [Indexed: 02/07/2023] Open
Abstract
Altered iron metabolism has been hypothesized to be associated with Alzheimer’s disease pathology, and prior work has shown associations between iron load and beta amyloid plaques. Quantitative susceptibility mapping (QSM) is a recently popularized MR technique to infer local tissue susceptibility secondary to the presence of iron as well as other minerals. Greater QSM values imply greater iron concentration in tissue. QSM has been used to study relationships between cerebral iron load and established markers of Alzheimer’s disease, however relationships remain unclear. In this work we study QSM signal characteristics and associations between susceptibility measured on QSM and established clinical and imaging markers of Alzheimer’s disease. The study included 421 participants (234 male, median age 70 years, range 34–97 years) from the Mayo Clinic Study of Aging and Alzheimer’s Disease Research Center; 296 (70%) had a diagnosis of cognitively unimpaired, 69 (16%) mild cognitive impairment, and 56 (13%) amnestic dementia. All participants had multi-echo gradient recalled echo imaging, PiB amyloid PET, and Tauvid tau PET. Variance components analysis showed that variation in cortical susceptibility across participants was low. Linear regression models were fit to assess associations with regional susceptibility. Expected increases in susceptibility were found with older age and cognitive impairment in the deep and inferior gray nuclei (pallidum, putamen, substantia nigra, subthalamic nucleus) (betas: 0.0017 to 0.0053 ppm for a 10 year increase in age, p = 0.03 to < 0.001; betas: 0.0021 to 0.0058 ppm for a 5 point decrease in Short Test of Mental Status, p = 0.003 to p < 0.001). Effect sizes in cortical regions were smaller, and the age associations were generally negative. Higher susceptibility was significantly associated with higher amyloid PET SUVR in the pallidum and putamen (betas: 0.0029 and 0.0012 ppm for a 20% increase in amyloid PET, p = 0.05 and 0.02, respectively), higher tau PET in the basal ganglia with the largest effect size in the pallidum (0.0082 ppm for a 20% increase in tau PET, p < 0.001), and with lower cortical gray matter volume in the medial temporal lobe (0.0006 ppm for a 20% decrease in volume, p = 0.03). Overall, these findings suggest that susceptibility in the deep and inferior gray nuclei, particularly the pallidum and putamen, may be a marker of cognitive decline, amyloid deposition, and off-target binding of the tau ligand. Although iron has been demonstrated in amyloid plaques and in association with neurodegeneration, it is of insufficient quantity to be reliably detected in the cortex using this implementation of QSM.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA; Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA; Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | | | - Arvin Arani
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Terry M Therneau
- Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA; Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Ronald C Petersen
- Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA; Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
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Isaacs BR, Keuken MC, Alkemade A, Temel Y, Bazin PL, Forstmann BU. Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients. J Clin Med 2020; 9:E3124. [PMID: 32992558 PMCID: PMC7600568 DOI: 10.3390/jcm9103124] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/17/2020] [Accepted: 09/25/2020] [Indexed: 12/17/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.
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Affiliation(s)
- Bethany R. Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Max C. Keuken
- Municipality of Amsterdam, Services & Data, Cluster Social, 1000 AE Amsterdam, The Netherlands;
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
| | - Yasin Temel
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Pierre-Louis Bazin
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
| | - Birte U. Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
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Multi-centre, multi-vendor reproducibility of 7T QSM and R 2* in the human brain: Results from the UK7T study. Neuroimage 2020; 223:117358. [PMID: 32916289 PMCID: PMC7480266 DOI: 10.1016/j.neuroimage.2020.117358] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 09/03/2020] [Accepted: 09/03/2020] [Indexed: 12/13/2022] Open
Abstract
Introduction We present the reliability of ultra-high field T2* MRI at 7T, as part of the UK7T Network's “Travelling Heads” study. T2*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R2* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R2* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5–3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R2* mapping at 7T, in readiness for future multi-site clinical studies. Methods Ten healthy volunteers were scanned with harmonised single- and multi-echo T2*-weighted gradient echo pulse sequences. Participants were scanned five times at each “home” site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R2* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space. Results and Discussion Mean susceptibility (χ) and R2* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001–0.005 ppm (χ) and 0.0005–0.001 ms−1 (R2*). For χ this is 2.1–4.8 fold better than 3T reports, and 1.1–3.4 fold better for R2*. The median ICC from within- and cross-site R2* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B0 inhomogeneity such as the inferior frontal cortex. Across sites, R2* values were more consistent than QSM in subcortical structures due to differences in B0-shimming. On a between-subject level, our measured χ and R2* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol. Conclusion The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.
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Rittman T. Neurological update: neuroimaging in dementia. J Neurol 2020; 267:3429-3435. [PMID: 32638104 PMCID: PMC7578138 DOI: 10.1007/s00415-020-10040-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 06/26/2020] [Accepted: 06/30/2020] [Indexed: 12/18/2022]
Abstract
Neuroimaging for dementia has made remarkable progress in recent years, shedding light on diagnostic subtypes of dementia, predicting prognosis and monitoring pathology. This review covers some updates in the understanding of dementia using structural imaging, positron emission tomography (PET), structural and functional connectivity, and using big data and artificial intelligence. Progress with neuroimaging methods allows neuropathology to be examined in vivo, providing a suite of biomarkers for understanding neurodegeneration and for application in clinical trials. In addition, we highlight quantitative susceptibility imaging as an exciting new technique that may prove to be a sensitive biomarker for a range of neurodegenerative diseases. There are challenges in translating novel imaging techniques to clinical practice, particularly in developing standard methodologies and overcoming regulatory issues. It is likely that clinicians will need to lead the way if these obstacles are to be overcome. Continued efforts applying neuroimaging to understand mechanisms of neurodegeneration and translating them to clinical practice will complete a revolution in neuroimaging.
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Affiliation(s)
- Timothy Rittman
- Department of Neurosciences, University of Cambridge, Cambridge, UK.
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Biondetti E, Karsa A, Thomas DL, Shmueli K. Investigating the accuracy and precision of TE-dependent versus multi-echo QSM using Laplacian-based methods at 3 T. Magn Reson Med 2020; 84:3040-3053. [PMID: 32491224 DOI: 10.1002/mrm.28331] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 03/19/2020] [Accepted: 04/29/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE Multi-echo gradient-recalled echo acquisitions for QSM enable optimizing the SNR for several tissue types through multi-echo (TE) combination or investigating temporal variations in the susceptibility (potentially reflecting tissue microstructure) by calculating one QSM image at each TE (TE-dependent QSM). In contrast with multi-echo QSM, applying Laplacian-based methods (LBMs) for phase unwrapping and background field removal to single TEs could introduce nonlinear temporal variations (independent of tissue microstructure) into the measured susceptibility. Here, we aimed to compare the effect of LBMs on the QSM susceptibilities in TE-dependent versus multi-echo QSM. METHODS TE-dependent recalled echo data simulated in a numerical head phantom and gradient-recalled echo images acquired at 3 T in 10 healthy volunteers. Several QSM pipelines were tested, including four distinct LBMs: sophisticated harmonic artifact reduction for phase data (SHARP), variable-radius sophisticated harmonic artifact reduction for phase data (V-SHARP), Laplacian boundary value background field removal (LBV), and one-step total generalized variation (TGV). Results from distinct pipelines were compared using visual inspection, summary statistics of susceptibility in deep gray matter/white matter/venous regions of interest, and, in the healthy volunteers, regional susceptibility bias analysis and nonparametric tests. RESULTS Multi-echo versus TE-dependent QSM had higher regional accuracy, especially in high-susceptibility regions and at shorter TEs. Everywhere except in the veins, a processing pipeline incorporating TGV provided the most temporally stable TE-dependent QSM results with an accuracy similar to multi-echo QSM. CONCLUSIONS For TE-dependent QSM, carefully choosing LBMs can minimize the introduction of LBM-related nonlinear temporal susceptibility variations.
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Affiliation(s)
- Emma Biondetti
- Centre de NeuroImagerie de Recherche (CENIR), Team "Movement Investigations and Therapeutics", Institut du Cerveau (ICM), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France.,Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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40
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Spotorno N, Acosta-Cabronero J, Stomrud E, Lampinen B, Strandberg OT, van Westen D, Hansson O. Relationship between cortical iron and tau aggregation in Alzheimer's disease. Brain 2020; 143:1341-1349. [PMID: 32330946 PMCID: PMC7241946 DOI: 10.1093/brain/awaa089] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 02/05/2020] [Accepted: 02/10/2020] [Indexed: 12/14/2022] Open
Abstract
A growing body of evidence suggests that the dysregulation of neuronal iron may play a critical role in Alzheimer's disease. Recent MRI studies have established a relationship between iron accumulation and amyloid-β aggregation. The present study provides further insight demonstrating a relationship between iron and tau accumulation using magnetic resonance-based quantitative susceptibility mapping and tau-PET in n = 236 subjects with amyloid-β pathology (from the Swedish BioFINDER-2 study). Both voxel-wise and regional analyses showed a consistent association between differences in bulk magnetic susceptibility, which can be primarily ascribed to an increase in iron content, and tau-PET signal in regions known to be affected in Alzheimer's disease. Subsequent analyses revealed that quantitative susceptibility specifically mediates the relationship between tau-PET and cortical atrophy measures, thus suggesting a modulatory effect of iron burden on the disease process. We also found evidence suggesting the relationship between quantitative susceptibility and tau-PET is stronger in younger participants (age ≤ 65). Together, these results provide in vivo evidence of an association between iron deposition and both tau aggregation and neurodegeneration, which help advance our understanding of the role of iron dysregulation in the Alzheimer's disease aetiology.
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Affiliation(s)
- Nicola Spotorno
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Björn Lampinen
- Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden
| | - Olof T Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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41
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Thomas GEC, Leyland LA, Schrag AE, Lees AJ, Acosta-Cabronero J, Weil RS. Brain iron deposition is linked with cognitive severity in Parkinson's disease. J Neurol Neurosurg Psychiatry 2020; 91:418-425. [PMID: 32079673 PMCID: PMC7147185 DOI: 10.1136/jnnp-2019-322042] [Citation(s) in RCA: 101] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 01/14/2020] [Accepted: 01/22/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Dementia is common in Parkinson's disease (PD) but measures that track cognitive change in PD are lacking. Brain tissue iron accumulates with age and co-localises with pathological proteins linked to PD dementia such as amyloid. We used quantitative susceptibility mapping (QSM) to detect changes related to cognitive change in PD. METHODS We assessed 100 patients with early-stage to mid-stage PD, and 37 age-matched controls using the Montreal Cognitive Assessment (MoCA), a validated clinical algorithm for risk of cognitive decline in PD, measures of visuoperceptual function and the Movement Disorders Society Unified Parkinson's Disease Rating Scale part 3 (UPDRS-III). We investigated the association between these measures and QSM, an MRI technique sensitive to brain tissue iron content. RESULTS We found QSM increases (consistent with higher brain tissue iron content) in PD compared with controls in prefrontal cortex and putamen (p<0.05 corrected for multiple comparisons). Whole brain regression analyses within the PD group identified QSM increases covarying: (1) with lower MoCA scores in the hippocampus and thalamus, (2) with poorer visual function and with higher dementia risk scores in parietal, frontal and medial occipital cortices, (3) with higher UPDRS-III scores in the putamen (all p<0.05 corrected for multiple comparisons). In contrast, atrophy, measured using voxel-based morphometry, showed no differences between groups, or in association with clinical measures. CONCLUSIONS Brain tissue iron, measured using QSM, can track cognitive involvement in PD. This may be useful to detect signs of early cognitive change to stratify groups for clinical trials and monitor disease progression.
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Affiliation(s)
| | | | - Anette-Eleonore Schrag
- Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK
- Movement Disorders Consortium, University College London, London, UK
| | - Andrew John Lees
- Reta Lila Institute for Brain Studies, University College London, London, UK
| | | | - Rimona Sharon Weil
- Dementia Research Centre, UCL Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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42
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Olsson H, Andersen M, Lätt J, Wirestam R, Helms G. Reducing bias in dual flip angle T
1
‐mapping in human brain at 7T. Magn Reson Med 2020; 84:1347-1358. [DOI: 10.1002/mrm.28206] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 01/19/2020] [Accepted: 01/20/2020] [Indexed: 12/11/2022]
Affiliation(s)
- Hampus Olsson
- Department of Medical Radiation Physics Clinical Sciences Lund Lund University Lund Sweden
| | | | - Jimmy Lätt
- Center for Medical Imaging and Physiology Skane University Hospital Lund Sweden
| | - Ronnie Wirestam
- Department of Medical Radiation Physics Clinical Sciences Lund Lund University Lund Sweden
| | - Gunther Helms
- Department of Medical Radiation Physics Clinical Sciences Lund Lund University Lund Sweden
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43
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Multi-site harmonization of 7 tesla MRI neuroimaging protocols. Neuroimage 2019; 206:116335. [PMID: 31712167 PMCID: PMC7212005 DOI: 10.1016/j.neuroimage.2019.116335] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 10/25/2019] [Accepted: 11/04/2019] [Indexed: 12/11/2022] Open
Abstract
Increasing numbers of 7 T (7 T) magnetic resonance imaging (MRI) scanners are in research and clinical use. 7 T MRI can increase the scanning speed, spatial resolution and contrast-to-noise-ratio of many neuroimaging protocols, but technical challenges in implementation have been addressed in a variety of ways across sites. In order to facilitate multi-centre studies and ensure consistency of findings across sites, it is desirable that 7 T MRI sites implement common high-quality neuroimaging protocols that can accommodate different scanner models and software versions. With the installation of several new 7 T MRI scanners in the United Kingdom, the UK7T Network was established with an aim to create a set of harmonized structural and functional neuroimaging sequences and protocols. The Network currently includes five sites, which use three different scanner platforms, provided by two different vendors. Here we describe the harmonization of functional and anatomical imaging protocols across the three different scanner models, detailing the necessary changes to pulse sequences and reconstruction methods. The harmonized sequences are fully described, along with implementation details. Example datasets acquired from the same subject on all Network scanners are made available. Based on these data, an evaluation of the harmonization is provided. In addition, the implementation and validation of a common system calibration process is described.
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44
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Dusek P, Mekle R, Skowronska M, Acosta-Cabronero J, Huelnhagen T, Robinson SD, Schubert F, Deschauer M, Els A, Ittermann B, Schottmann G, Madai VI, Paul F, Klopstock T, Kmiec T, Niendorf T, Wuerfel J, Schneider SA. Brain iron and metabolic abnormalities in C19orf12 mutation carriers: A 7.0 tesla MRI study in mitochondrial membrane protein-associated neurodegeneration. Mov Disord 2019; 35:142-150. [PMID: 31518459 DOI: 10.1002/mds.27827] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 07/20/2019] [Accepted: 07/24/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Mitochondrial membrane protein-associated neurodegeneration is an autosomal-recessive disorder caused by C19orf12 mutations and characterized by iron deposits in the basal ganglia. OBJECTIVES The aim of this study was to quantify iron concentrations in deep gray matter structures using quantitative susceptibility mapping MRI and to characterize metabolic abnormalities in the pyramidal pathway using 1 H MR spectroscopy in clinically manifesting membrane protein-associated neurodegeneration patients and asymptomatic C19orf12 gene mutation heterozygous carriers. METHODS We present data of 4 clinically affected membrane protein-associated neurodegeneration patients (mean age: 21.0 ± 2.9 years) and 9 heterozygous gene mutation carriers (mean age: 50.4 ± 9.8 years), compared to age-matched healthy controls. MRI assessments were performed on a 7.0 Tesla whole-body system, consisting of whole-brain gradient-echo scans and short echo time, single-volume MR spectroscopy in the white matter of the precentral/postcentral gyrus. Quantitative susceptibility mapping, a surrogate marker for iron concentration, was performed using a state-of-the-art multiscale dipole inversion approach with focus on the globus pallidus, thalamus, putamen, caudate nucleus, and SN. RESULTS AND CONCLUSION In membrane protein-associated neurodegeneration patients, magnetic susceptibilities were 2 to 3 times higher in the globus pallidus (P = 0.02) and SN (P = 0.02) compared to controls. In addition, significantly higher magnetic susceptibility was observed in the caudate nucleus (P = 0.02). Non-manifesting heterozygous mutation carriers exhibited significantly increased magnetic susceptibility (relative to controls) in the putamen (P = 0.003) and caudate nucleus (P = 0.001), which may be an endophenotypic marker of genetic heterozygosity. MR spectroscopy revealed significantly increased levels of glutamate, taurine, and the combined concentration of glutamate and glutamine in membrane protein-associated neurodegeneration, which may be a correlate of corticospinal pathway dysfunction frequently observed in membrane protein-associated neurodegeneration patients. © 2019 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Petr Dusek
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Prague, Czechia.,Department of Radiology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Prague, Czechia
| | - Ralf Mekle
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.,Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Marta Skowronska
- 2nd Department of Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Till Huelnhagen
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Florian Schubert
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Marcus Deschauer
- Department of Neurology, Technical University Munich, Munich, Germany
| | - Antje Els
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Gudrun Schottmann
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Vince I Madai
- Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Thomas Klopstock
- Department of Neurology with Friedrich-Baur-Institute, Ludwig-Maximilians-University of Munich, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Tomasz Kmiec
- Department of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, Poland
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Jens Wuerfel
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany.,Medical Image Analysis Center and Department Biomedical Engineering, University Basel, Basel, Switzerland
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45
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Tabelow K, Balteau E, Ashburner J, Callaghan MF, Draganski B, Helms G, Kherif F, Leutritz T, Lutti A, Phillips C, Reimer E, Ruthotto L, Seif M, Weiskopf N, Ziegler G, Mohammadi S. hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. Neuroimage 2019; 194:191-210. [PMID: 30677501 PMCID: PMC6547054 DOI: 10.1016/j.neuroimage.2019.01.029] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 12/21/2018] [Accepted: 01/10/2019] [Indexed: 12/20/2022] Open
Abstract
Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.
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Affiliation(s)
| | | | | | | | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gunther Helms
- Medical Radiation Physics, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | | | - Enrico Reimer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gabriel Ziegler
- Institute for Cognitive Neurology and Dementia Research, University of Magdeburg, Germany
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Lancione M, Donatelli G, Cecchi P, Cosottini M, Tosetti M, Costagli M. Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths. Neuroimage 2019; 197:557-564. [PMID: 31075389 DOI: 10.1016/j.neuroimage.2019.05.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 04/10/2019] [Accepted: 05/02/2019] [Indexed: 12/13/2022] Open
Abstract
Quantitative Susceptibility Mapping (QSM) provides a way of measuring iron concentration and myelination non-invasively and has the potential of becoming a tool of paramount importance in the study of a host of different pathologies. However, several experimental factors and the physical properties of magnetic susceptibility (χ) can impair the reliability of QSM, and it is therefore essential to assess QSM reproducibility for repeated acquisitions and different field strength. In particular, it has recently been demonstrated that QSM measurements strongly depend on echo time (TE): the same tissue, measured on the same scanner, exhibits different apparent frequency shifts depending on the TE used. This study aims to assess the influence of TE on intra-scanner and inter-scanner reproducibility of QSM, by using MRI systems operating at 3T and 7T. To maximize intra-scanner reproducibility it is necessary to match the TEs of the acquisition protocol, but the application of this rule leads to inconsistent QSM values across scanners operating at different static magnetic field. This study however demonstrates that, provided a careful choice of acquisition parameters, and in particular by using TEs at 3T that are approximately 2.6 times longer than those at 7T, highly reproducible whole-brain χ maps can be achieved also across different scanners, which renders QSM a suitable technique for longitudinal follow-up in clinical settings and in multi-center studies.
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Affiliation(s)
| | - Graziella Donatelli
- IMAGO7 Foundation, Pisa, Italy; Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Paolo Cecchi
- Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | | | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy; IRCCS Stella Maris, Pisa, Italy.
| | - Mauro Costagli
- IMAGO7 Foundation, Pisa, Italy; IRCCS Stella Maris, Pisa, Italy
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