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Ladopoulos T, Abbas Z, Krieger B, Bellenberg B, James JC, Bauer J, Gold R, Lukas C, Schneider R. Neurological disability and brain grey matter atrophy in primary progressive multiple sclerosis are determined by microstructural lesional changes, but not by lesion load. J Neurol 2025; 272:302. [PMID: 40167785 PMCID: PMC11961454 DOI: 10.1007/s00415-025-13043-x] [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: 12/07/2024] [Revised: 03/08/2025] [Accepted: 03/14/2025] [Indexed: 04/02/2025]
Abstract
BACKGROUND Conventional MRI measures, such as the number and volume of MS lesions, are histologically non-specific and cannot sufficiently explain clinical disability or brain atrophy in MS. Nevertheless, demyelinating plaques exhibit distinct histopathological features in relapsing and progressive multiple sclerosis (MS) subtypes. The aim of this study was to assess microstructural characteristics of MS lesions using quantitative MRI and explore their associations with grey matter (GM) atrophy and clinical disability. METHODS 56 control subjects (CS), 121 patients with relapsing-remitting (RRMS), and 38 patients with primary progressive MS (PPMS) underwent 1.5 T MRI scans and clinical examinations. Lesion and brain segmentation based on T1-weighted and FLAIR images were performed using SAMSEG. The MDME sequence and SyMRI software were used to estimate relaxation rates and myelin volume fraction in MS lesions and normal-appearing white matter (NAWM). Associations between quantitative lesional and NAWM MRI parameters with GM atrophy and clinical disability were investigated. RESULTS Brain regional volumes and quantitative lesional and NAWM MRI parameters were significantly decreased in patients with PPMS compared to those with RRMS. Quantitative lesional MRI parameters demonstrated statistically significant associations with cortical and deep GM volumes as well as with disability scores in RRMS and especially in PPMS. In contrast to RRMS, lesion volume was not associated with either GM atrophy or clinical disability in the PPMS group. CONCLUSIONS Quantitative lesional MRI measures, but not lesion load, were strongly associated with clinical disability and GM atrophy in PPMS patients, likely reflecting differences in lesion pathology between MS subtypes.
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Affiliation(s)
- Theodoros Ladopoulos
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany.
- Institute of Neuroradiology, St Josef Hospital, Ruhr University, Bochum, Germany.
| | - Zainab Abbas
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
| | - Britta Krieger
- Institute of Neuroradiology, St Josef Hospital, Ruhr University, Bochum, Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St Josef Hospital, Ruhr University, Bochum, Germany
| | - Jeyanthan Charles James
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
| | - Jana Bauer
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
| | - Ralf Gold
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
| | - Carsten Lukas
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
- Institute of Neuroradiology, St Josef Hospital, Ruhr University, Bochum, Germany
| | - Ruth Schneider
- Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany
- Institute of Neuroradiology, St Josef Hospital, Ruhr University, Bochum, Germany
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Sisk LM, Keding TJ, Cohodes EM, McCauley S, Pierre JC, Odriozola P, Kribakaran S, Haberman JT, Zacharek SJ, Hodges HR, Caballero C, Gold G, Huang AY, Talton A, Gee DG. Multivariate links between the developmental timing of adversity exposure and white matter tract connectivity in adulthood. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2025:S2451-9022(25)00060-6. [PMID: 39978462 DOI: 10.1016/j.bpsc.2025.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2024] [Revised: 01/17/2025] [Accepted: 02/10/2025] [Indexed: 02/22/2025]
Abstract
BACKGROUND Early-life adversity is pervasive worldwide and represents a potent risk factor for increased mental health burden across the lifespan. However, there is substantial individual heterogeneity in associations between adversity exposure, neurobiological changes, and mental health problems. Accounting for key features of adversity such as the developmental timing of exposure may clarify associations between adversity, neurodevelopment, and mental health. METHODS The present study leverages sparse canonical correlation analysis to characterize modes of covariation between adversity exposure across development and the connectivity of white matter tracts throughout the brain in a sample of 107 adults. RESULTS We found that adversity exposure during preschool-age and middle childhood (ages 4-5 and 8 in particular) were consistently linked across diffusion metrics with alterations in white matter tract connectivity. Whereas tracts supporting sensorimotor functions displayed higher connectivity with higher preschool-age and middle childhood adversity exposure, tracts supporting cortico-cortical communication displayed lower connectivity. Further, latent patterns of tract connectivity linked with adversity experienced across preschool-age and middle childhood (ages 3-8) were associated with post-traumatic stress symptoms in adulthood. CONCLUSIONS Our findings underscore that adversity exposure may differentially affect white matter in a function- and developmental-timing specific manner and suggest that adversity experienced between ages 3-8 may shape the development of white matter tracts across the brain in ways that are relevant for mental health in adulthood.
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Affiliation(s)
- Lucinda M Sisk
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Taylor J Keding
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Emily M Cohodes
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Sarah McCauley
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Jasmyne C Pierre
- Department of Psychology, The City College of New York, New York, NY, USA
| | - Paola Odriozola
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Sahana Kribakaran
- Department of Psychology, Yale University, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | | | - Sadie J Zacharek
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hopewell R Hodges
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | | | - Gillian Gold
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Audrey Y Huang
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Ashley Talton
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Dylan G Gee
- Department of Psychology, Yale University, New Haven, CT, USA.
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Liang Y, Huang J, Zhang X, Xu F, Bo C, Lin M, Wen X. Quantitative assessment of thalamic damage and serum neurofilament light chain in relapsing-remitting multiple sclerosis. J Neuroimmunol 2025; 399:578504. [PMID: 39647403 DOI: 10.1016/j.jneuroim.2024.578504] [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: 09/13/2024] [Revised: 11/08/2024] [Accepted: 11/30/2024] [Indexed: 12/10/2024]
Abstract
BACKGROUND The study assessed group differences in the thalamus microstructural parameters among healthy individuals and relapsing-remitting multiple sclerosis (RRMS) patients and examined the relationship between quantitative MRI (qMRI) parameters and neurological scores, T2 lesion load, and serum neurofilament light chain (sNfL) levels. METHODS A total of 30 patients with RRMS and 26 age- and sex-matched healthy controls were recruited in this study. The qMRI images were obtained from these individuals. T2 lesion load, thalamic volume, and parameters of thalamic subnuclei were estimated. The neurological functions of participants were assessed using a battery of tests. sNfL concentrations were measured using the single molecule array (SIMOA) technique. RESULTS T2 relaxometry in the whole thalamus and its subnuclei were increased, and showed an apparent correlation with T2 lesion load and the severity of MS (EDSS, MSSS, 9HPT, T25FW, SDMT). T1 variability was prolonged in most thalamic subnuclei, and it was correlated with the severity of MS (EDSS, 9HPT, SDMT). Thalamic volumetric parameters of MS patients were smaller than those of healthy controls (p < 0.001) and showed an apparent correlation with MS severity. Surprisingly, sNfL levels showed no correlation with T2 relaxometry, T1 variability, or thalamic volumetric parameters. CONCLUSION Quantitative synthetic MRI, especially, the metric T2 relaxation times provides a surrogate parameter for assessing underlying thalamic and subnuclei damage in the RRMS group. Integrating structural and quantitative MRI allows a better assessment of the neurodegeneration in the normal-appearing thalamus of RRMS.
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Affiliation(s)
- Yan Liang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Huang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiyue Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Fang Xu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chunrui Bo
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Ming Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xinmei Wen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
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Boa Sorte Silva NC, Balbim GM, Stein RG, Gu Y, Tam RC, Dao E, Alkeridy W, Lam K, Kramer AF, Liu‐Ambrose T. Physical activity may protect myelin via modulation of high-density lipoprotein. Alzheimers Dement 2025; 21:e14599. [PMID: 39989020 PMCID: PMC11848041 DOI: 10.1002/alz.14599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2024] [Revised: 12/24/2024] [Accepted: 01/13/2025] [Indexed: 02/25/2025]
Abstract
INTRODUCTION Physical activity is associated with greater myelin content in older individuals with cerebral small vessel disease (CSVD), a condition marked by demyelination. However, potential mechanisms underlying this relationship remain understudied. METHODS We assessed cross-sectionally whether serum high-density lipoprotein (HDL), low-density lipoprotein, and triglycerides moderated the association between physical activity and in vivo myelin in older individuals with CSVD and mild cognitive impairment. RESULTS We included 81 highly educated, community-dwelling older individuals (mean age 74.57 years), 64% of whom were female. Regression models revealed that HDL levels significantly moderated the relationship between physical activity and myelin in the sagittal stratum, wherein higher physical activity levels were linked to greater myelin levels for those with average or high HDL (standardized B [95% CI] = 0.289 [0.087 to 0.491], p = 0.006). DISCUSSION Physical activity may promote myelin health partly through HDL. Data from longitudinal studies are needed to confirm our findings. HIGHLIGHTS Myelin loss is common in individuals with cerebral small vessel disease (CSVD). Physical activity was positively associated with myelin in older adults with CSVD. High-density lipoproteins (HDL) levels were also positively related to myelin. Physical activity effects on myelin were moderated by HDL levels.
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Affiliation(s)
- Nárlon C. Boa Sorte Silva
- Department of HealthKinesiology, and Applied PhysiologyFaculty of Arts and ScienceConcordia UniversityMontréalQuébecCanada
| | - Guilherme M. Balbim
- Department of Physical TherapyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Ryan G. Stein
- Department of Physical TherapyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Yi Gu
- Department of Physical TherapyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Roger C. Tam
- School of Biomedical EngineeringFaculty of Applied Science and Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Elizabeth Dao
- Department of Physical TherapyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Walid Alkeridy
- Department of MedicineKing Saud UniversityCollege of MedicineRiyadhSaudi Arabia
| | - Kevin Lam
- Department of MedicineDivision of NeurologyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Arthur F. Kramer
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
| | - Teresa Liu‐Ambrose
- Department of Physical TherapyFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
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Sanabria-Diaz G, Cagol A, Lu PJ, Barakovic M, Ocampo-Pineda M, Chen X, Weigel M, Ruberte E, Siebenborn NDOS, Galbusera R, Schädelin S, Benkert P, Kuhle J, Kappos L, Melie-Garcia L, Granziera C. Advanced MRI Measures of Myelin and Axon Volume Identify Repair in Multiple Sclerosis. Ann Neurol 2024. [PMID: 39390658 DOI: 10.1002/ana.27102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 08/10/2024] [Accepted: 09/04/2024] [Indexed: 10/12/2024]
Abstract
OBJECTIVE Pathological studies suggest that multiple sclerosis (MS) lesions endure multiple waves of damage and repair; however, the dynamics and characteristics of these processes are poorly understood in patients living with MS. METHODS We studied 128 MS patients (75 relapsing-remitting, 53 progressive) and 72 healthy controls who underwent advanced magnetic resonance imaging and clinical examination at baseline and 2 years later. Magnetization transfer saturation and multi-shell diffusion imaging were used to quantify longitudinal changes in myelin and axon volumes within MS lesions. Lesions were grouped into 4 classes (repair, damage, mixed repair damage, and stable). The frequency of each class was correlated to clinical measures, demographic characteristics, and levels of serum neurofilament light chain (sNfL). RESULTS Stable lesions were the most frequent (n = 2,276; 44%), followed by lesions with patterns of "repair" (n = 1,352; 26.2%) and damage (n = 1,214; 23.5%). The frequency of "repair" lesion was negatively associated with disability (β = -0.04; p < 0.001) and sNfL (β = -0.16; p < 0.001) at follow-up. The frequency of the "damage" class was higher in progressive than relapsing-remitting patients (p < 0.05) and was related to disability (baseline: β = -0.078; follow-up: β = -0.076; p < 0.001) and age (baseline: β = -0.078; p < 0.001). Stable lesions were more frequent in relapsing-remitting than in progressive patients (p < 0.05), and in younger patients versus older (β = -0.07; p < 0.001) at baseline. Further, "mixed" lesions were most frequent in older patients (β = 0.004; p < 0.001) at baseline. INTERPRETATION These findings show that repair and damage processes within MS lesions occur across the entire disease spectrum and that their frequency correlates with patients disability, age, disease duration, and extent of neuroaxonal damage. ANN NEUROL 2024.
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Affiliation(s)
- Gretel Sanabria-Diaz
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Cagol
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Health Sciences, University of Genova, Genoa, Italy
| | - Po-Jui Lu
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Mario Ocampo-Pineda
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Xinjie Chen
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Esther Ruberte
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC), Basel, Switzerland
| | - Nina de Oliveira S Siebenborn
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC), Basel, Switzerland
| | - Riccardo Galbusera
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schädelin
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Pascal Benkert
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Multiple Sclerosis Centre, Department of Neurology, Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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Singh V, Zheng Y, Ontaneda D, Mahajan KR, Holloman J, Fox RJ, Nakamura K, Trapp BD. Disability independent of cerebral white matter demyelination in progressive multiple sclerosis. Acta Neuropathol 2024; 148:34. [PMID: 39217272 PMCID: PMC11365858 DOI: 10.1007/s00401-024-02796-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 08/20/2024] [Accepted: 08/20/2024] [Indexed: 09/04/2024]
Abstract
The pathogenic mechanisms contributing to neurological disability in progressive multiple sclerosis (PMS) are poorly understood. Cortical neuronal loss independent of cerebral white matter (WM) demyelination in myelocortical MS (MCMS) and identification of MS patients with widespread cortical atrophy and disability progression independent of relapse activity (PIRA) support pathogenic mechanisms other than cerebral WM demyelination. The three-dimensional distribution and underlying pathology of myelinated T2 lesions were investigated in postmortem MCMS brains. Postmortem brain slices from previously characterized MCMS (10 cases) and typical MS (TMS) cases (12 cases) were co-registered with in situ postmortem T2 hyperintensities and T1 hypointensities. T1 intensity thresholds were used to establish a classifier that differentiates MCMS from TMS. The classifier was validated in 36 uncharacterized postmortem brains and applied to baseline MRIs from 255 living PMS participants enrolled in SPRINT-MS. Myelinated T2 hyperintensities in postmortem MCMS brains have a contiguous periventricular distribution that expands at the occipital poles of the lateral ventricles where a surface-in gradient of myelinated axonal degeneration was observed. The MRI classifier distinguished pathologically confirmed postmortem MCMS and TMS cases with an accuracy of 94%. For SPRINT-MS patients, the MRI classifier identified 78% as TMS, 10% as MCMS, and 12% with a paucity of cerebral T1 and T2 intensities. In SPRINT-MS, expanded disability status scale and brain atrophy measures were similar in MCMS and TMS cohorts. A paucity of cerebral WM demyelination in 22% of living PMS patients raises questions regarding a primary role for cerebral WM demyelination in disability progression in all MS patients and has implications for clinical management of MS patients and clinical trial outcomes in PMS. Periventricular myelinated fiber degeneration provides additional support for surface-in gradients of neurodegeneration in MS.
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Affiliation(s)
- Vikas Singh
- Department of Neurosciences, NC30, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Yufan Zheng
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Daniel Ontaneda
- Mellen Center for Treatment and Research in MS, Cleveland Clinic, Cleveland, OH, USA
| | - Kedar R Mahajan
- Department of Neurosciences, NC30, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
- Mellen Center for Treatment and Research in MS, Cleveland Clinic, Cleveland, OH, USA
| | - Jameson Holloman
- Department of Neurosciences, NC30, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
- Mellen Center for Treatment and Research in MS, Cleveland Clinic, Cleveland, OH, USA
| | - Robert J Fox
- Mellen Center for Treatment and Research in MS, Cleveland Clinic, Cleveland, OH, USA
| | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Bruce D Trapp
- Department of Neurosciences, NC30, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA.
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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [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] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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8
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Zuroff LR, Green AJ. The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair. J Neuroophthalmol 2024; 44:143-156. [PMID: 38654413 DOI: 10.1097/wno.0000000000002149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration. METHODS A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted. RESULTS There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials. CONCLUSIONS We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures.
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Affiliation(s)
- Leah R Zuroff
- Department of Neurology (LZ), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Neurology (AJG), University of California San Francisco, San Francisco, California
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9
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Frigon EM, Gérin-Lajoie A, Dadar M, Boire D, Maranzano J. Comparison of histological procedures and antigenicity of human post-mortem brains fixed with solutions used in gross anatomy laboratories. Front Neuroanat 2024; 18:1372953. [PMID: 38659652 PMCID: PMC11039794 DOI: 10.3389/fnana.2024.1372953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 04/01/2024] [Indexed: 04/26/2024] Open
Abstract
Background Brain banks provide small tissue samples to researchers, while gross anatomy laboratories could provide larger samples, including complete brains to neuroscientists. However, they are preserved with solutions appropriate for gross-dissection, different from the classic neutral-buffered formalin (NBF) used in brain banks. Our previous work in mice showed that two gross-anatomy laboratory solutions, a saturated-salt-solution (SSS) and an alcohol-formaldehyde-solution (AFS), preserve antigenicity of the main cellular markers (neurons, astrocytes, microglia, and myelin). Our goal is now to compare the quality of histology and antigenicity preservation of human brains fixed with NBF by immersion (practice of brain banks) vs. those fixed with a SSS and an AFS by whole body perfusion, practice of gross-anatomy laboratories. Methods We used a convenience sample of 42 brains (31 males, 11 females; 25-90 years old) fixed with NBF (N = 12), SSS (N = 13), and AFS (N = 17). One cm3 tissue blocks were cut, cryoprotected, frozen and sliced into 40 μm sections. The four cell populations were labeled using immunohistochemistry (Neurons = neuronal-nuclei = NeuN, astrocytes = glial-fibrillary-acidic-protein = GFAP, microglia = ionized-calcium-binding-adaptor-molecule1 = Iba1 and oligodendrocytes = myelin-proteolipid-protein = PLP). We qualitatively assessed antigenicity and cell distribution, and compared the ease of manipulation of the sections, the microscopic tissue quality, and the quality of common histochemical stains (e.g., Cresyl violet, Luxol fast blue, etc.) across solutions. Results Sections of SSS-fixed brains were more difficult to manipulate and showed poorer tissue quality than those from brains fixed with the other solutions. The four antigens were preserved, and cell labeling was more often homogeneous in AFS-fixed specimens. NeuN and GFAP were not always present in NBF and SSS samples. Some antigens were heterogeneously distributed in some specimens, independently of the fixative, but an antigen retrieval protocol successfully recovered them. Finally, the histochemical stains were of sufficient quality regardless of the fixative, although neurons were more often paler in SSS-fixed specimens. Conclusion Antigenicity was preserved in human brains fixed with solutions used in human gross-anatomy (albeit the poorer quality of SSS-fixed specimens). For some specific variables, histology quality was superior in AFS-fixed brains. Furthermore, we show the feasibility of frequently used histochemical stains. These results are promising for neuroscientists interested in using brain specimens from anatomy laboratories.
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Affiliation(s)
- Eve-Marie Frigon
- Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, QC, Canada
| | - Amy Gérin-Lajoie
- Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, QC, Canada
| | - Mahsa Dadar
- Department of Psychiatry, Douglas Research Center, McGill University, Montreal, QC, Canada
| | - Denis Boire
- Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, QC, Canada
| | - Josefina Maranzano
- Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, QC, Canada
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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10
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Schäper J, Bieri O. Myelin water imaging at 0.55 T using a multigradient-echo sequence. Magn Reson Med 2024; 91:1043-1056. [PMID: 38010053 DOI: 10.1002/mrm.29949] [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: 09/07/2023] [Revised: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T. METHODS Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T. RESULTS The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate. CONCLUSION This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.
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Affiliation(s)
- Jessica Schäper
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
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11
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Kreiter D, Postma AA, Hupperts R, Gerlach O. Hallmarks of spinal cord pathology in multiple sclerosis. J Neurol Sci 2024; 456:122846. [PMID: 38142540 DOI: 10.1016/j.jns.2023.122846] [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: 10/19/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement.
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Affiliation(s)
- Daniel Kreiter
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Raymond Hupperts
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Oliver Gerlach
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
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12
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Laureano B, Irzan H, O'Reilly H, Ourselin S, Marlow N, Melbourne A. Myelination of preterm brain networks at adolescence. Magn Reson Imaging 2024; 105:114-124. [PMID: 37984490 DOI: 10.1016/j.mri.2023.11.001] [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: 06/09/2022] [Revised: 10/31/2023] [Accepted: 11/04/2023] [Indexed: 11/22/2023]
Abstract
Prematurity and preterm stressors severely affect the development of infants born before 37 weeks of gestation, with increasing effects seen at earlier gestations. Although preterm mortality rates have declined due to the advances in neonatal care, disability rates, especially in middle-income settings, continue to grow. With the advances in MR imaging technology, there has been a focus on safely imaging the preterm brain to better understand its development and discover the brain regions and networks affected by prematurity. Such studies aim to support interventions and improve the neurodevelopment of preterm infants and deliver accurate prognoses. Few studies, however, have focused on the fully developed brain of preterm born infants, especially in extremely preterm subjects. To assess the long-term effect of prematurity on the adult brain, myelin related biomarkers such as myelin water fraction and g-ratio are measured for a cohort of 19-year-old extremely preterm born subjects. Using multi-modal imaging techniques that combine T2 relaxometry and neurite density information, the results show that specific brain regions associated with white matter injuries due to preterm birth, such as the posterior limb of the internal capsule and corpus callosum, are still less myelinated in adulthood. Furthermore, a weak positive relationship between myelin water fraction values and Full-Scale Intelligence Quotient (FSIQ) scores was found in multiple brain regions previously defined as less myelinated in the Extremely Preterm (EPT) cohort. These findings might suggest altered connectivity in the adult preterm brain and explain differences in cognitive outcomes.
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Affiliation(s)
- Beatriz Laureano
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK.
| | - Hassna Irzan
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Helen O'Reilly
- Children's Disability Network Team, St. Michael's House, Dublin, Ireland
| | - Sebastian Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Neil Marlow
- Institute for Women's Health, University College London, London, UK
| | - Andrew Melbourne
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Dept. of Medical Physics and Biomedical Engineering, University College London, London, UK
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13
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Stellingwerff MD, Al-Saady ML, Chan KS, Dvorak A, Marques JP, Kolind S, Roosendaal SD, Wolf NI, Barkhof F, van der Knaap MS, Pouwels PJW. Applicability of multiple quantitative magnetic resonance methods in genetic brain white matter disorders. J Neuroimaging 2024; 34:61-77. [PMID: 37925602 DOI: 10.1111/jon.13167] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/29/2023] [Accepted: 10/20/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND AND PURPOSE Magnetic resonance imaging (MRI) measures of tissue microstructure are important for monitoring brain white matter (WM) disorders like leukodystrophies and multiple sclerosis. They should be sensitive to underlying pathological changes. Three whole-brain isotropic quantitative methods were applied and compared within a cohort of controls and leukodystrophy patients: two novel myelin water imaging (MWI) techniques (multi-compartment relaxometry diffusion-informed MWI: MCR-DIMWI, and multi-echo T2 relaxation imaging with compressed sensing: METRICS) and neurite orientation dispersion and density imaging (NODDI). METHODS For 9 patients with different leukodystrophies (age range 0.4-62.4 years) and 15 control subjects (2.3-61.3 years), T1-weighted MRI, fluid-attenuated inversion recovery, multi-echo gradient echo with variable flip angles, METRICS, and multi-shell diffusion-weighted imaging were acquired on 3 Tesla. MCR-DIMWI, METRICS, NODDI, and quality control measures were extracted to evaluate differences between patients and controls in WM and deep gray matter (GM) regions of interest (ROIs). Pearson correlations, effect size calculations, and multi-level analyses were performed. RESULTS MCR-DIMWI and METRICS-derived myelin water fractions (MWFs) were lower and relaxation times were higher in patients than in controls. Effect sizes of MWF values and relaxation times were large for both techniques. Differences between patients and controls were more pronounced in WM ROIs than in deep GM. MCR-DIMWI-MWFs were more homogeneous within ROIs and more bilaterally symmetrical than METRICS-MWFs. The neurite density index was more sensitive in detecting differences between patients and controls than fractional anisotropy. Most measures obtained from MCR-DIMWI, METRICS, NODDI, and diffusion tensor imaging correlated strongly with each other. CONCLUSION This proof-of-concept study shows that MCR-DIMWI, METRICS, and NODDI are sensitive techniques to detect changes in tissue microstructure in WM disorders.
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Affiliation(s)
- Menno D Stellingwerff
- Department of Child Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Cellular & Molecular Mechanisms, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, Netherlands
| | - Murtadha L Al-Saady
- Department of Child Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Cellular & Molecular Mechanisms, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, Netherlands
| | - Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Adam Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Shannon Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Stefan D Roosendaal
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Nicole I Wolf
- Department of Child Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Cellular & Molecular Mechanisms, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Amsterdam, Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Marjo S van der Knaap
- Department of Child Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Cellular & Molecular Mechanisms, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, and Amsterdam Neuroscience, Amsterdam, Netherlands
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14
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Khormi I, Al-Iedani O, Alshehri A, Ramadan S, Lechner-Scott J. MR myelin imaging in multiple sclerosis: A scoping review. J Neurol Sci 2023; 455:122807. [PMID: 38035651 DOI: 10.1016/j.jns.2023.122807] [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: 07/24/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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15
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Khan AF, Haynes G, Mohammadi E, Muhammad F, Hameed S, Smith ZA. Utility of MRI in Quantifying Tissue Injury in Cervical Spondylotic Myelopathy. J Clin Med 2023; 12:jcm12093337. [PMID: 37176777 PMCID: PMC10179707 DOI: 10.3390/jcm12093337] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/28/2023] [Accepted: 05/05/2023] [Indexed: 05/15/2023] Open
Abstract
Cervical spondylotic myelopathy (CSM) is a progressive disease that worsens over time if untreated. However, the rate of progression can vary among individuals and may be influenced by various factors, such as the age of the patients, underlying conditions, and the severity and location of the spinal cord compression. Early diagnosis and prompt treatment can help slow the progression of CSM and improve symptoms. There has been an increased use of magnetic resonance imaging (MRI) methods in diagnosing and managing CSM. MRI methods provide detailed images and quantitative structural and functional data of the cervical spinal cord and brain, allowing for an accurate evaluation of the extent and location of tissue injury. This review aims to provide an understanding of the use of MRI methods in interrogating functional and structural changes in the central nervous system in CSM. Further, we identified several challenges hindering the clinical utility of these neuroimaging methods.
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Affiliation(s)
- Ali Fahim Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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16
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Johnson P, Vavasour IM, Stojkova BJ, Abel S, Lee LE, Laule C, Tam R, Li DKB, Ackermans N, Schabas AJ, Chan J, Cross H, Sayao AL, Devonshire V, Carruthers R, Traboulsee A, Kolind SH. Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis. J Neuroimaging 2023; 33:227-234. [PMID: 36443960 DOI: 10.1111/jon.13069] [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: 06/16/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND PURPOSE Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability. METHODS Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed. RESULTS NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC. CONCLUSIONS Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.
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Affiliation(s)
- Poljanka Johnson
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Shawna Abel
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nathalie Ackermans
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Alice J Schabas
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Jillian Chan
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Helen Cross
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Ana-Luiza Sayao
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Virginia Devonshire
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Carruthers
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
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17
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Boa Sorte Silva NC, Dao E, Liang Hsu C, Tam RC, Lam K, Alkeridy W, Laule C, Vavasour IM, Stein RG, Liu-Ambrose T. Myelin and Physical Activity in Older Adults With Cerebral Small Vessel Disease and Mild Cognitive Impairment. J Gerontol A Biol Sci Med Sci 2023; 78:545-553. [PMID: 35876839 DOI: 10.1093/gerona/glac149] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Myelin loss is a feature of cerebral small vessel disease (cSVD). Although physical activity levels may exert protective effects over cSVD pathology, its specific relationship with myelin content in people living with the cSVD is unknown. Thus, we investigated whether physical activity levels are associated with myelin in community-dwelling older adults with cSVD and mild cognitive impairment. METHODS Cross-sectional data from 102 individuals with cSVD and mild cognitive impairment were analyzed (mean age [SD] = 74.7 years [5.5], 63.7% female). Myelin was measured using a magnetic resonance gradient and spin echo sequence. Physical activity was estimated using the Physical Activity Scale for the Elderly. Hierarchical regression models adjusting for total intracranial volume, age, sex, body mass index, and education were conducted to determine the associations between myelin content and physical activity. Significant models were further adjusted for white matter hyperintensity volume. RESULTS In adjusted models, greater physical activity was linked to higher myelin content in the whole-brain white matter (R2change = .04, p = .048). Greater physical activity was also associated with myelin content in the sagittal stratum (R2change = .08, p = .004), anterior corona radiata (R2change = .04, p = .049), and genu of the corpus callosum (R2change = .05, p = .018). Adjusting for white matter hyperintensity volume did not change any of these associations. CONCLUSIONS Physical activity may be a strategy to maintain myelin in older adults with cSVD and mild cognitive impairment. Future randomized controlled trials of exercise are needed to determine whether exercise increases myelin content.
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Affiliation(s)
- Nárlon C Boa Sorte Silva
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Elizabeth Dao
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Chun Liang Hsu
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts, USA
| | - Roger C Tam
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kevin Lam
- Department of Medicine, Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Walid Alkeridy
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, King Saud University, College of Medicine, Riyadh, Saudi Arabia.,Department of Medicine, Division of Geriatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ryan G Stein
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Teresa Liu-Ambrose
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
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Baadsvik EL, Weiger M, Froidevaux R, Faigle W, Ineichen BV, Pruessmann KP. Mapping the myelin bilayer with short-T 2 MRI: Methods validation and reference data for healthy human brain. Magn Reson Med 2023; 89:665-677. [PMID: 36253953 PMCID: PMC10091754 DOI: 10.1002/mrm.29481] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/24/2022] [Accepted: 09/20/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To explore the properties of short-T2 signals in human brain, investigate the impact of various experimental procedures on these properties and evaluate the performance of three-component analysis. METHODS Eight samples of non-pathological human brain tissue were subjected to different combinations of experimental procedures including D2 O exchange and frozen storage. Short-T2 imaging techniques were employed to acquire multi-TE (33-2067 μs) data, to which a three-component complex model was fitted in two steps to recover the properties of the underlying signal components and produce amplitude maps of each component. For validation of the component amplitude maps, the samples underwent immunohistochemical myelin staining. RESULTS The signal component representing the myelin bilayer exhibited super-exponential decay with T2,min of 5.48 μs and a chemical shift of 1.07 ppm, and its amplitude could be successfully mapped in both white and gray matter in all samples. These myelin maps corresponded well to myelin-stained tissue sections. Gray matter signals exhibited somewhat different components than white matter signals, but both tissue types were well represented by the signal model. Frozen tissue storage did not alter the signal components but influenced component amplitudes. D2 O exchange was necessary to characterize the non-aqueous signal components, but component amplitude mapping could be reliably performed also in the presence of H2 O signals. CONCLUSIONS The myelin mapping approach explored here produced reasonable and stable results for all samples. The extensive tissue and methodological investigations performed in this work form a basis for signal interpretation in future studies both ex vivo and in vivo.
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Affiliation(s)
- Emily Louise Baadsvik
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Romain Froidevaux
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Abstract
Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. This review summarizes recent developments in advanced neuroimaging of cSVD with a focus on clinical and research applications. In the first section, we highlight how advanced structural imaging techniques, including diffusion magnetic resonance imaging (MRI), enable improved detection of tissue damage, including characterization of tissue appearing normal on conventional MRI. These techniques enable progression to be monitored and may be useful as surrogate endpoint in clinical trials. Quantitative MRI, including iron and myelin imaging, provides insights into tissue composition on the molecular level. In the second section, we cover how advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, which could be targeted in mechanistic research and early-stage intervention trials. Such techniques include the use of dynamic contrast enhanced MRI to measure blood-brain barrier permeability, and MRI methods to assess cerebrovascular reactivity. In the third section, we discuss how the increased spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of perforating arteries, and flow velocity and pulsatility within them. The advanced MRI techniques we describe are providing novel pathophysiological insights in cSVD and allow improved quantification of disease burden and progression. They have application in clinical trials, both in assessing novel therapeutic mechanisms, and as a sensitive endpoint to assess efficacy of interventions on parenchymal tissue damage. We also discuss challenges of these advanced techniques and suggest future directions for research.
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and
Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University,
Utrecht, The Netherlands
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, UK
Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG)
and qbig, Department of Biomedical Engineering, University of Basel, Basel,
Switzerland,Marco Duering, Medical Image Analysis
Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of
Basel, Marktgasse 8, Basel, CH-4051, Switzerland.
; @MarcoDuering
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20
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Berg RC, Menegaux A, Amthor T, Gilbert G, Mora M, Schlaeger S, Pongratz V, Lauerer M, Sorg C, Doneva M, Vavasour I, Mühlau M, Preibisch C. Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains. Neuroimage 2022; 264:119750. [PMID: 36379421 PMCID: PMC9931395 DOI: 10.1016/j.neuroimage.2022.119750] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/11/2022] [Accepted: 11/11/2022] [Indexed: 11/15/2022] Open
Abstract
The myelin concentration and the degree of myelination of nerve fibers can provide valuable information on the integrity of human brain tissue. Magnetic resonance imaging (MRI) of myelin-sensitive parameters can help to non-invasively evaluate demyelinating diseases such as multiple sclerosis (MS). Several different myelin-sensitive MRI methods have been proposed to determine measures of the degree of myelination, in particular the g-ratio. However, variability in underlying physical principles and different biological models influence measured myelin concentrations, and consequently g-ratio values. We therefore investigated similarities and differences between five different myelin-sensitive MRI measures and their effects on g-ratio mapping in the brains of both MS patients and healthy volunteers. We compared two different estimates of the myelin water fraction (MWF) as well as the inhomogeneous magnetization transfer ratio (ihMTR), magnetization transfer saturation (MTsat), and macromolecular tissue volume (MTV) in 13 patients with MS and 14 healthy controls. In combination with diffusion-weighted imaging, we derived g-ratio parameter maps for each of the five different myelin measures. The g-ratio values calculated from different myelin measures varied strongly, especially in MS lesions. While, compared to normal-appearing white matter, MTsat and one estimate of the MWF resulted in higher g-ratio values within lesions, ihMTR, MTV, and the second MWF estimate resulted in lower lesion g-ratio values. As myelin-sensitive measures provide rough estimates of myelin content rather than absolute myelin concentrations, resulting g-ratio values strongly depend on the utilized myelin measure and model used for g-ratio mapping. When comparing g-ratio values, it is, thus, important to utilize the same MRI methods and models or to consider methodological differences. Particular caution is necessary in pathological tissue such as MS lesions.
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Affiliation(s)
- Ronja C. Berg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Corresponding author at: Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaninger Str. 22, 81675, München, Germany. (R.C. Berg)
| | - Aurore Menegaux
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | | | | | - Maria Mora
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Sarah Schlaeger
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Viola Pongratz
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Markus Lauerer
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany,Technical University of Munich, School of Medicine, Department of Psychiatry, Munich, Germany
| | | | - Irene Vavasour
- University of British Columbia, Department of Radiology, Vancouver, BC, Canada
| | - Mark Mühlau
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
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21
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Pitt D, Lo CH, Gauthier SA, Hickman RA, Longbrake E, Airas LM, Mao-Draayer Y, Riley C, De Jager PL, Wesley S, Boster A, Topalli I, Bagnato F, Mansoor M, Stuve O, Kister I, Pelletier D, Stathopoulos P, Dutta R, Lincoln MR. Toward Precision Phenotyping of Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/6/e200025. [PMID: 36041861 PMCID: PMC9427000 DOI: 10.1212/nxi.0000000000200025] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 02/07/2022] [Indexed: 11/15/2022]
Abstract
The classification of multiple sclerosis (MS) has been established by Lublin in 1996 and revised in 2013. The revision includes clinically isolated syndrome, relapsing-remitting, primary progressive and secondary progressive MS, and has added activity (i.e., formation of white matter lesions or clinical relapses) as a qualifier. This allows for the distinction between active and nonactive progression, which has been shown to be of clinical importance. We propose that a logical extension of this classification is the incorporation of additional key pathological processes, such as chronic perilesional inflammation, neuroaxonal degeneration, and remyelination. This will distinguish MS phenotypes that may present as clinically identical but are driven by different combinations of pathological processes. A more precise description of MS phenotypes will improve prognostication and personalized care as well as clinical trial design. Thus, our proposal provides an expanded framework for conceptualizing MS and for guiding development of biomarkers for monitoring activity along the main pathological axes in MS.
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Affiliation(s)
- David Pitt
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada.
| | - Chih Hung Lo
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Susan A Gauthier
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Richard A Hickman
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Erin Longbrake
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Laura M Airas
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Yang Mao-Draayer
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Claire Riley
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Philip Lawrence De Jager
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Sarah Wesley
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Aaron Boster
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Ilir Topalli
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Francesca Bagnato
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Mohammad Mansoor
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Olaf Stuve
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Ilya Kister
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Daniel Pelletier
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Panos Stathopoulos
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Ranjan Dutta
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
| | - Matthew R Lincoln
- From the Yale University (David Pitt, C.H.L., E.L., M.M., M.R.L.), New Haven; Nanyang Technological University (C.H.L.), Singapore; Weill Cornell Medicine (S.A.G.), New York; Memorial Sloan Kettering Cancer Center (R.A.H.), New York; University of Turku (L.M.A.), Finland; University of Michigan Medical School (Y.M.-D.), Ann Arbor; Columbia University Medical Center (C.R., P.L.D.J., S.W.), New York; The Boster Center for Multiple Sclerosis (A.B.), Columbus, OH; Cerneris Inc (I.T.), Wilmington, DE; Vanderbilt University Medical Center (F.B.), Nashville, TN; University of Texas Southwestern Medical Center (O.S.), Dallas; NYU Langone Medical Center (I.K.), New York; University of Southern California (Daniel Pelletier), Los Angeles; National and Kapodistrian University of Athens Medical School (P.S.), Greece; Cleveland Clinic Lerner College of Medicine (R.D.), Case Western Reserve University, OH; and University of Toronto and St. Michael's Hospital (M.L.), ON, Canada
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22
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Combes AJE, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States.
| | - Margareta A Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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23
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Abstract
PURPOSE OF REVIEW Myelin water imaging (MWI) is generally regarded as the most rigorous approach for noninvasive, in-vivo measurement of myelin content, which has been histopathologically validated. As such, it has been increasingly applied to neurological diseases with white matter involvement, especially those affecting myelin. This review provides an overview of the most recent research applying MWI in neurological syndromes. RECENT FINDINGS Myelin water imaging has been applied in neurological syndromes including multiple sclerosis, Alzheimer's disease, Huntington's disease, traumatic brain injury, Parkinson's disease, cerebral small vessel disease, leukodystrophies and HIV. These syndromes generally showed alterations observable with MWI, with decreased myelin content tending to correlate with lower cognitive scores and worse clinical presentation. MWI has also been correlated with genetic variation in the APOE and PLP1 genes, demonstrating genetic factors related to myelin health. SUMMARY MWI can detect and quantify changes not observable with conventional imaging, thereby providing insight into the pathophysiology and disease mechanisms of a diverse range of neurological syndromes.
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24
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Piredda GF, Hilbert T, Ravano V, Canales-Rodríguez EJ, Pizzolato M, Meuli R, Thiran JP, Richiardi J, Kober T. Data-driven myelin water imaging based on T 1 and T 2 relaxometry. NMR IN BIOMEDICINE 2022; 35:e4668. [PMID: 34936147 DOI: 10.1002/nbm.4668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 11/16/2021] [Accepted: 11/30/2021] [Indexed: 06/14/2023]
Abstract
Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T1 and T2 relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T1 /T2 data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Marco Pizzolato
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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25
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Rahmanzadeh R, Galbusera R, Lu PJ, Bahn E, Weigel M, Barakovic M, Franz J, Nguyen TD, Spincemaille P, Schiavi S, Daducci A, La Rosa F, Absinta M, Sati P, Cuadra MB, Radue EW, Leppert D, Kuhle J, Kappos L, Brück W, Reich DS, Stadelmann C, Wang Y, Granziera C. A new advanced MRI biomarker for remyelinated lesions in Multiple Sclerosis. Ann Neurol 2022; 92:486-502. [PMID: 35713309 PMCID: PMC9527017 DOI: 10.1002/ana.26441] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/12/2022] [Accepted: 06/14/2022] [Indexed: 11/28/2022]
Abstract
Objectives Neuropathological studies have shown that multiple sclerosis (MS) lesions are heterogeneous in terms of myelin/axon damage and repair as well as iron content. However, it remains a challenge to identify specific chronic lesion types, especially remyelinated lesions, in vivo in patients with MS. Methods We performed 3 studies: (1) a cross‐sectional study in a prospective cohort of 115 patients with MS and 76 healthy controls, who underwent 3 T magnetic resonance imaging (MRI) for quantitative susceptibility mapping (QSM), myelin water fraction (MWF), and neurite density index (NDI) maps. White matter (WM) lesions in QSM were classified into 5 QSM lesion types (iso‐intense, hypo‐intense, hyperintense, lesions with hypo‐intense rims, and lesions with paramagnetic rim legions [PRLs]); (2) a longitudinal study of 40 patients with MS to study the evolution of lesions over 2 years; (3) a postmortem histopathology‐QSM validation study in 3 brains of patients with MS to assess the accuracy of QSM classification to identify neuropathological lesion types in 63 WM lesions. Results At baseline, hypo‐ and isointense lesions showed higher mean MWF and NDI values compared to other QSM lesion types (p < 0.0001). Further, at 2‐year follow‐up, hypo‐/iso‐intense lesions showed an increase in MWF. Postmortem analyses revealed that QSM highly accurately identifies (1) fully remyelinated areas as hypo‐/iso‐intense (sensitivity = 88.89% and specificity = 100%), (2) chronic inactive lesions as hyperintense (sensitivity = 71.43% and specificity = 92.00%), and (3) chronic active/smoldering lesions as PRLs (sensitivity = 92.86% and specificity = 86.36%). Interpretation These results provide the first evidence that it is possible to distinguish chronic MS lesions in a clinical setting, hereby supporting with new biomarkers to develop and assess remyelinating treatments. ANN NEUROL 2022;92:486–502
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Affiliation(s)
- Reza Rahmanzadeh
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Erik Bahn
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Matthias Weigel
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jonas Franz
- Institute of Neuropathology, University Medical Center, Göttingen, Germany.,Max Planck Institute for Experimental Medicine, Göttingen, Germany.,Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - David Leppert
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Wolfgang Brück
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA
| | | | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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26
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Wilczynski E, Sasson E, Eliav U, Navon G, Nevo U. An in vivo implementation of the MEX MRI for myelin fraction of mice brain. MAGMA (NEW YORK, N.Y.) 2022; 35:267-276. [PMID: 34357453 DOI: 10.1007/s10334-021-00950-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/11/2021] [Accepted: 07/26/2021] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Magnetization EXchange (MEX) sequence measures a signal linearly dependent on the myelin proton fraction by selective suppression of water magnetization and a recovery period. Varying the recovery period enables extraction of the percentile fraction of myelin bound protons. We aim to demonstrate the MEX sequence sensitivity to the fraction of protons associated with myelin in mice brain, in vivo. METHODS The cuprizone mouse model was used to manipulate the myelin content. Mice fed cuprizone (n = 15) and normal chow (n = 8) were imaged in vivo using MEX sequence. MR images were segmented into corpus callosum and internal capsule (white matter) and cortical gray matter, and fitted to the recovery equation. Results were analyzed with correlation to MWF and histopathology. RESULTS The extracted parameters show significant differences in the corpus callosum between the cuprizone and control groups. The cuprizone group exhibited reduced myelin fraction 26.5% (P < 0.01). The gray matter values were less affected, with 13.5% reduction (P < 0.05); no changes were detected in the internal capsule. Results were validated by MWF scans and good correlation to the histology analysis (R2 = 0.685). CONCLUSION The results of this first in vivo implementation of the MEX sequence provide a quantitative measure of demyelination in brain white matter.
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Affiliation(s)
- Ella Wilczynski
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Efrat Sasson
- School of Chemistry, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Uzi Eliav
- School of Chemistry, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Gil Navon
- School of Chemistry, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Uri Nevo
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel. .,Sagol School of Neuroscience, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
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27
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Zhang HW, Zhang YQ, Liu XL, Mo YQ, Lei Y, Lin F, Feng YN. MR imaging features of Lhermitte-Duclos disease: Case reports and literature review. Medicine (Baltimore) 2022; 101:e28667. [PMID: 35089210 PMCID: PMC8797601 DOI: 10.1097/md.0000000000028667] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/31/2021] [Accepted: 01/05/2022] [Indexed: 01/05/2023] Open
Abstract
RATIONALE Lhermitte-Duclos disease (LDD) is a rare tumor of the nervous system with a typical "tiger striped'" sign, but its features on functional magnetic resonance imaging (fMRI) are still inconclusive. PATIENT CONCERNS To explore the characteristics of LDDs using fMRI. DIAGNOSES We report 3 cases of pathologically confirmed LDDs. INTERVENTIONS Three patients underwent brain tumor surgery. OUTCOMES All the patients had a good prognosis. LESSONS Magnetic resonance spectroscopy and susceptibility-weighted imaging combined with conventional MRI can be used to better diagnose LDDs. Perfusion-weighted imaging is not specific for distinguishing cerebellar tumors. The combined application of fMRI and conventional MRI can improve the accuracy of LDD diagnoses.
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Affiliation(s)
- Han-wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yuan-qing Zhang
- Special Clinic, Shenzhen Children's Hospital, Shenzhen, YiTian Road, China
| | - Xiao-lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yong-qian Mo
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yi Lei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yu-ning Feng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
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28
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Yik JT, Becquart P, Gill J, Petkau J, Traboulsee A, Carruthers R, Kolind SH, Devonshire V, Sayao AL, Schabas A, Tam R, Moore GRW, Li DKB, Stukas S, Wellington C, Quandt JA, Vavasour IM, Laule C. Serum neurofilament light chain correlates with myelin and axonal magnetic resonance imaging markers in multiple sclerosis. Mult Scler Relat Disord 2022; 57:103366. [PMID: 35158472 DOI: 10.1016/j.msard.2021.103366] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/08/2021] [Accepted: 11/01/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Neurofilaments are cytoskeletal proteins that are detectable in the blood after neuroaxonal injury. Multiple sclerosis (MS) disease progression, greater lesion volume, and brain atrophy are associated with higher levels of serum neurofilament light chain (NfL), but few studies have examined the relationship between NfL and advanced magnetic resonance imaging (MRI) measures related to myelin and axons. We assessed the relationship between serum NfL and brain MRI measures in a diverse group of MS participants. METHODS AND MATERIALS 103 participants (20 clinically isolated syndrome, 33 relapsing-remitting, 30 secondary progressive, 20 primary progressive) underwent 3T MRI to obtain myelin water fraction (MWF), geometric mean T2 (GMT2), water content, T1; high angular resolution diffusion imaging (HARDI)-derived axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA); diffusion basis spectrum imaging (DBSI)-derived AD, RD, FA; restricted, hindered, water and fiber fractions; and volume measurements of normalized brain, lesion, thalamic, deep gray matter (GM), and cortical thickness. Multiple linear regressions assessed the strength of association between serum NfL (dependent variable) and each MRI measure in whole brain (WB), normal appearing white matter (NAWM) and T2 lesions (independent variables), while controlling for age, expanded disability status scale, and disease duration. RESULTS Serum NfL levels were significantly associated with metrics of axonal damage (FA: R2WB-HARDI = 0.29, R2NAWM-HARDI = 0.31, R2NAWM-DBSI = 0.30, R2Lesion-DBSI = 0.31; AD: R2WB-HARDI=0.31), myelin damage (MWF: R2WB = 0.29, R2NAWM = 0.30, RD: R2WB-HARDI = 0.32, R2NAWM-HARDI = 0.34, R2Lesion-DBSI = 0.30), edema and inflammation (T1: R2Lesion = 0.32; GMT2: R2WB = 0.31, R2Lesion = 0.31), and cellularity (restricted fraction R2WB = 0.30, R2NAWM = 0.32) across the entire MS cohort. Higher serum NfL levels were associated with significantly higher T2 lesion volume (R2 = 0.35), lower brain structure volumes (thalamus R2 = 0.31; deep GM R2 = 0.33; normalized brain R2 = 0.31), and smaller cortical thickness R2 = 0.31). CONCLUSION The association between NfL and myelin MRI markers suggest that elevated serum NfL is a useful biomarker that reflects not only acute axonal damage, but also damage to myelin and inflammation, likely due to the known synergistic myelin-axon coupling relationship.
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Affiliation(s)
- Jackie T Yik
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Pierre Becquart
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Jasmine Gill
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - John Petkau
- Department of Statistics, University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Robert Carruthers
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada; Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Virginia Devonshire
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ana-Luiza Sayao
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Alice Schabas
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - G R Wayne Moore
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - David K B Li
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Sophie Stukas
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Cheryl Wellington
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Jacqueline A Quandt
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Irene M Vavasour
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada.
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Hannoun S, Kocevar G, Codjia P, Barile B, Cotton F, Durand-Dubief F, Sappey-Marinier D. T1/T2 ratio: A quantitative sensitive marker of brain tissue integrity in multiple sclerosis. J Neuroimaging 2021; 32:328-336. [PMID: 34752685 DOI: 10.1111/jon.12943] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/30/2021] [Accepted: 10/14/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND AND PURPOSE The aim of this study is to determine whether cerebral white matter (WM) microstructural damage, defined by decreased fractional anisotropy (FA) and increased axial (AD) and radial (RD) diffusivities, could be detected as accurately by measuring the T1/T2 ratio, in relapsing-remitting multiple sclerosis (RRMS) patients compared to healthy control (HC) subjects. METHODS Twenty-eight RRMS patients and 24 HC subjects were included in this study. Region-based analysis based on the ICBM-81 diffusion tensor imaging (DTI) atlas WM labels was performed to compare T1/T2 ratio to DTI values in normal-appearing WM (NAWM) regions of interest. Lesions segmentation was also performed and compared to the HC global WM. RESULTS A significant 19.65% decrease of T1/T2 ratio values was observed in NAWM regions of RRMS patients compared to HC. A significant 6.30% decrease of FA, as well as significant 4.76% and 10.27% increases of AD and RD, respectively, were observed in RRMS compared to the HC group in various NAWM regions. Compared to the global WM HC mask, lesions have significantly decreased T1/T2 ratio and FA and increased AD and RD (p < . 001). CONCLUSIONS Results showed significant differences between RRMS and HC in both DTI and T1/T2 ratio measurements. T1/T2 ratio even demonstrated extensive WM abnormalities when compared to DTI, thereby highlighting the ratio's sensitivity to subtle differences in cerebral WM structural integrity using only conventional MRI sequences.
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Affiliation(s)
- Salem Hannoun
- Medical Imaging Sciences Program, Division of Health Professions, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Gabriel Kocevar
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Seenovate, Datascience pole, Lyon, France
| | - Pekes Codjia
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Berardino Barile
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France
| | - Francois Cotton
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Francoise Durand-Dubief
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Neurologie A, Hôpital Neurologique Pierre Wertheimer, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron, France
| | - Dominique Sappey-Marinier
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Département IRM, CERMEP-Imagerie du Vivant, Université de Lyon, Bron, France
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30
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Assessing the differential sensitivities of wave-CAIPI ViSTa myelin water fraction and magnetization transfer saturation for efficiently quantifying tissue damage in MS. Mult Scler Relat Disord 2021; 56:103309. [PMID: 34688179 DOI: 10.1016/j.msard.2021.103309] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/21/2021] [Accepted: 10/02/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Wave-CAIPI Visualization of Short Transverse relaxation time component (ViSTa) is a recently developed, short-T1-sensitized MRI method for fast quantification of myelin water fraction (MWF) in the human brain. It represents a promising technique for the evaluation of subtle, early signals of demyelination in the cerebral white matter of multiple sclerosis (MS) patients. Currently however, few studies exist that robustly assess the utility of ViSTa MWF measures of myelin compared to more conventional MRI measures of myelin in the brain of MS patients. Moreover, there are no previous studies evaluating the sensitivity of ViSTa MWF for the non-invasive detection of subtle tissue damage in both normal-appearing white matter (NAWM) and white matter lesions of MS patients. As a result, a central purpose of this study was to systematically evaluate the relationship between myelin sensitivity of T1-based ViSTa MWF mapping and a more generally recognized metric, Magnetization Transfer Saturation (MTsat), in healthy control and MS brain white matter. METHODS ViSTa MWF and MTsat values were evaluated in automatically-classified normal appearing white matter (NAWM), white matter (WM) lesion tissue, cortical gray matter, and deep gray matter of 29 MS patients and 10 healthy controls using 3T MRI. MWF and MT sat were also assessed in a tract-specific manner using the Johns Hopkins University WM atlas. MRI-derived measures of cerebral myelin content were uniquely compared by employing non-normal distribution-specific measures of median, interquartile range and skewness. Separate analyses of variance were applied to test tissue-specific differences in MTsat and ViSTa MWF distribution metrics. Non-parametric tests were utilized when appropriate. All tests were corrected for multiple comparisons using the False Discovery Rate method at the level, α=0.05. RESULTS Differences in whole NAWM MS tissue damage were detected with a higher effect size when using ViSTa MWF (q = 0.0008; ƞ2 = 0.34) compared to MTsat (q = 0.02; ƞ2= 0.24). We also observed that, as a possible measure of WM pathology, ViSTa-derived NAWM MWF voxel distributions of MS subjects were consistently skewed towards lower MWF values, while MTsat voxel distributions showed reduced skewness values. We further identified tract-specific reductions in mean ViSTa MWF of MS patients compared to controls that were not observed with MTsat. However, MTsat (q = 1.4 × 10-21; ƞ2 = 0.88) displayed higher effect sizes when differentiating NAWM and MS lesion tissue. Using regression analysis at the group level, we identified a linear relationship between MTsat and ViSTa MWF in NAWM (R2 = 0.46; p = 7.8 × 10-4) lesions (R2 = 0.30; p = 0.004), and with all tissue types combined (R2 = 0.71; p = 8.4 × 10-45). The linear relationship was also observed in most of the WM tracts we investigated. ViSTa MWF in NAWM of MS patients correlated with both disease duration (p = 0.02; R2 = 0.27) and WM lesion volume (p = 0.002; R2 = 0.34). CONCLUSION Because ViSTa MWF and MTsat metrics exhibit differential sensitivities to tissue damage in MS white matter, they can be collected in combination to provide an efficient, comprehensive measure of myelin water and macromolecular pool proton signals. These complementary measures may offer a more sensitive, non-invasive biopsy of early precursor signals in NAWM that occur prior to lesion formation. They may also aid in monitoring the efficacy of remyelination therapies.
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31
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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Vavasour IM, Sun P, Graf C, Yik JT, Kolind SH, Li DK, Tam R, Sayao AL, Schabas A, Devonshire V, Carruthers R, Traboulsee A, Moore GW, Song SK, Laule C. Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging. Mult Scler 2021; 28:418-428. [PMID: 34132126 DOI: 10.1177/13524585211023345] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T1 and T2 relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS. OBJECTIVE To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes. METHODS 103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T1, T2, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes. RESULTS A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures. CONCLUSION Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.
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Affiliation(s)
- Irene M Vavasour
- Department of Radiology, The University of British Columbia, UBC Hospital, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada
| | - Peng Sun
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Carina Graf
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Jackie T Yik
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - David Kb Li
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Ana-Luiza Sayao
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alice Schabas
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Virginia Devonshire
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Robert Carruthers
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Gr Wayne Moore
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Sheng-Kwei Song
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Cornelia Laule
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
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33
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Demyelination and remyelination detected in an alternative cuprizone mouse model of multiple sclerosis with 7.0 T multiparameter magnetic resonance imaging. Sci Rep 2021; 11:11060. [PMID: 34040141 PMCID: PMC8155133 DOI: 10.1038/s41598-021-90597-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 05/11/2021] [Indexed: 02/07/2023] Open
Abstract
The aim of this study was to investigate the mechanisms underlying demyelination and remyelination with 7.0 T multiparameter magnetic resonance imaging (MRI) in an alternative cuprizone (CPZ) mouse model of multiple sclerosis (MS). Sixty mice were divided into six groups (n = 10, each), and these groups were imaged with 7.0 T multiparameter MRI and treated with an alternative CPZ administration schedule. T2-weighted imaging (T2WI), susceptibility-weighted imaging (SWI), and diffusion tensor imaging (DTI) were used to compare the splenium of the corpus callosum (sCC) among the groups. Prussian blue and Luxol fast blue staining were performed to assess pathology. The correlations of the mean grayscale value (mGSV) of the pathology results and the MRI metrics were analyzed to evaluate the multiparameter MRI results. One-way ANOVA and post hoc comparison showed that the normalized T2WI (T2-nor), fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) values were significantly different among the six groups, while the mean phase (Φ) value of SWI was not significantly different among the groups. Correlation analysis showed that the correlation between the T2-nor and mGSV was higher than that among the other values. The correlations among the FA, RD, MD, and mGSV remained instructive. In conclusion, ultrahigh-field multiparameter MRI can reflect the pathological changes associated with and the underlying mechanisms of demyelination and remyelination in MS after the successful establishment of an acute CPZ-induced model.
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34
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Singh K, Cornell CS, Jackson R, Kabiri M, Phipps M, Desai M, Fogle R, Ying X, Anarat-Cappillino G, Geller S, Johnson J, Roberts E, Malley K, Devlin T, DeRiso M, Berthelette P, Zhang YV, Ryan S, Rao S, Thurberg BL, Bangari DS, Kyostio-Moore S. CRISPR/Cas9 generated knockout mice lacking phenylalanine hydroxylase protein as a novel preclinical model for human phenylketonuria. Sci Rep 2021; 11:7254. [PMID: 33790381 PMCID: PMC8012645 DOI: 10.1038/s41598-021-86663-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 03/18/2021] [Indexed: 02/01/2023] Open
Abstract
Phenylketonuria (PKU) is an autosomal recessive inborn error of L-phenylalanine (Phe) metabolism. It is caused by a partial or complete deficiency of the enzyme phenylalanine hydroxylase (PAH), which is necessary for conversion of Phe to tyrosine (Tyr). This metabolic error results in buildup of Phe and reduction of Tyr concentration in blood and in the brain, leading to neurological disease and intellectual deficits. Patients exhibit retarded body growth, hypopigmentation, hypocholesterolemia and low levels of neurotransmitters. Here we report first attempt at creating a homozygous Pah knock-out (KO) (Hom) mouse model, which was developed in the C57BL/6 J strain using CRISPR/Cas9 where codon 7 (GAG) in Pah gene was changed to a stop codon TAG. We investigated 2 to 6-month-old, male, Hom mice using comprehensive behavioral and biochemical assays, MRI and histopathology. Age and sex-matched heterozygous Pah-KO (Het) mice were used as control mice, as they exhibit enough PAH enzyme activity to provide Phe and Tyr levels comparable to the wild-type mice. Overall, our findings demonstrate that 6-month-old, male Hom mice completely lack PAH enzyme, exhibit significantly higher blood and brain Phe levels, lower levels of brain Tyr and neurotransmitters along with lower myelin content and have significant behavioral deficit. These mice exhibit phenotypes that closely resemble PKU patients such as retarded body growth, cutaneous hypopigmentation, and hypocholesterolemia when compared to the age- and sex-matched Het mice. Altogether, biochemical, behavioral, and pathologic features of this novel mouse model suggest that it can be used as a reliable translational tool for PKU preclinical research and drug development.
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Affiliation(s)
- Kuldeep Singh
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA ,Present Address: WuXi AppTec Inc., 8th Floor, 55 Cambridge Parkway, Cambridge, MA 02142 USA
| | - Cathleen S. Cornell
- grid.417555.70000 0000 8814 392XGenomic Medicine Unit, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
| | - Robert Jackson
- grid.417555.70000 0000 8814 392XGenomic Medicine Unit, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
| | - Mostafa Kabiri
- grid.420214.1Transgenic Model and Technology, Translational In-Vivo Research Platform, Industrie Park Hoechst, Sanofi, Frankfurt, Germany
| | - Michael Phipps
- grid.417555.70000 0000 8814 392XTransgenic Model and Technology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Mitul Desai
- grid.417555.70000 0000 8814 392XGlobal Bioimaging, Translational In-Vivo Models Research Platform, Sanofi, Framingham, MA 01701 USA
| | - Robert Fogle
- grid.417555.70000 0000 8814 392XGlobal Bioimaging, Translational In-Vivo Models Research Platform, Sanofi, Framingham, MA 01701 USA
| | - Xiaoyou Ying
- grid.417555.70000 0000 8814 392XGlobal Bioimaging, Translational In-Vivo Models Research Platform, Sanofi, Framingham, MA 01701 USA
| | - Gulbenk Anarat-Cappillino
- grid.417555.70000 0000 8814 392XPre-Development Sciences NA, Analytical R&D, Sanofi, Framingham, MA 01701 USA
| | - Sarah Geller
- grid.417555.70000 0000 8814 392XPre-Development Sciences NA, Analytical R&D, Sanofi, Framingham, MA 01701 USA
| | - Jennifer Johnson
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Errin Roberts
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Katie Malley
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Tim Devlin
- grid.417555.70000 0000 8814 392XTransgenic Model and Technology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Matthew DeRiso
- grid.417555.70000 0000 8814 392XTransgenic Model and Technology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Patricia Berthelette
- grid.417555.70000 0000 8814 392XGenomic Medicine Unit, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
| | - Yao V. Zhang
- grid.417555.70000 0000 8814 392XGenomic Medicine Unit, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
| | - Susan Ryan
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Srinivas Rao
- grid.417555.70000 0000 8814 392XTranslational In-Vivo Models Research Platform, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
| | - Beth L. Thurberg
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Dinesh S. Bangari
- grid.417555.70000 0000 8814 392XGlobal Discovery Pathology, Translational In-Vivo Models Research Platform, Sanofi, 5 The Mountain Road, Framingham, MA 01701 USA
| | - Sirkka Kyostio-Moore
- grid.417555.70000 0000 8814 392XGenomic Medicine Unit, Sanofi, 49 New York Avenue, Framingham, MA 01701 USA
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Rahmanzadeh R, Lu PJ, Barakovic M, Weigel M, Maggi P, Nguyen TD, Schiavi S, Daducci A, La Rosa F, Schaedelin S, Absinta M, Reich DS, Sati P, Wang Y, Bach Cuadra M, Radue EW, Kuhle J, Kappos L, Granziera C. Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging. Brain 2021; 144:1684-1696. [PMID: 33693571 PMCID: PMC8374972 DOI: 10.1093/brain/awab088] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 12/29/2020] [Accepted: 01/03/2021] [Indexed: 12/25/2022] Open
Abstract
Damage to the myelin sheath and the neuroaxonal unit is a cardinal feature of multiple sclerosis; however, a detailed characterization of the interaction between myelin and axon damage in vivo remains challenging. We applied myelin water and multi-shell diffusion imaging to quantify the relative damage to myelin and axons (i) among different lesion types; (ii) in normal-appearing tissue; and (iii) across multiple sclerosis clinical subtypes and healthy controls. We also assessed the relation of focal myelin/axon damage with disability and serum neurofilament light chain as a global biological measure of neuroaxonal damage. Ninety-one multiple sclerosis patients (62 relapsing-remitting, 29 progressive) and 72 healthy controls were enrolled in the study. Differences in myelin water fraction and neurite density index were substantial when lesions were compared to healthy control subjects and normal-appearing multiple sclerosis tissue: both white matter and cortical lesions exhibited a decreased myelin water fraction and neurite density index compared with healthy (P < 0.0001) and peri-plaque white matter (P < 0.0001). Periventricular lesions showed decreased myelin water fraction and neurite density index compared with lesions in the juxtacortical region (P < 0.0001 and P < 0.05). Similarly, lesions with paramagnetic rims showed decreased myelin water fraction and neurite density index relative to lesions without a rim (P < 0.0001). Also, in 75% of white matter lesions, the reduction in neurite density index was higher than the reduction in the myelin water fraction. Besides, normal-appearing white and grey matter revealed diffuse reduction of myelin water fraction and neurite density index in multiple sclerosis compared to healthy controls (P < 0.01). Further, a more extensive reduction in myelin water fraction and neurite density index in normal-appearing cortex was observed in progressive versus relapsing-remitting participants. Neurite density index in white matter lesions correlated with disability in patients with clinical deficits (P < 0.01, beta = -10.00); and neurite density index and myelin water fraction in white matter lesions were associated to serum neurofilament light chain in the entire patient cohort (P < 0.01, beta = -3.60 and P < 0.01, beta = 0.13, respectively). These findings suggest that (i) myelin and axon pathology in multiple sclerosis is extensive in both lesions and normal-appearing tissue; (ii) particular types of lesions exhibit more damage to myelin and axons than others; (iii) progressive patients differ from relapsing-remitting patients because of more extensive axon/myelin damage in the cortex; and (iv) myelin and axon pathology in lesions is related to disability in patients with clinical deficits and global measures of neuroaxonal damage.
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Affiliation(s)
- Reza Rahmanzadeh
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Pietro Maggi
- Department of Neurology, Lausanne University Hospital, Lausanne, Switzerland.,Cliniques universitaires Saint Luc, Université catholique de Louvain, Brussel, Belgium
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Radiology Department, Center for Biomedical Imaging (CIBM), Lausanne University and University Hospital, Lausanne, Switzerland
| | - Sabine Schaedelin
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Radiology Department, Center for Biomedical Imaging (CIBM), Lausanne University and University Hospital, Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
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Erramuzpe A, Schurr R, Yeatman JD, Gotlib IH, Sacchet MD, Travis KE, Feldman HM, Mezer AA. A Comparison of Quantitative R1 and Cortical Thickness in Identifying Age, Lifespan Dynamics, and Disease States of the Human Cortex. Cereb Cortex 2021; 31:1211-1226. [PMID: 33095854 PMCID: PMC8485079 DOI: 10.1093/cercor/bhaa288] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/25/2020] [Accepted: 09/03/2020] [Indexed: 07/22/2023] Open
Abstract
Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6-81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.
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Affiliation(s)
| | - R Schurr
- The Hebrew University of Jerusalem, The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
| | - J D Yeatman
- Graduate School of Education, Stanford University, Stanford, CA, USA
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - I H Gotlib
- Psychology, Stanford University, Stanford, CA, USA
| | - M D Sacchet
- Harvard Medical School, Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - K E Travis
- Pediatrics, Stanford University, Stanford, CA, USA
| | - H M Feldman
- Development and Behavior Unit, Stanford University, Stanford, CA, USA
| | - A A Mezer
- The Hebrew University of Jerusalem, The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
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37
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Barros C, Fernandes A. Linking Cognitive Impairment to Neuroinflammation in Multiple Sclerosis using neuroimaging tools. Mult Scler Relat Disord 2020; 47:102622. [PMID: 33227630 DOI: 10.1016/j.msard.2020.102622] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 11/08/2020] [Accepted: 11/09/2020] [Indexed: 12/24/2022]
Abstract
Multiple sclerosis (MS) is a complex chronic immune disease in the central nervous system, causing neurological disability among young and middle-aged adults. Impaired cognition is now emerging as a major clinical symptom being present in more than 50% of MS patients. Recent data support that neuroinflammation mediated by glial cells plays a key part in MS course and, particularly, microglia is responsible for the pruning of synapses possibly impacting on vital neural networks maintenance. However, the knowledge of microglia-mediated mechanisms underlying cognitive impairment in MS is poor and unfortunately, there are no medicines to overcome this "invisible" symptom. Interestingly, the use of powerful diagnostic imaging tools as structural and functional MRI as well as PET brought new insights into some biological mechanisms, but no link between the possibility to use early visible alterations to predict cognitive deficits was clarified yet. In this review, we focus on the interplay between MS-related cognitive structures and neuroinflammation, specifically the presence of microglia and their reactivity. Moreover, we also discuss new imaging tools to assess cognitive impairment and to track microglia activation. Understanding the role of microglia in cognitive impairment and how it can be prevented may be a promising contribution to innovative therapeutic strategies that culminate in the improvement of MS patients' life quality.
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Affiliation(s)
- Catarina Barros
- Neuron-Glia Biology in Health and Disease, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Portugal
| | - Adelaide Fernandes
- Neuron-Glia Biology in Health and Disease, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Portugal; Department of Biochemistry and Human Biology, Faculty of Pharmacy, Universidade de Lisboa, Portugal.
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38
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da Costa RC, De Decker S, Lewis MJ, Volk H. Diagnostic Imaging in Intervertebral Disc Disease. Front Vet Sci 2020; 7:588338. [PMID: 33195623 PMCID: PMC7642913 DOI: 10.3389/fvets.2020.588338] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 09/09/2020] [Indexed: 12/27/2022] Open
Abstract
Imaging is integral in the diagnosis of canine intervertebral disc disease (IVDD) and in differentiating subtypes of intervertebral disc herniation (IVDH). These include intervertebral disc extrusion (IVDE), intervertebral disc protrusion (IVDP) and more recently recognized forms such as acute non-compressive nucleus pulposus extrusion (ANNPE), hydrated nucleus pulposus extrusion (HNPE), and intradural/intramedullary intervertebral disc extrusion (IIVDE). Many imaging techniques have been described in dogs with roles for survey radiographs, myelography, computed tomography (CT), and magnetic resonance imaging (MRI). Given how common IVDH is in dogs, a thorough understanding of the indications and limitations for each imaging modality to aid in diagnosis, treatment planning and prognosis is essential to successful case management. While radiographs can provide useful information, especially for identifying intervertebral disc degeneration or calcification, there are notable limitations. Myelography addresses some of the constraints of survey radiographs but has largely been supplanted by cross-sectional imaging. Computed tomography with or without myelography and MRI is currently utilized most widely and have become the focus of most contemporary studies on this subject. Novel advanced imaging applications are being explored in dogs but are not yet routinely performed in clinical patients. The following review will provide a comprehensive overview on common imaging modalities reported to aid in the diagnosis of IVDH including IVDE, IVDP, ANNPE, HNPE, and IIVDE. The review focuses primarily on canine IVDH due to its frequency and vast literature as opposed to feline IVDH.
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Affiliation(s)
- Ronaldo C da Costa
- Department of Veterinary Clinical Sciences, The Ohio State University, Columbus, OH, United States
| | - Steven De Decker
- Department of Clinical Sciences and Services, Royal Veterinary College, London, United Kingdom
| | - Melissa J Lewis
- Department of Veterinary Clinical Sciences, Purdue University College of Veterinary Medicine, West Lafayette, IN, United States
| | - Holger Volk
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hanover, Hanover, Germany
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39
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Mancini M, Karakuzu A, Cohen-Adad J, Cercignani M, Nichols TE, Stikov N. An interactive meta-analysis of MRI biomarkers of myelin. eLife 2020; 9:e61523. [PMID: 33084576 PMCID: PMC7647401 DOI: 10.7554/elife.61523] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 10/20/2020] [Indexed: 12/17/2022] Open
Abstract
Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analyzed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology.
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Affiliation(s)
- Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of SussexBrightonUnited Kingdom
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- CUBRIC, Cardiff UniversityCardiffUnited Kingdom
| | | | - Julien Cohen-Adad
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- Functional Neuroimaging Unit, CRIUGM, Université de MontréalMontrealCanada
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, University of SussexBrightonUnited Kingdom
- Neuroimaging Laboratory, Fondazione Santa LuciaRomeItaly
| | - Thomas E Nichols
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of OxfordOxfordUnited Kingdom
- Big Data Institute, University of OxfordOxfordUnited Kingdom
| | - Nikola Stikov
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- Montreal Heart Institute, Université de MontréalMontrealCanada
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40
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Destri A, Sánchez L, Stewart J, Dennis R. Clinical, MRI and histopathological findings in a dog with distemper meningomyelitis. VETERINARY RECORD CASE REPORTS 2020. [DOI: 10.1136/vetreccr-2020-001173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Alessandra Destri
- Small Animal Referrals, Diagnostic ImagingAnimal Health TrustNewmarketUK
| | - Lluís Sánchez
- Small Animal Referrals, Neurology and NeurosurgeryAnimal Health TrustNewmarketSuffolkUK
| | - Jennifer Stewart
- Small Animal Referrals, PathologyAnimal Health TrustNewmarketSuffolkUK
| | - Ruth Dennis
- Small Animal Referrals, Diagnostic ImagingAnimal Health TrustNewmarketUK
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41
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Piredda GF, Hilbert T, Canales-Rodríguez EJ, Pizzolato M, von Deuster C, Meuli R, Pfeuffer J, Daducci A, Thiran JP, Kober T. Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA. Magn Reson Med 2020; 85:209-222. [PMID: 32720406 DOI: 10.1002/mrm.28427] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 06/17/2020] [Accepted: 06/23/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T2 acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns. METHODS A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T2 data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm3 , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm3 , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps. RESULTS Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of -0.2% (P = .24) with the limits of agreement ranging from -3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps. CONCLUSION By combining a 3D multi-echo GRASE sequence with CAIPIRINHA sampling, whole-brain MWF maps were obtained in 10:30 min with 1.6 mm isotropic resolution. The good correlation with conventional MESE-based maps demonstrates that the implemented sequence may be a promising alternative to time-consuming MESE acquisitions.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Erick Jorge Canales-Rodríguez
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain
| | - Marco Pizzolato
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Constantin von Deuster
- Siemens Healthcare AG, Zurich, Switzerland
- SCMI, Swiss Center for Musculoskeletal Imaging, Zurich, Switzerland
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Josef Pfeuffer
- Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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42
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Rocca MA, Preziosa P, Filippi M. What role should spinal cord MRI take in the future of multiple sclerosis surveillance? Expert Rev Neurother 2020; 20:783-797. [PMID: 32133874 DOI: 10.1080/14737175.2020.1739524] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
INTRODUCTION In multiple sclerosis (MS), inflammatory, demyelinating, and neurodegenerative phenomena affect the spinal cord, with detrimental effects on patients' clinical disability. Although spinal cord imaging may be challenging, improvements in MRI technologies have contributed to better evaluate spinal cord involvement in MS. AREAS COVERED This review summarizes the current state-of-art of the application of conventional and advanced MRI techniques to evaluate spinal cord damage in MS. Typical features of spinal cord lesions, their role in the diagnostic work-up of suspected MS, their predictive role for subsequent disease course and clinical worsening, and their utility to define treatment response are discussed. The role of spinal cord atrophy and of other advanced MRI techniques to better evaluate the associations between spinal cord abnormalities and the accumulation of clinical disability are also evaluated. Finally, how spinal cord assessment could evolve in the future to improve monitoring of disease progression and treatment effects is examined. EXPERT OPINION Spinal cord MRI provides relevant additional information to brain MRI in understanding MS pathophysiology, in allowing an earlier and more accurate diagnosis of MS, and in identifying MS patients at higher risk to develop more severe disability. A future role in monitoring the effects of treatments is also foreseen.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute , Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute , Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute , Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute , Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute , Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute , Milan, Italy.,Neurophysiology Unit, IRCCS San Raffaele Scientific Institute , Milan, Italy.,Vita-Salute San Raffaele University , Milan, Italy
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43
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Geeraert BL, Lebel RM, Lebel C. A multiparametric analysis of white matter maturation during late childhood and adolescence. Hum Brain Mapp 2019; 40:4345-4356. [PMID: 31282058 DOI: 10.1002/hbm.24706] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 05/28/2019] [Accepted: 06/21/2019] [Indexed: 12/21/2022] Open
Abstract
White matter development has been well described using diffusion tensor imaging (DTI), but the microstructural processes driving development remain unclear due to methodological limitations. Here, using neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT), and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT), we describe white matter development at the microstructural level in a longitudinal cohort of healthy 6-15 year olds. We evaluated age and gender-related trends in fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), orientation dispersion index (ODI), quantitative ihMT (qihMT), myelin volume fraction (VFm ), and g-ratio. We found age-related increases of VFm in most regions, showing ongoing myelination in vivo during late childhood and adolescence for the first time. No relationship was observed between qihMT and age, suggesting myelin volume increases are driven by increased water content. Age-related increases were observed for NDI, suggesting axonal packing is also occurring during this time. g-ratio decreased with age in the uncinate fasciculus, implying changes in communication efficiency are ongoing in this region. FA increased and MD decreased with age in most regions. Gender effects were present in the left cingulum for FA, and an age-by-gender interaction was found for MD in the left uncinate fasciculus. These findings suggest that FA and MD remain useful markers of gender-related processes, and gender differences are likely driven by factors other than myelin. We conclude that white matter development during late childhood and adolescence is driven by a combination of axonal packing and myelin volume increases.
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Affiliation(s)
- Bryce L Geeraert
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Robert Marc Lebel
- Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Radiology, University of Calgary, Calgary, Alberta, Canada.,GE Healthcare, Calgary, Canada
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Radiology, University of Calgary, Calgary, Alberta, Canada
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44
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Cortese R, Collorone S, Ciccarelli O, Toosy AT. Advances in brain imaging in multiple sclerosis. Ther Adv Neurol Disord 2019; 12:1756286419859722. [PMID: 31275430 PMCID: PMC6598314 DOI: 10.1177/1756286419859722] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 05/21/2019] [Indexed: 12/31/2022] Open
Abstract
Brain imaging is increasingly used to support clinicians in diagnosing multiple sclerosis (MS) and monitoring its progression. However, the role of magnetic resonance imaging (MRI) in MS goes far beyond its clinical application. Indeed, advanced imaging techniques have helped to detect different components of MS pathogenesis in vivo, which is now considered a heterogeneous process characterized by widespread damage of the central nervous system, rather than multifocal demyelination of white matter. Recently, MRI biomarkers more sensitive to disease activity than clinical disability outcome measures, have been used to monitor response to anti-inflammatory agents in patients with relapsing-remitting MS. Similarly, MRI markers of neurodegeneration exhibit the potential as primary and secondary outcomes in clinical trials for progressive phenotypes. This review will summarize recent advances in brain neuroimaging in MS from the research setting to clinical applications.
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Affiliation(s)
- Rosa Cortese
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
| | - Sara Collorone
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Russell Square, London WC1B 5EH, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
- National Institute for Health Research, UCL Hospitals, Biomedical Research Centre, London, UK
| | - Ahmed T. Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
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45
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Imaging the multiple sclerosis lesion: insights into pathogenesis, progression and repair. Curr Opin Neurol 2019; 32:338-345. [DOI: 10.1097/wco.0000000000000698] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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46
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Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging. Sci Rep 2019; 9:8147. [PMID: 31148572 PMCID: PMC6544650 DOI: 10.1038/s41598-019-44615-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 05/21/2019] [Indexed: 12/16/2022] Open
Abstract
Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.
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Cooper G, Finke C, Chien C, Brandt AU, Asseyer S, Ruprecht K, Bellmann-Strobl J, Paul F, Scheel M. Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis. Front Neurol 2019; 10:334. [PMID: 31024428 PMCID: PMC6465519 DOI: 10.3389/fneur.2019.00334] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 03/19/2019] [Indexed: 01/24/2023] Open
Abstract
Normal appearing white matter (NAWM) damage develops early in multiple sclerosis (MS) and continues in the absence of new lesions. The ratio of T1w and T2w (T1w/T2w ratio), a measure of white matter integrity, has previously shown reduced intensity values in MS NAWM. We evaluate the validity of a standardized T1w/T2w ratio (sT1w/T2w ratio) in MS and whether this method is sensitive in detecting MS-related differences in NAWM. T1w and T2w scans were acquired at 3 Tesla in 47 patients with relapsing-remitting MS and 47 matched controls (HC). T1w/T2w and sT1w/T2w ratios were then calculated. We compared between-group variability between T1w/T2w and sT1w/T2w ratio in HC and MS and assessed for group differences. We also evaluated the relationship between the T1w/T2w and sT1w/T2w ratios and clinically relevant variables. Compared to the classic T1w/T2w ratio, the between-subject variability in sT1w/T2w ratio showed a significant reduction in MS patients (p < 0.001) and HC (p < 0.001). However, only sT1w/T2w ratio values were reduced in patients compared to HC (p < 0.001). The sT1w/T2w ratio intensity values were significantly influenced by age, T2 lesion volume and group status (MS vs. HC) (adjusted R2 = 0.30, p < 0.001). We demonstrate the validity of the sT1w/T2w ratio in MS and that it is more sensitive to MS-related differences in NAWM compared to T1w/T2w ratio. The sT1w/T2w ratio shows promise as an easily-implemented measure of NAWM in MS using readily available scans and simple post-processing methods.
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Affiliation(s)
- Graham Cooper
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claudia Chien
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Susanna Asseyer
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Judith Bellmann-Strobl
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,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 and Berlin Institute of Health, Berlin, Germany.,Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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Miki Y. Magnetic resonance imaging diagnosis of demyelinating diseases: An update. ACTA ACUST UNITED AC 2019. [DOI: 10.1111/cen3.12501] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Yukio Miki
- Department of Diagnostic and Interventional Radiology Osaka City University Graduate School of Medicine Osaka Japan
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Lassmann H. Multiple Sclerosis Pathology and its Reflection by Imaging Technologies: Introduction. Brain Pathol 2018; 28:721-722. [PMID: 30375112 PMCID: PMC8028543 DOI: 10.1111/bpa.12649] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 07/18/2017] [Indexed: 12/25/2022] Open
Affiliation(s)
- Hans Lassmann
- Center for Brain ResearchMedical University of ViennaWienAustria
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