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Cagol A, Ocampo-Pineda M, Lu PJ, Weigel M, Barakovic M, Melie-Garcia L, Chen X, Lutti A, Calabrese P, Kuhle J, Kappos L, Sormani MP, Granziera C. Advanced Quantitative MRI Unveils Microstructural Thalamic Changes Reflecting Disease Progression in Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200299. [PMID: 39270143 DOI: 10.1212/nxi.0000000000200299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/15/2024]
Abstract
BACKGROUND AND OBJECTIVES In patients with multiple sclerosis (PwMS), thalamic atrophy occurs during the disease course. However, there is little understanding of the mechanisms leading to volume loss and of the relationship between microstructural thalamic pathology and disease progression. This cross-sectional and longitudinal study aimed to comprehensively characterize in vivo pathologic changes within thalamic microstructure in PwMS using advanced multiparametric quantitative MRI (qMRI). METHODS Thalamic microstructural integrity was evaluated using quantitative T1, magnetization transfer saturation, multishell diffusion, and quantitative susceptibility mapping (QSM) in 183 PwMS and 105 healthy controls (HCs). The same qMRI protocol was available for 127 PwMS and 73 HCs after a 2-year follow-up period. Inclusion criteria for PwMS encompassed either an active relapsing-remitting MS (RRMS) or inactive progressive MS (PMS) disease course. Thalamic alterations were compared between PwMS and HCs and among disease phenotypes. In addition, the study investigated the relationship between thalamic damage and clinical and conventional MRI measures of disease severity. RESULTS Compared with HCs, PwMS exhibited substantial thalamic alterations, indicative of microstructural and macrostructural damage, demyelination, and disruption in iron homeostasis. These alterations extended beyond focal thalamic lesions, affecting normal-appearing thalamic tissue diffusely. Over the follow-up period, PwMS displayed an accelerated decrease in myelin volume fraction [mean difference in annualized percentage change (MD-ApC) = -1.50; p = 0.041] and increase in quantitative T1 (MD-ApC = 0.92; p < 0.0001) values, indicating heightened demyelinating and neurodegenerative processes. The observed differences between PwMS and HCs were substantially driven by the subgroup with PMS, wherein thalamic degeneration was significantly accelerated, even in comparison with patients with RRMS. Thalamic qMRI alterations showed extensive correlations with conventional MRI, clinical, and cognitive disease burden measures. Disability progression over follow-up was associated with accelerated thalamic degeneration, as reflected by enhanced diffusion (β = -0.067; p = 0.039) and QSM (β = -0.077; p = 0.027) changes. Thalamic qMRI metrics emerged as significant predictors of neurologic and cognitive disability even when accounting for other established markers including white matter lesion load and brain and thalamic atrophy. DISCUSSION These findings offer deeper insights into thalamic pathology in PwMS, emphasizing the clinical relevance of thalamic damage and its link to disease progression. Advanced qMRI biomarkers show promising potential in guiding interventions aimed at mitigating thalamic neurodegenerative processes.
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Affiliation(s)
- Alessandro Cagol
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Mario Ocampo-Pineda
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Po-Jui Lu
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Matthias Weigel
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Muhamed Barakovic
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Lester Melie-Garcia
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Xinjie Chen
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Antoine Lutti
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Pasquale Calabrese
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Jens Kuhle
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Ludwig Kappos
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Maria Pia Sormani
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
| | - Cristina Granziera
- From the Translational Imaging in Neurology (ThINk) Basel (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel; Department of Neurology (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (A.C., M.O.-P., P.-J.L., M.W., M.B., L.M.-G., X.C., J.K., L.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Dipartimento di Scienze della Salute, (A.C., M.P.S.), Università degli Studi di Genova, Italy; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Laboratory for Research in Neuroimaging (A.L.), Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne; Neuropsychology and Behavioral Neurology Unit (P.C.), Division of Cognitive and Molecular Neuroscience, University of Basel, Switzerland; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy
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Callen AM, Zurawski J, Chu R, Tie Y, Tauhid S, Quattrucci M, Healy BC, Bakshi R. The role of 7 T MRI to assess atrophy of the subcortical deep gray matter in relapsing-remitting multiple sclerosis. J Neurol 2024:10.1007/s00415-024-12656-y. [PMID: 39240345 DOI: 10.1007/s00415-024-12656-y] [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: 05/23/2024] [Revised: 08/19/2024] [Accepted: 08/20/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Deep gray matter (DGM) atrophy and lesions are found in multiple sclerosis (MS). OBJECTIVE To optimize automated segmentation for 7 T DGM volumetrics and assess sensitivity to atrophy and relationship to DGM lesions and disability in relapsing-remitting (RR) MS. METHODS 30 RRMS subjects [mean age 44.0 years, median Expanded Disability Status Scale (EDSS) score 2] and 14 healthy controls underwent 7 T MRI with 3D magnetization-prepared 2 rapid gradient-echoes (MP2RAGE) and fluid-attenuated inversion recovery. Customizing an automated pipeline to assess DGM structure volumes required pre-processing combining two MP2RAGE inversion times and uniform T1 images, and noise-suppressed reconstruction. DGM volumes were normalized. Brain DGM lesions and white matter T2 lesion volume (T2LV) were expert-quantified. Spearman correlations and Wilcoxon rank-sum tests were assessed. RESULTS DGM lesions were found in 77% (n = 23) of MS subjects and no controls, with thalamic lesions most prevalent (73%). An average of 3.6 DGM lesions was found per person with MS. Total DGM volumes were lower in MS vs. controls (p = 0.034), varying by region, most pronounced in the caudate (p = 0.008). DGM volumes inversely correlated with EDSS (total DGM: r = - 0.45, p = 0.014; globus pallidus: r = - 0.42, p = 0.023; putamen: r = - 0.44, p = 0.016; caudate: r = - 0.37, p = 0.047) and T2LV (total DGM: r = - 0.53, p = 0.003; putamen: r = - 0.40, p = 0.030; thalamus: r = - 0.63, p < 0.001). DGM atrophy was most closely linked to disability among all MRI measures. Thalamic lesion volume correlated inversely with thalamic volume (r = - 0.38, p = 0.045). CONCLUSION 7 T MRI shows a link between DGM atrophy and both white matter lesions and physical disability in RRMS. Thalamic lesions are associated with thalamic atrophy.
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Affiliation(s)
- Alexis M Callen
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Jonathan Zurawski
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Renxin Chu
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Yanmei Tie
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shahamat Tauhid
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Molly Quattrucci
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Brian C Healy
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA
| | - Rohit Bakshi
- Department of Neurology, Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Rd, Mailbox, 9002L, Boston, MA, 02115-6128, USA.
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Wang X, Liu S, Yan Z, Yin F, Feng J, Liu H, Liu Y, Li Y. Radiomics Nomograms Based on Multi-sequence MRI for Identifying Cognitive Impairment and Predicting Cognitive Progression in Relapsing-Remitting Multiple Sclerosis. Acad Radiol 2024:S1076-6332(24)00591-9. [PMID: 39198138 DOI: 10.1016/j.acra.2024.08.026] [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: 07/08/2024] [Revised: 08/08/2024] [Accepted: 08/14/2024] [Indexed: 09/01/2024]
Abstract
RATIONALE AND OBJECTIVES To build radiomics nomograms based on multi-sequence MRI to facilitate the identification of cognitive impairment (CI) and prediction of cognitive progression (CP) in patients with relapsing-remitting multiple sclerosis (RRMS). MATERIALS AND METHODS We retrospectively included two RRMS cohorts with multi-sequence MRI and Symbol Digit Modalities Test (SDMT) data: dataset1 (n = 149, for training and validation) and dataset2 (n = 29, for external validation). 80 patients of dataset1 had a 2-year follow-up SDMT. CI and CP were evaluated using SDMT scores at baseline and follow-up. The included DIR sequence aided in identifying cortical lesions. Lesion radiomics and structural features were extracted and selected from multi-sequence MRI, followed by the computation of radiomics and structural scores. The nomogram was developed through multivariate logistic regression, integrating clinical data, radiomics, and structural scores to identify CI in patients. Moreover, a similar method was employed to further construct a nomogram predicting CP in patients. RESULTS The nomogram demonstrated superior performance in identifying patients with CI, with area under the curve (AUC) values of 0.937 (95% Conf. Interval: 0.898-0.975) and 0.876 (0.810-0.943) in internal and external validation sets, compared to models solely based on clinical data, lesion radiomics, and structural features. Furthermore, another nomogram constructed in predicting CP also exhibited outstanding performance, with an AUC value of 0.969 (0.875-1.000) in the validation set. CONCLUSION These nomograms, integrating clinical data, multi-sequence lesions radiomics, and structural features, enable more effective identification of CI and early prediction of CP in RRMS patients, providing important support for clinical decision-making.
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Affiliation(s)
- Xiaohua Wang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Shangqing Liu
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Zichun Yan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Feiyue Yin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jinzhou Feng
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Hao Liu
- Yizhun Medical AI, Beijing 100000, China
| | - Yanbing Liu
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
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Cortese R, Battaglini M, Stromillo ML, Luchetti L, Leoncini M, Gentile G, Gasparini D, Plantone D, Altieri M, D'Ambrosio A, Gallo A, Giannì C, Piervincenzi C, Pantano P, Pagani E, Valsasina P, Preziosa P, Tedone N, Rocca MA, Filippi M, De Stefano N. Regional hippocampal atrophy reflects memory impairment in patients with early relapsing remitting multiple sclerosis. J Neurol 2024; 271:4897-4908. [PMID: 38743090 PMCID: PMC11319433 DOI: 10.1007/s00415-024-12290-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND Research work has shown that hippocampal subfields are atrophic to varying extents in multiple sclerosis (MS) patients. However, studies examining the functional implications of subfield-specific hippocampal damage in early MS are limited. We aim to gain insights into the relationship between hippocampal atrophy and memory function by investigating the correlation between global and regional hippocampal atrophy and memory performance in early MS patients. METHODS From the Italian Neuroimaging Network Initiative (INNI) dataset, we selected 3D-T1-weighted brain MRIs of 219 early relapsing remitting (RR)MS and 246 healthy controls (HC) to identify hippocampal atrophic areas. At the time of MRI, patients underwent Selective-Reminding-Test (SRT) and Spatial-Recall-Test (SPART) and were classified as mildly (MMI-MS: n.110) or severely (SMI-MS: n:109) memory impaired, according to recently proposed cognitive phenotypes. RESULTS Early RRMS showed lower hippocampal volumes compared to HC (p < 0.001), while these did not differ between MMI-MS and SMI-MS. In MMI-MS, lower hippocampal volumes correlated with worse memory tests (r = 0.23-0.37, p ≤ 0.01). Atrophic voxels were diffuse in the hippocampus but more prevalent in cornu ammonis (CA, 79%) than in tail (21%). In MMI-MS, decreased subfield volumes correlated with decreases in memory, particularly in the right CA1 (SRT-recall: r = 0.38; SPART: r = 0.34, p < 0.01). No correlations were found in the SMI-MS group. CONCLUSION Hippocampal atrophy spreads from CA to tail from early disease stages. Subfield hippocampal atrophy is associated with memory impairment in MMI-MS, while this correlation is lost in SMI-MS. This plays in favor of a limited capacity for an adaptive functional reorganization of the hippocampi in MS patients.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
- SIENA Imaging SRL, 53100, Siena, Italy
| | - Maria Laura Stromillo
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
| | - Ludovico Luchetti
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
- SIENA Imaging SRL, 53100, Siena, Italy
| | - Matteo Leoncini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
- SIENA Imaging SRL, 53100, Siena, Italy
| | - Giordano Gentile
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
- SIENA Imaging SRL, 53100, Siena, Italy
| | - Daniele Gasparini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
| | - Domenico Plantone
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
| | - Manuela Altieri
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Alessandro D'Ambrosio
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Costanza Giannì
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli, IS, Italy
| | | | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli, IS, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Nicolo' Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy.
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Young G, Nguyen VS, Howlett-Prieto Q, Abuaf AF, Carroll TJ, Kawaji K, Javed A. T1 mapping from routine 3D T1-weighted inversion recovery sequences in clinical practice: comparison against reference inversion recovery fast field echo T1 scans and feasibility in multiple sclerosis. Neuroradiology 2024:10.1007/s00234-024-03400-4. [PMID: 38880824 DOI: 10.1007/s00234-024-03400-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 06/06/2024] [Indexed: 06/18/2024]
Abstract
BACKGROUND AND PURPOSE Quantitative T1 mapping can be an essential tool for assessing tissue injury in multiple sclerosis (MS). We introduce T1-REQUIRE, a method that converts a single high-resolution anatomical 3D T1-weighted Turbo Field Echo (3DT1TFE) scan into a parametric T1 map that could be used for quantitative assessment of tissue damage. We present the accuracy and feasibility of this method in MS. METHODS 14 subjects with relapsing-remitting MS and 10 healthy subjects were examined. T1 maps were generated from 3DT1TFE images using T1-REQUIRE, which estimates T1 values using MR signal equations and internal tissue reference T1 values. Estimated T1 of lesions, white, and gray matter regions were compared with reference Inversion-Recovery Fast Field Echo T1 values and analyzed via correlation and Bland-Altman (BA) statistics. RESULTS 159 T1-weighted (T1W) hypointense MS lesions and 288 gray matter regions were examined. T1 values for MS lesions showed a Pearson's correlation of r = 0.81 (p < 0.000), R2 = 0.65, and Bias = 4.18%. BA statistics showed a mean difference of -53.95 ms and limits of agreement (LOA) of -344.20 and 236.30 ms. Non-lesional normal-appearing white matter had a correlation coefficient of r = 0.82 (p < 0.000), R2 = 0.67, Bias = 8.78%, mean difference of 73.87 ms, and LOA of -55.67 and 203.41 ms. CONCLUSIONS We demonstrate the feasibility of retroactively derived high-resolution T1 maps from routinely acquired anatomical images, which could be used to quantify tissue pathology in MS. The results of this study will set the stage for testing this method in larger clinical studies for examining MS disease activity and progression.
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Affiliation(s)
- Griffin Young
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Vivian S Nguyen
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Quentin Howlett-Prieto
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Timothy J Carroll
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Keigo Kawaji
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Adil Javed
- Department of Neurology, The University of Chicago, Chicago, IL, 5841 South Maryland Avenue, MC2030, 60637, USA.
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6
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Guadalupi L, Vanni V, Balletta S, Caioli S, De Vito F, Fresegna D, Sanna K, Nencini M, Donninelli G, Volpe E, Mariani F, Battistini L, Stampanoni Bassi M, Gilio L, Bruno A, Dolcetti E, Buttari F, Mandolesi G, Centonze D, Musella A. Interleukin-9 protects from microglia- and TNF-mediated synaptotoxicity in experimental multiple sclerosis. J Neuroinflammation 2024; 21:128. [PMID: 38745307 PMCID: PMC11092167 DOI: 10.1186/s12974-024-03120-9] [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: 02/09/2024] [Accepted: 05/01/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a progressive neurodegenerative disease of the central nervous system characterized by inflammation-driven synaptic abnormalities. Interleukin-9 (IL-9) is emerging as a pleiotropic cytokine involved in MS pathophysiology. METHODS Through biochemical, immunohistochemical, and electrophysiological experiments, we investigated the effects of both peripheral and central administration of IL-9 on C57/BL6 female mice with experimental autoimmune encephalomyelitis (EAE), a model of MS. RESULTS We demonstrated that both systemic and local administration of IL-9 significantly improved clinical disability, reduced neuroinflammation, and mitigated synaptic damage in EAE. The results unveil an unrecognized central effect of IL-9 against microglia- and TNF-mediated neuronal excitotoxicity. Two main mechanisms emerged: first, IL-9 modulated microglial inflammatory activity by enhancing the expression of the triggering receptor expressed on myeloid cells-2 (TREM2) and reducing TNF release. Second, IL-9 suppressed neuronal TNF signaling, thereby blocking its synaptotoxic effects. CONCLUSIONS The data presented in this work highlight IL-9 as a critical neuroprotective molecule capable of interfering with inflammatory synaptopathy in EAE. These findings open new avenues for treatments targeting the neurodegenerative damage associated with MS, as well as other inflammatory and neurodegenerative disorders of the central nervous system.
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Affiliation(s)
- Livia Guadalupi
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
| | - Valentina Vanni
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
| | - Sara Balletta
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
| | - Silvia Caioli
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
| | | | - Diego Fresegna
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
| | - Krizia Sanna
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
| | - Monica Nencini
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
| | - Gloria Donninelli
- Molecular Neuroimmunology Unit, IRCCS Fondazione Santa Lucia, Via del Fosso di Fiorano 64, Rome, 00143, Italy
| | - Elisabetta Volpe
- Molecular Neuroimmunology Unit, IRCCS Fondazione Santa Lucia, Via del Fosso di Fiorano 64, Rome, 00143, Italy
| | - Fabrizio Mariani
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
| | - Luca Battistini
- Neuroimmunology Unit, IRCCS Fondazione Santa Lucia, Via del Fosso di Fiorano 64, Rome, 00143, Italy
| | | | - Luana Gilio
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
| | - Antonio Bruno
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
- Ph.D. Program in Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
| | - Ettore Dolcetti
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
- Ph.D. Program in Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
| | - Fabio Buttari
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy
| | - Georgia Mandolesi
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
- Department of Human Sciences and Quality of Life Promotion, University of Rome San Raffaele, Rome, 00166, Italy
| | - Diego Centonze
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, 00133, Italy.
- Unit of Neurology, IRCCS Neuromed, Pozzilli (Is), 86077, Italy.
| | - Alessandra Musella
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Rome, 00166, Italy
- Department of Human Sciences and Quality of Life Promotion, University of Rome San Raffaele, Rome, 00166, Italy
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7
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Thornton MA, Futia GL, Stockton ME, Budoff SA, Ramirez AN, Ozbay B, Tzang O, Kilborn K, Poleg-Polsky A, Restrepo D, Gibson EA, Hughes EG. Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis. Nat Neurosci 2024; 27:846-861. [PMID: 38539013 PMCID: PMC11104262 DOI: 10.1038/s41593-024-01613-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/26/2024] [Indexed: 04/09/2024]
Abstract
The generation of new myelin-forming oligodendrocytes in the adult central nervous system is critical for cognitive function and regeneration following injury. Oligodendrogenesis varies between gray and white matter regions, suggesting that local cues drive regional differences in myelination and the capacity for regeneration. However, the layer- and region-specific regulation of oligodendrocyte populations is unclear due to the inability to monitor deep brain structures in vivo. Here we harnessed the superior imaging depth of three-photon microscopy to permit long-term, longitudinal in vivo three-photon imaging of the entire cortical column and subcortical white matter in adult mice. We find that cortical oligodendrocyte populations expand at a higher rate in the adult brain than those of the white matter. Following demyelination, oligodendrocyte replacement is enhanced in the white matter, while the deep cortical layers show deficits in regenerative oligodendrogenesis and the restoration of transcriptional heterogeneity. Together, our findings demonstrate that regional microenvironments regulate oligodendrocyte population dynamics and heterogeneity in the healthy and diseased brain.
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Affiliation(s)
- Michael A Thornton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gregory L Futia
- Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Michael E Stockton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Samuel A Budoff
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Alexandra N Ramirez
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Baris Ozbay
- Intelligent Imaging Innovations, Denver, CO, USA
| | - Omer Tzang
- Intelligent Imaging Innovations, Denver, CO, USA
| | - Karl Kilborn
- Intelligent Imaging Innovations, Denver, CO, USA
| | - Alon Poleg-Polsky
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Diego Restrepo
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Emily A Gibson
- Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ethan G Hughes
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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8
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Nicola MA, Attaai AH, Abdel-Raheem MH, Mohammed AF, Abu-Elhassan YF. Neuroprotective effects of rutin against cuprizone-induced multiple sclerosis in mice. Inflammopharmacology 2024; 32:1295-1315. [PMID: 38512652 PMCID: PMC11006763 DOI: 10.1007/s10787-024-01442-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: 07/29/2023] [Accepted: 01/24/2024] [Indexed: 03/23/2024]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease of the central nervous system that injures the myelin sheath, provoking progressive axonal degeneration and functional impairments. No efficient therapy is available at present to combat such insults, and hence, novel safe and effective alternatives for MS therapy are extremely required. Rutin (RUT) is a flavonoid that exhibits antioxidant, anti-inflammatory, and neuroprotective effects in several brain injuries. The present study evaluated the potential beneficial effects of two doses of RUT in a model of pattern-III lesion of MS, in comparison to the conventional standard drug; dimethyl fumarate (DMF). Demyelination was induced in in male adult C57BL/6 mice by dietary 0.2% (w/w) cuprizone (CPZ) feeding for 6 consecutive weeks. Treated groups received either oral RUT (50 or 100 mg/kg) or DMF (15 mg/kg), along with CPZ feeding, for 6 consecutive weeks. Mice were then tested for behavioral changes, followed by biochemical analyses and histological examinations of the corpus callosum (CC). Results revealed that CPZ caused motor dysfunction, demyelination, and glial activation in demyelinated lesions, as well as significant oxidative stress, and proinflammatory cytokine elevation. Six weeks of RUT treatment significantly improved locomotor activity and motor coordination. Moreover, RUT considerably improved remyelination in the CC of CPZ + RUT-treated mice, as revealed by luxol fast blue staining and transmission electron microscopy. Rutin also significantly attenuated CPZ-induced oxidative stress and inflammation in the CC of tested animals. The effect of RUT100 was obviously more marked than either that of DMF, regarding most of the tested parameters, or even its smaller tested dose. In silico docking revealed that RUT binds tightly within NF-κB at the binding site of the protein-DNA complex, with a good negative score of -6.79 kcal/mol. Also, RUT-Kelch-like ECH-associated protein 1 (Keap1) model clarifies the possible inhibition of Keap1-Nrf2 protein-protein interaction. Findings of the current study provide evidence for the protective effect of RUT in CPZ-induced demyelination and behavioral dysfunction in mice, possibly by modulating NF-κB and Nrf2 signaling pathways. The present study may be one of the first to indicate a pro-remyelinating effect for RUT, which might represent a potential additive benefit in treating MS.
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Affiliation(s)
- Mariam A Nicola
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Assiut University, Asyût, 71526, Egypt.
| | - Abdelraheim H Attaai
- Department of Anatomy and Histology, School of Veterinary Medicine, Badr University in Assiut, New Nasser City, West of Assiut, Asyût, Egypt
- Department of Anatomy and Embryology, Faculty of Veterinary Medicine, Assiut University, Asyût, 71526, Egypt
| | | | - Anber F Mohammed
- Department of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Assiut University, Asyût, 71526, Egypt
| | - Yasmin F Abu-Elhassan
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Assiut University, Asyût, 71526, Egypt
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9
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Niehaus P, Gonzalez de Vega R, Haindl MT, Birkl C, Leoni M, Birkl-Toeglhofer AM, Haybaeck J, Ropele S, Seeba M, Goessler W, Karst U, Langkammer C, Clases D. Multimodal analytical tools for the molecular and elemental characterisation of lesions in brain tissue of multiple sclerosis patients. Talanta 2024; 270:125518. [PMID: 38128277 DOI: 10.1016/j.talanta.2023.125518] [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: 09/13/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 12/23/2023]
Abstract
Multiple sclerosis (MS) is a prevalent immune-mediated inflammatory disease of the central nervous system inducing a widespread degradation of myelin and resulting in neurological deficits. Recent advances in molecular and atomic imaging provide the means to probe the microenvironment in affected brain tissues at an unprecedented level of detail and may provide new insights. This study showcases state-of-the-art spectroscopic and mass spectrometric techniques to compare distributions of molecular and atomic entities in MS lesions and surrounding brain tissues. MS brains underwent post-mortem magnetic resonance imaging (MRI) to locate and subsequently dissect MS lesions and surrounding white matter. Digests of lesions and unaffected white matter were analysed via ICP-MS/MS revealing significant differences in concentrations of Li, Mg, P, K, Mn, V, Rb, Ag, Gd and Bi. Micro x-ray fluorescence spectroscopy (μXRF) and laser ablation - inductively coupled plasma - time of flight - mass spectrometry (LA-ICP-ToF-MS) were used as micro-analytical imaging techniques to study distributions of both endogenous and xenobiotic elements. The essential trace elements Fe, Cu and Zn were subsequently calibrated using in-house manufactured gelatine standards. Lipid distributions were studied using IR-micro spectroscopy and matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI). MALDI-MSI was complemented with high-resolution tandem mass spectrometry and trapped ion mobility spectroscopy for the annotation of specified phospho- and sphingolipids, revealing specific lipid species decreased in MS lesions compared to surrounding white matter. This explorative study demonstrated that modern molecular and atomic mapping techniques provide high-resolution imaging for relevant bio-indicative entities which may complement our current understanding of the underlying pathophysiological processes.
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Affiliation(s)
- Peter Niehaus
- Institute of Inorganic and Analytical Chemistry, University of Münster, Germany
| | | | | | - Christoph Birkl
- Department of Radiology, Medical University of Innsbruck, Austria
| | - Marlene Leoni
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria
| | - Anna Maria Birkl-Toeglhofer
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria; Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Austria
| | - Johannes Haybaeck
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria
| | | | | | - Uwe Karst
- Institute of Inorganic and Analytical Chemistry, University of Münster, Germany
| | | | - David Clases
- Institute of Chemistry, University of Graz, Austria.
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10
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Degraeve B, Henry A, Lenne B. Relationship between emotion recognition and cognition in multiple sclerosis: a meta-analysis protocol. BMJ Neurol Open 2024; 6:e000471. [PMID: 38268751 PMCID: PMC10806822 DOI: 10.1136/bmjno-2023-000471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 11/05/2023] [Indexed: 01/26/2024] Open
Abstract
Introduction Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease of the central nervous system characterised by a broad and unpredictable range of symptoms, including cognitive and socio-cognitive dysfunction. Alongside the well-known deficits in information processing speed (IPS), executive functioning and episodic memory, recent evidence also highlighted socio-cognitive impairments in MS, such as emotion-recognition deficits. Recently, several studies investigated the association between emotion-recognition and cognitive impairment to assess whether social cognition is parallel to (or even dependent on) general cognitive dysfunction. Yet, there have been inconsistent findings, raising the need for a meta-analysis of the literature. Objectives The aim of the present paper is to outline the protocol for an upcoming meta-analysis we designed to clarify these conclusions. Methods and analysis We plan to estimate combined effect sizes for the association between emotion-recognition and cognitive impairment in MS across three cognitive domains (IPS, executive functions and episodic memory) and 7 emotion scores of interests (total and by 6-basic emotions subscores). Further, we plan to investigate whether identified variables are the cause for heterogeneity in any combined association. To that end, we will conduct additional meta-regression analyses to explore whether overall correlations differ according to clinical characteristics of MS patients (ie, disease duration, MS-phenotype, severity of depression and disability). Ultimately, this study will provide support either for an association of these disorders (in which emotion-recognition deficits might result from more fundamental cognitive dysfunction), or for two distinct sets of symptoms which may occur independently, for targeted patient profiles.
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Affiliation(s)
| | - Audrey Henry
- C2S (EA 6291), Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, Université de Reims Champagne-Ardenne, Reims, France
| | - Bruno Lenne
- FLSH/ETHICS (EA7446), Lille Catholic University, Lille, France
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11
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Oertel FC, Hastermann M, Paul F. Delimiting MOGAD as a disease entity using translational imaging. Front Neurol 2023; 14:1216477. [PMID: 38333186 PMCID: PMC10851159 DOI: 10.3389/fneur.2023.1216477] [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: 05/03/2023] [Accepted: 08/23/2023] [Indexed: 02/10/2024] Open
Abstract
The first formal consensus diagnostic criteria for myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) were recently proposed. Yet, the distinction of MOGAD-defining characteristics from characteristics of its important differential diagnoses such as multiple sclerosis (MS) and aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorder (NMOSD) is still obstructed. In preclinical research, MOG antibody-based animal models were used for decades to derive knowledge about MS. In clinical research, people with MOGAD have been combined into cohorts with other diagnoses. Thus, it remains unclear to which extent the generated knowledge is specifically applicable to MOGAD. Translational research can contribute to identifying MOGAD characteristic features by establishing imaging methods and outcome parameters on proven pathophysiological grounds. This article reviews suitable animal models for translational MOGAD research and the current state and prospect of translational imaging in MOGAD.
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Affiliation(s)
- Frederike Cosima Oertel
- Experimental and Clinical Research Center, Max-Delbrück-Centrum für Molekulare Medizin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Maria Hastermann
- Experimental and Clinical Research Center, Max-Delbrück-Centrum für Molekulare Medizin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max-Delbrück-Centrum für Molekulare Medizin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology, Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
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12
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Shahbodaghy F, Shafaghi L, Rostampour M, Rostampour A, Kolivand P, Gharaylou Z. Symmetry differences of structural connectivity in multiple sclerosis and healthy state. Brain Res Bull 2023; 205:110816. [PMID: 37972899 DOI: 10.1016/j.brainresbull.2023.110816] [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: 04/13/2023] [Revised: 10/27/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
Focal and diffuse cerebral damages occur in Multiple Sclerosis (MS) that promotes profound shifts in local and global structural connectivity parameters, mainly derived from diffusion tensor imaging. Most of the reconstruction analyses have applied conventional tracking algorithms largely based on the controversial streamline count. For a more credible explanation of the diffusion MRI signal, we used convex optimization modeling for the microstructure-informed tractography2 (COMMIT2) framework. All multi-shell diffusion data from 40 healthy controls (HCs) and 40 relapsing-remitting MS (RRMS) patients were transformed into COMMIT2-weighted matrices based on the Schefer-200 parcels atlas (7 networks) and 14 bilateral subcortical regions. The success of the classification process between MS and healthy state was efficiently predicted by the left DMN-related structures and visual network-associated pathways. Additionally, the lesion volume and age of onset were remarkably correlated with the components of the left DMN. Using complementary approaches such as global metrics revealed differences in WM microstructural integrity between MS and HCs (efficiency, strength). Our findings demonstrated that the cutting-edge diffusion MRI biomarkers could hold the potential for interpreting brain abnormalities in a more distinctive way.
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Affiliation(s)
- Fatemeh Shahbodaghy
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
| | - Lida Shafaghi
- Department of Neuroscience, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Massoumeh Rostampour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ali Rostampour
- Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran
| | - Pirhossein Kolivand
- Department of Health Economics, School of Medicine, Shahed University, Tehran, Iran
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13
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Finsterer J. Sudden Death Is More Likely to Result From SARS-COV-2 Infection Than Multiple Sclerosis. J Korean Med Sci 2023; 38:e393. [PMID: 37967883 PMCID: PMC10643249 DOI: 10.3346/jkms.2023.38.e393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/13/2023] [Indexed: 11/17/2023] Open
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14
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Krupka D, Serrazina F, Salavisa M. Demyelination induced galactorrhea: an atypical presentation of multiple sclerosis. Neurol Sci 2023; 44:4155-4157. [PMID: 37407770 DOI: 10.1007/s10072-023-06935-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 06/28/2023] [Indexed: 07/07/2023]
Affiliation(s)
- Danna Krupka
- Serviço de Neurologia, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Morada: Rua da Junqueira, 126, 1349-019, Lisboa, Portugal.
| | - Filipa Serrazina
- Serviço de Neurologia, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Morada: Rua da Junqueira, 126, 1349-019, Lisboa, Portugal
| | - Manuel Salavisa
- Serviço de Neurologia, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Morada: Rua da Junqueira, 126, 1349-019, Lisboa, Portugal
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15
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Thornton MA, Futia GL, Stockton ME, Budoff SA, Ramirez AN, Ozbay B, Tzang O, Kilborn K, Poleg-Polsky A, Restrepo D, Gibson EA, Hughes EG. Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.29.564636. [PMID: 37961298 PMCID: PMC10634963 DOI: 10.1101/2023.10.29.564636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The generation of new myelin-forming oligodendrocytes in the adult CNS is critical for cognitive function and regeneration following injury. Oligodendrogenesis varies between gray and white matter regions suggesting that local cues drive regional differences in myelination and the capacity for regeneration. Yet, the determination of regional variability in oligodendrocyte cell behavior is limited by the inability to monitor the dynamics of oligodendrocytes and their transcriptional subpopulations in white matter of the living brain. Here, we harnessed the superior imaging depth of three-photon microscopy to permit long-term, longitudinal in vivo three-photon imaging of an entire cortical column and underlying subcortical white matter without cellular damage or reactivity. Using this approach, we found that the white matter generated substantially more new oligodendrocytes per volume compared to the gray matter, yet the rate of population growth was proportionally higher in the gray matter. Following demyelination, the white matter had an enhanced population growth that resulted in higher oligodendrocyte replacement compared to the gray matter. Finally, deep cortical layers had pronounced deficits in regenerative oligodendrogenesis and restoration of the MOL5/6-positive oligodendrocyte subpopulation following demyelinating injury. Together, our findings demonstrate that regional microenvironments regulate oligodendrocyte population dynamics and heterogeneity in the healthy and diseased brain.
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Affiliation(s)
- Michael A. Thornton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | | | - Michael E. Stockton
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Samuel A. Budoff
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus
| | - Alexandra N Ramirez
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Baris Ozbay
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Omer Tzang
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Karl Kilborn
- Intelligent Imaging Innovations (3i), Denver, CO, USA
| | - Alon Poleg-Polsky
- Physiology and Biophysics, University of Colorado Anschutz Medical Campus
| | - Diego Restrepo
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
| | - Emily A. Gibson
- Bioengineering, University of Colorado Anschutz Medical Campus
| | - Ethan G. Hughes
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus
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16
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Vasileiou ES, Fitzgerald KC. Multiple Sclerosis Pathogenesis and Updates in Targeted Therapeutic Approaches. Curr Allergy Asthma Rep 2023; 23:481-496. [PMID: 37402064 DOI: 10.1007/s11882-023-01102-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/06/2023] [Indexed: 07/05/2023]
Abstract
PURPOSE OF REVIEW In this review, we provide a comprehensive update on current scientific advances and emerging therapeutic approaches in the field of multiple sclerosis. RECENT FINDINGS Multiple sclerosis (MS) is a common disorder characterized by inflammation and degeneration within the central nervous system (CNS). MS is the leading cause of non-traumatic disability in the young adult population. Through ongoing research, an improved understanding of the disease underlying mechanisms and contributing factors has been achieved. As a result, therapeutic advancements and interventions have been developed specifically targeting the inflammatory components that influence disease outcome. Recently, a new type of immunomodulatory treatment, known as Bruton tyrosine kinase (BTK) inhibitors, has surfaced as a promising tool to combat disease outcomes. Additionally, there is a renewed interested in Epstein-Barr virus (EBV) as a major potentiator of MS. Current research efforts are focused on addressing the gaps in our understanding of the pathogenesis of MS, particularly with respect to non-inflammatory drivers. Significant and compelling evidence suggests that the pathogenesis of MS is complex and requires a comprehensive, multilevel intervention strategy. This review aims to provide an overview of MS pathophysiology and highlights the most recent advances in disease-modifying therapies and other therapeutic interventions.
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Affiliation(s)
- Eleni S Vasileiou
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Kathryn C Fitzgerald
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA.
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17
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Magliozzi R, Howell OW, Calabrese M, Reynolds R. Meningeal inflammation as a driver of cortical grey matter pathology and clinical progression in multiple sclerosis. Nat Rev Neurol 2023:10.1038/s41582-023-00838-7. [PMID: 37400550 DOI: 10.1038/s41582-023-00838-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/07/2023] [Indexed: 07/05/2023]
Abstract
Growing evidence from cerebrospinal fluid samples and post-mortem brain tissue from individuals with multiple sclerosis (MS) and rodent models indicates that the meninges have a key role in the inflammatory and neurodegenerative mechanisms underlying progressive MS pathology. The subarachnoid space and associated perivascular spaces between the membranes of the meninges are the access points for entry of lymphocytes, monocytes and macrophages into the brain parenchyma, and the main route for diffusion of inflammatory and cytotoxic molecules from the cerebrospinal fluid into the brain tissue. In addition, the meningeal spaces act as an exit route for CNS-derived antigens, immune cells and metabolites. A number of studies have demonstrated an association between chronic meningeal inflammation and a more severe clinical course of MS, suggesting that the build-up of immune cell aggregates in the meninges represents a rational target for therapeutic intervention. Therefore, understanding the precise cell and molecular mechanisms, timing and anatomical features involved in the compartmentalization of inflammation within the meningeal spaces in MS is vital. Here, we present a detailed review and discussion of the cellular, molecular and radiological evidence for a role of meningeal inflammation in MS, alongside the clinical and therapeutic implications.
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Affiliation(s)
- Roberta Magliozzi
- Neurology Section of Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy.
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Owain W Howell
- Neurology Section of Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
- Institute of Life Sciences, Swansea University, Swansea, UK
| | - Massimiliano Calabrese
- Neurology Section of Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Richard Reynolds
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
- Centre for Molecular Neuropathology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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18
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Locus for severity implicates CNS resilience in progression of multiple sclerosis. Nature 2023; 619:323-331. [PMID: 37380766 PMCID: PMC10602210 DOI: 10.1038/s41586-023-06250-x] [Citation(s) in RCA: 49] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 05/23/2023] [Indexed: 06/30/2023]
Abstract
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that results in significant neurodegeneration in the majority of those affected and is a common cause of chronic neurological disability in young adults1,2. Here, to provide insight into the potential mechanisms involved in progression, we conducted a genome-wide association study of the age-related MS severity score in 12,584 cases and replicated our findings in a further 9,805 cases. We identified a significant association with rs10191329 in the DYSF-ZNF638 locus, the risk allele of which is associated with a shortening in the median time to requiring a walking aid of a median of 3.7 years in homozygous carriers and with increased brainstem and cortical pathology in brain tissue. We also identified suggestive association with rs149097173 in the DNM3-PIGC locus and significant heritability enrichment in CNS tissues. Mendelian randomization analyses suggested a potential protective role for higher educational attainment. In contrast to immune-driven susceptibility3, these findings suggest a key role for CNS resilience and potentially neurocognitive reserve in determining outcome in MS.
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19
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Nardi L, Schmeisser MJ, Schumann S. Fixation and staining methods for macroscopical investigation of the brain. Front Neuroanat 2023; 17:1200196. [PMID: 37426902 PMCID: PMC10323195 DOI: 10.3389/fnana.2023.1200196] [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: 04/04/2023] [Accepted: 06/09/2023] [Indexed: 07/11/2023] Open
Abstract
The proper preservation of human brain tissue is an indispensable requirement for post-mortem investigations. Neuroanatomical teaching, neuropathological examination, neurosurgical training, basic and clinical neuroscientific research are some of the possible downstream applications of brain specimens and, although much apart from one another, proper tissue fixation and preservation is a common denominator to all of them. In this review, the most relevant procedures to fixate brain tissue are described. In situ and immersion fixation approaches have been so far the most widespread ways to deliver the fixatives inside the skull. Although most of them rely on the use of formalin, alternative fixative solutions containing lower amounts of this compound mixed with other preservative agents, have been attempted. The combination of fixation and freezing paved the way for fiber dissection, particularly relevant for the neurosurgical practice and clinical neuroscience. Moreover, special techniques have been developed in neuropathology to tackle extraordinary problems, such as the examination of highly infective specimens, as in the case of the Creutzfeldt-Jakob encephalopathy, or fetal brains. Fixation is a fundamental prerequisite for further staining of brain specimens. Although several staining techniques have been developed for the microscopical investigation of the central nervous system, numerous approaches are also available for staining macroscopic brain specimens. They are mostly relevant for neuroanatomical and neuropathological teaching and can be divided in white and gray matter staining techniques. Altogether, brain fixation and staining techniques are rooted in the origins of neuroscience and continue to arouse interest in both preclinical and clinical neuroscientists also nowadays.
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Affiliation(s)
- Leonardo Nardi
- Institute of Anatomy, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Michael J. Schmeisser
- Institute of Anatomy, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
- Focus Program Translational Neurosciences, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Sven Schumann
- Institute of Anatomy, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
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20
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Nasser NS, Sharma K, Mehta PM, Mahajan V, Mahajan H, Venugopal VK. Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-multiple-sclerosis white matter hyperintensities: A pilot study among the Indian population. AIMS Neurosci 2023; 10:144-153. [PMID: 37426773 PMCID: PMC10323258 DOI: 10.3934/neuroscience.2023011] [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: 12/26/2022] [Revised: 05/03/2023] [Accepted: 05/09/2023] [Indexed: 07/11/2023] Open
Abstract
AIM Synthetic MRI (SyMRI) works on the MDME sequence, which acquires the relaxation properties of the brain and helps to measure the accurate tissue properties in 6 minutes. The aim of this study was to evaluate the synthetic MRI (SyMRI)-generated myelin (MyC) to white matter (WM) ratio, the WM fraction (WMF), MyC partial maps performing normative brain volumetry to investigate MyC loss in multiple sclerosis (MS) patients with white-matter hyperintensites (WMHs) and non-MS patients with WMHs in a clinical setting. MATERIALS and METHODS Synthetic MRI images were acquired from 15 patients with MS, and from 15 non-MS patients on a 3T MRI scanner (Discovery MR750w; GE Healthcare; Milwaukee, USA) using MAGiC, a customized version of SyntheticMR's SyMRI® IMAGE software marketed by GE Healthcare under a license agreement. Fast multi-delay multi-echo acquisition was performed with a 2D axial pulse sequence with different combinations of echo time (TEs) and saturation delay times. The total image acquisition time was 6 minutes. SyMRI image analysis was done using SyMRI software (SyMRI Version: 11.3.6; Synthetic MR, Linköping, Sweden). SyMRI data were used to generate the MyC partial maps and WMFs to quantify the signal intensities of test group and control group, andcontrol group , and their mean values were recorded. All patients also underwent conventional diffusion-weighted imaging, i.e., T1w and T2w imaging. RESULTS The results showed that the WMF was significantly lower in the test group than in the control group (38.8% vs 33.2%, p < 0.001). The Mann-Whitney U nonparametric t-test revealed a significant difference in the mean myelin volume between the test group and the control group (158.66 ± 32.31 vs. 138.29 ± 29.28, p = 0.044). Also, there were no significant differences in the gray matter fraction and intracranial volume between the test group and the control group. CONCLUSIONS We observed MyC loss in test group using quantitative SyMRI. Thus, myelin loss in MS patients can be quantitatively evaluated using SyMRI.
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21
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Martin A, Emorine T, Megdiche I, Créange A, Kober T, Massire A, Bapst B. Accurate Diagnosis of Cortical and Infratentorial Lesions in Multiple Sclerosis Using Accelerated Fluid and White Matter Suppression Imaging. Invest Radiol 2023; 58:337-345. [PMID: 36730698 DOI: 10.1097/rli.0000000000000939] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
OBJECTIVES The precise location of multiple sclerosis (MS) cortical lesions can be very challenging at 3 T, yet distinguishing them from subcortical lesions is essential for the diagnosis and prognosis of the disease. Compressed sensing-accelerated fluid and white matter suppression imaging (CS-FLAWS) is a new magnetic resonance imaging sequence derived from magnetization-prepared 2 rapid acquisition gradient echo with promising features for the detection and classification of MS lesions. The objective of this study was to compare the diagnostic performances of CS-FLAWS (evaluated imaging) and phase sensitive inversion recovery (PSIR; reference imaging) for classification of cortical lesions (primary objective) and infratentorial lesions (secondary objective) in MS, in combination with 3-dimensional (3D) double inversion recovery (DIR). MATERIALS AND METHODS Prospective 3 T scans (MS first diagnosis or follow-up) acquired between March and August 2021 were retrospectively analyzed. All underwent 3D CS-FLAWS, axial 2D PSIR, and 3D DIR. Double-blinded reading sessions exclusively in axial plane and final consensual reading were performed to assess the number of cortical and infratentorial lesions. Wilcoxon test was used to compare the 2 imaging datasets (FLAWS + DIR and PSIR + DIR), and intraobserver and interobserver agreement was assessed using the intraclass correlation coefficient. RESULTS Forty-two patients were analyzed (38 with relapsing-remitting MS, 29 women, 42.7 ± 12.6 years old). Compressed sensing-accelerated FLAWS allowed the identification of 263 cortical lesions versus 251 with PSIR ( P = 0.74) and 123 infratentorial lesions versus 109 with PSIR ( P = 0.63), corresponding to a nonsignificant difference between the 2 sequences. Compressed sensing-accelerated FLAWS exhibited fewer false-negative findings than PSIR either for cortical lesions (1 vs 13; P < 0.01) or infratentorial lesions (1 vs 15; P < 0.01). No false-positive findings were found with any of the 2 sequences. Diagnostic confidence was high for each contrast. CONCLUSION Three-dimensional CS-FLAWS is as accurate as 2D PSIR imaging for classification of cortical and infratentorial MS lesions, with fewer false-negative findings, opening the way to a reliable full brain MS exploration in a clinically acceptable duration (5 minutes 15 seconds).
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22
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Bouman PM, Noteboom S, Nobrega Santos FA, Beck ES, Bliault G, Castellaro M, Calabrese M, Chard DT, Eichinger P, Filippi M, Inglese M, Lapucci C, Marciniak A, Moraal B, Morales Pinzon A, Mühlau M, Preziosa P, Reich DS, Rocca MA, Schoonheim MM, Twisk JWR, Wiestler B, Jonkman LE, Guttmann CRG, Geurts JJG, Steenwijk MD. Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection. Radiology 2023; 307:e221425. [PMID: 36749211 PMCID: PMC10102645 DOI: 10.1148/radiol.221425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/18/2022] [Accepted: 11/28/2022] [Indexed: 02/08/2023]
Abstract
Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.
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Affiliation(s)
- Piet M. Bouman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Samantha Noteboom
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Fernando A. Nobrega Santos
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Erin S. Beck
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Gregory Bliault
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Marco Castellaro
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimiliano Calabrese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Declan T. Chard
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paul Eichinger
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimo Filippi
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Matilde Inglese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Caterina Lapucci
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Andrzej Marciniak
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Bastiaan Moraal
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Alfredo Morales Pinzon
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Mark Mühlau
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paolo Preziosa
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Daniel S. Reich
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Maria A. Rocca
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Menno M. Schoonheim
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jos W. R. Twisk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Benedict Wiestler
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Laura E. Jonkman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Charles R. G. Guttmann
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jeroen J. G. Geurts
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Martijn D. Steenwijk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
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23
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Quigley S, Yiannakas MC, Bede P, Meaney J, Kearney H. Neuropathologically informed imaging of cortical grey matter lesions in MS - A pilot study. Mult Scler Relat Disord 2023; 71:104555. [PMID: 36870314 DOI: 10.1016/j.msard.2023.104555] [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: 12/09/2022] [Revised: 01/06/2023] [Accepted: 02/05/2023] [Indexed: 02/10/2023]
Abstract
Multiple sclerosis (MS) is frequently misdiagnosed based on MRI abnormalities detected in the brain white matter. Cortical lesions have been well described neuropathologically, but remain challenging to detect in clinical practice. Therefore, the ability to detect cortical lesions offers real potential to reduce misdiagnosis. Cortical lesions have been shown to have a predilection for regions with CSF stasis - such as the insula and cingulate gyrus. This pathological observation forms the basis of our current pilot MR imaging study, which successfully uses high spatial resolution imaging of these two anatomical regions to clearly identify cortical lesions in MS.
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Affiliation(s)
- S Quigley
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | - M C Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - P Bede
- Department of Neurology, St James's Hospital, Dublin, Ireland; Computational Neuroimaging Group (CNG), TBSI, Trinity College Dublin, Ireland
| | - J Meaney
- Centre for Advanced Medical Imaging, St James's Hospital and Trinity College Dublin, Dublin, Ireland
| | - H Kearney
- Department of Neurology, St James's Hospital, Dublin, Ireland; Academic Unit of Neurology, Trinity College Dublin, Ireland.
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Yıldız Z, Doymaz F, Özden F. The reliability and validity of the Turkish version of the apraxia screen of TULIA in multiple sclerosis patients. Disabil Rehabil 2022; 44:8042-8047. [PMID: 34898347 DOI: 10.1080/09638288.2021.2003447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
PURPOSE The study was aimed to analyze the psychometric properties of the Turkish version of the Apraxia Screen of TULIA (T-AST). METHODS A total of 112 patients with multiple sclerosis (MS) were included in the study. T-AST tasks were performed once while recording with a video camera. Two physiotherapists scored T-AST, independently. Rater(1) performed a second assessment of apraxia with AST one week later. The disability was evaluated by Expanded Disability Status Scale (EDSS). Cognitive assessment was carried out with Mini-Mental State Examination (MMSE). Depression was evaluated with Hamilton Depression Rating Scale (HAM-D). Multiple Sclerosis International Quality of Life (MusiQoL) was used to assess the quality of life. In addition, fatigue was evaluated with Fatigue Severity Scale (FSS). RESULTS The mean age of the patients was 42.3 ± 11.0 years. The Cronbach's alpha coefficient of the rater(1)'s and rater(2)'s evaluation was 0.820 and 0.800, respectively. ICC score of the intra-rater reliability was 0.960. ICC score of the inter-rater reliability was 0.971. The Spearman correlation coefficients between T-AST and MMSE, EDSS, MusiQoL, HAM-D, FSS were low to excellent, respectively (r = 0.863; p < 0.001, r = -0.768; p < 0.001, r = -0.560; p < 0.001, r = -0.393, p < 0.001, r = -0.324, p < 0.001). CONCLUSION The Turkish version of the AST is a reliable and valid tool for assessing upper limb apraxia in patients with MS.Implications for RehabilitationThe Turkish version of the Apraxia Screen of TULIA (T-AST) is a reliable and valid test for assessing apraxia in patients with multiple sclerosis.Considering the short structure, high reliability, and validity, T-AST could be used in clinical practice and clinical trials.
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Affiliation(s)
- Zeynep Yıldız
- Department of Occupational Therapy, Artvin Çoruh University, Vocational School of Health Services, Artvin, Turkey
| | - Fadime Doymaz
- Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Kıbrıs İlim University, Kyrenia, North Cyprus
| | - Fatih Özden
- Elderly Care Department, Muğla Sıtkı Koçman University, Köyceğiz Vocational School of Health Services, Muğla, Turkey
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Tiu VE, Popescu BO, Enache II, Tiu C, Terecoasa E, Panea CA. Serum and CSF Biomarkers Predict Active Early Cognitive Decline Rather Than Established Cognitive Impairment at the Moment of RRMS Diagnosis. Diagnostics (Basel) 2022; 12:diagnostics12112571. [PMID: 36359416 PMCID: PMC9689215 DOI: 10.3390/diagnostics12112571] [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: 07/16/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Cognitive impairment (CI) begins early in the evolution of multiple sclerosis (MS) but may only become obvious in the later stages of the disease. Little data is available regarding predictive biomarkers for early, active cognitive decline in relapse remitting MS (RRMS) patients. (2) Methods: 50 RRMS patients in the first 6 months following diagnosis were included. The minimum follow-up was one year. Biomarker samples were collected at baseline, 3-, 6- and 12-month follow-up. Cognitive performance was assessed at baseline and 12-month follow-up; (3) Results: Statistically significant differences were found for patients undergoing active cognitive decline for sNfL z-scores at baseline and 3 months, CSF NfL baseline values, CSF Aβ42 and the Bremso score as well. The logistic regression model based on these 5 variables was statistically significant, χ2(4) = 22.335, p < 0.0001, R2 = 0.671, with a sensitivity of 57.1%, specificity of 97.4%, a positive predictive value of 80% and a negative predictive value of 92.6%. (4) Conclusions: Our study shows that serum biomarkers (adjusted sNfL z-scores at baseline and 3 months) and CSF biomarkers (CSF NfL baseline values, CSF Aβ42), combined with a clinical score (BREMSO), can accurately predict an early cognitive decline for RRMS patients at the moment of diagnosis.
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Affiliation(s)
- Vlad Eugen Tiu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Elias University Emergency Hospital, 011461 Bucharest, Romania
| | - Bogdan Ovidiu Popescu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Colentina Clinical Hospital, 020125 Bucharest, Romania
- Correspondence:
| | - Iulian Ion Enache
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Cristina Tiu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Elena Terecoasa
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Cristina Aura Panea
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Elias University Emergency Hospital, 011461 Bucharest, Romania
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26
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Barile B, Ashtari P, Stamile C, Marzullo A, Maes F, Durand-Dubief F, Van Huffel S, Sappey-Marinier D. Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome. Front Robot AI 2022; 9:926255. [PMID: 36313252 PMCID: PMC9608344 DOI: 10.3389/frobt.2022.926255] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/18/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose: The main goal of this study is to investigate the discrimination power of Grey Matter (GM) thickness connectome data between Multiple Sclerosis (MS) clinical profiles using statistical and Machine Learning (ML) methods. Materials and Methods: A dataset composed of 90 MS patients acquired at the MS clinic of Lyon Neurological Hospital was used for the analysis. Four MS profiles were considered, corresponding to Clinical Isolated Syndrome (CIS), Relapsing-Remitting MS (RRMS), Secondary Progressive MS (SPMS), and Primary Progressive MS (PPMS). Each patient was classified in one of these profiles by our neurologist and underwent longitudinal MRI examinations including T1-weighted image acquisition at each examination, from which the GM tissue was segmented and the cortical GM thickness measured. Following the GM parcellation using two different atlases (FSAverage and Glasser 2016), the morphological connectome was built and six global metrics (Betweenness Centrality (BC), Assortativity (r), Transitivity (T), Efficiency (E g ), Modularity (Q) and Density (D)) were extracted. Based on their connectivity metrics, MS profiles were first statistically compared and second, classified using four different learning machines (Logistic Regression, Random Forest, Support Vector Machine and AdaBoost), combined in a higher level ensemble model by majority voting. Finally, the impact of the GM spatial resolution on the MS clinical profiles classification was analyzed. Results: Using binary comparisons between the four MS clinical profiles, statistical differences and classification performances higher than 0.7 were observed. Good performances were obtained when comparing the two early clinical forms, RRMS and PPMS (F1 score of 0.86), and the two neurodegenerative profiles, PPMS and SPMS (F1 score of 0.72). When comparing the two atlases, slightly better performances were obtained with the Glasser 2016 atlas, especially between RRMS with PPMS (F1 score of 0.83), compared to the FSAverage atlas (F1 score of 0.69). Also, the thresholding value for graph binarization was investigated suggesting more informative graph properties in the percentile range between 0.6 and 0.8. Conclusion: An automated pipeline was proposed for the classification of MS clinical profiles using six global graph metrics extracted from the GM morphological connectome of MS patients. This work demonstrated that GM morphological connectivity data could provide good classification performances by combining four simple ML models, without the cost of long and complex MR techniques, such as MR diffusion, and/or deep learning architectures.
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Affiliation(s)
- Berardino Barile
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - Pooya Ashtari
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | | | - Aldo Marzullo
- Department of Mathematics and Computer Science, University of Calabria, Rende, Italy
| | - Frederik Maes
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - Françoise Durand-Dubief
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- Hôpital Neurologique, Service de Neurologie, Hospices Civils de Lyon, Bron, France
| | | | - Dominique Sappey-Marinier
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- CERMEP–Imagerie du Vivant, Université de Lyon, Lyon, France
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Siger M. Magnetic Resonance Imaging in Primary Progressive Multiple Sclerosis Patients : Review. Clin Neuroradiol 2022; 32:625-641. [PMID: 35258820 PMCID: PMC9424179 DOI: 10.1007/s00062-022-01144-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 11/29/2021] [Indexed: 11/21/2022]
Abstract
The recently developed effective treatment of primary progressive multiple sclerosis (PPMS) requires the accurate diagnosis of patients with this type of disease. Currently, the diagnosis of PPMS is based on the 2017 McDonald criteria, although the contribution of magnetic resonance imaging (MRI) to this process is fundamental. PPMS, one of the clinical types of MS, represents 10%-15% of all MS patients. Compared to relapsing-remitting MS (RRMS), PPMS differs in terms of pathology, clinical presentation and MRI features. Regarding conventional MRI, focal lesions on T2-weighted images and acute inflammatory lesions with contrast enhancement are less common in PPMS than in RRMS. On the other hand, MRI features of chronic inflammation, such as slowly evolving/expanding lesions (SELs) and leptomeningeal enhancement (LME), and brain and spinal cord atrophy are more common MRI characteristics in PPMS than RRMS. Nonconventional MRI also shows differences in subtle white and grey matter damage between PPMS and other clinical types of disease. In this review, we present separate diagnostic criteria, conventional and nonconventional MRI specificity for PPMS, which may support and simplify the diagnosis of this type of MS in daily clinical practice.
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Affiliation(s)
- Malgorzata Siger
- Department of Neurology, Medical University of Łódź, 22 Kopcinskiego Str., 90-153, Łódź, Poland.
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28
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Riem L, Beardsley SA, Obeidat AZ, Schmit BD. Visual oscillation effects on dynamic balance control in people with multiple sclerosis. J Neuroeng Rehabil 2022; 19:90. [PMID: 35978431 PMCID: PMC9382748 DOI: 10.1186/s12984-022-01060-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 06/15/2022] [Indexed: 12/03/2022] Open
Abstract
Background People with multiple sclerosis (PwMS) have balance deficits while ambulating through environments that contain moving objects or visual manipulations to perceived self-motion. However, their ability to parse object from self-movement has not been explored. The purpose of this research was to examine the effect of medial–lateral oscillations of the visual field and of objects within the scene on gait in PwMS and healthy age-matched controls using virtual reality (VR). Methods Fourteen PwMS (mean age 49 ± 11 years, functional gait assessment score of 27.8 ± 1.8, and Berg Balance scale score 54.7 ± 1.5) and eleven healthy controls (mean age: 53 ± 12 years) participated in this study. Dynamic balance control was assessed while participants walked on a treadmill at a self-selected speed while wearing a VR headset that projected an immersive forest scene. Visual conditions consisted of (1) no visual manipulations (speed-matched anterior/posterior optical flow), (2) 0.175 m mediolateral translational oscillations of the scene that consisted of low pairing (0.1 and 0.31 Hz) or (3) high pairing (0.15 and 0.465 Hz) frequencies, (4) 5 degree medial–lateral rotational oscillations of virtual trees at a low frequency pairing (0.1 and 0.31 Hz), and (5) a combination of the tree and scene movements in (3) and (4). Results We found that both PwMS and controls exhibited greater instability and visuomotor entrainment to simulated mediolateral translation of the visual field (scene) during treadmill walking. This was demonstrated by significant (p < 0.05) increases in mean step width and variability and center of mass sway. Visuomotor entrainment was demonstrated by high coherence between center of mass sway and visual motion (magnitude square coherence = ~ 0.5 to 0.8). Only PwMS exhibited significantly greater instability (higher step width variability and center of mass sway) when objects moved within the scene (i.e., swaying trees). Conclusion Results suggest the presence of visual motion processing errors in PwMS that reduced dynamic stability. Specifically, object motion (via tree sway) was not effectively parsed from the observer’s self-motion. Identifying this distinction between visual object motion and self-motion detection in MS provides insight regarding stability control in environments with excessive external movement, such as those encountered in daily life.
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Affiliation(s)
- Lara Riem
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, P.O. Box 1881, Milwaukee, WI, 53201-1881, USA
| | - Scott A Beardsley
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, P.O. Box 1881, Milwaukee, WI, 53201-1881, USA
| | - Ahmed Z Obeidat
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Brian D Schmit
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, P.O. Box 1881, Milwaukee, WI, 53201-1881, USA.
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29
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The Effectiveness of Physiotherapy Interventions for Mobility in Severe Multiple Sclerosis: A Systematic Review and Meta-Analysis. Mult Scler Int 2022; 2022:2357785. [PMID: 35860179 PMCID: PMC9293575 DOI: 10.1155/2022/2357785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/21/2022] [Indexed: 11/25/2022] Open
Abstract
Background People with Multiple Sclerosis (pwMS) prioritise gait as the most valuable function to be affected by MS. Physiotherapy plays a key role in managing gait impairment in MS. There is little evidence on the effectiveness of physiotherapy for severe MS. Objective To undertake a systematic review and meta-analysis of the literature to identify evidence for the effectiveness of physiotherapy for gait impairment in severe MS. Methods. The available literature was systematically searched, using a predetermined protocol, to identify research studies investigating a physiotherapy intervention for mobility in people with severe MS (EDSS ≥ 6.0). Data on mobility related endpoints was extracted. Meta-analysis was performed where a given mobility end point was reported in at least 3 studies. Results 37 relevant papers were identified, which included 788 pwMS. Seven mobility-related endpoints were meta-analysed. Robot-Assisted Gait Training (RAGT) was found to improve performance on the 6-minute walk test, 10-metre walk test, fatigue severity scale, and Berg Balance Scale. Neither body weight supported training nor conventional walking training significantly improved any mobility-related outcomes. Conclusion Physiotherapy interventions are feasible for mobility in severe MS. There is some evidence for the effectiveness of RAGT.
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30
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Bells S, Longoni G, Berenbaum T, de Medeiros CB, Narayanan S, Banwell BL, Arnold DL, Mabbott DJ, Ann Yeh E. Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders. Neuroimage Clin 2022; 34:103001. [PMID: 35381508 PMCID: PMC8980471 DOI: 10.1016/j.nicl.2022.103001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022]
Abstract
A multi-modal approach was used to evaluate the visual pathway from anterior (retina) to posterior (visual cortex) in both paediatric MOGAD and MS patients. MS patients exhibited more widespread white matter abnormalities; MOGAD patients exhibited white matter changes primarily within the optic radiation. The pattern of cortical thinning differed in MS and MOGAD patients. Reduced RNFLT was associated with lower axonal density in MOGAD and tortuosity in MS.
The impact of multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) - associated disorders (MOGAD) on brain structure in youth remains poorly understood. Reductions in cortical mantle thickness on structural MRI and abnormal diffusion-based white matter metrics (e.g., diffusion tensor parameters) have been well documented in MS but not in MOGAD. Characterizing structural abnormalities found in children with these disorders can help clarify the differences and similarities in their impact on neuroanatomy. Importantly, while MS and MOGAD affect the entire CNS, the visual pathway is of particular interest in both groups, as most patients have evidence for clinical or subclinical involvement of the anterior visual pathway. Thus, the visual pathway is of key interest in analyses of structural abnormalities in these disorders and may distinguish MOGAD from MS patients. In this study we collected MRI data on 18 MS patients, 14 MOGAD patients and 26 age- and sex-matched typically developing children (TDC). Full-brain group differences in fixel diffusion measures (fibre-bundle populations) and cortical thickness measures were tested using age and sex as covariates. Visual pathway analysis was performed by extracting mean diffusion measures within lesion free optic radiations, cortical thickness within the visual cortex, and retinal nerve fibre layer (RNFL) and ganglion cell layer thickness measures from optical coherence tomography (OCT). Fixel based analysis (FBA) revealed MS patients have widespread abnormal white matter within the corticospinal tract, inferior longitudinal fasciculus, and optic radiations, while within MOGAD patients, non-lesional impact on white matter was found primarily in the right optic radiation. Cortical thickness measures were reduced predominately in the temporal and parietal lobes in MS patients and in frontal, cingulate and visual cortices in MOGAD patients. Additionally, our findings of associations between reduced RNFLT and axonal density in MOGAD and TORT in MS patients in the optic radiations imply widespread axonal and myelin damage in the visual pathway, respectively. Overall, our approach of combining FBA, cortical thickness and OCT measures has helped evaluate similarities and differences in brain structure in MS and MOGAD patients in comparison to TDC.
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Affiliation(s)
- Sonya Bells
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Pediatric Neurology, Spectrum Health Helen Devos Children's Hospital, Grand Rapids, USA; Department of Pediatrics and Human Development, Michigan State University, East Lansing, USA
| | - Giulia Longoni
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada
| | - Tara Berenbaum
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Cynthia B de Medeiros
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Sridar Narayanan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Brenda L Banwell
- Division of Child Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, USA
| | - Douglas L Arnold
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Donald J Mabbott
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada
| | - E Ann Yeh
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada.
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31
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Zirngibl M, Assinck P, Sizov A, Caprariello AV, Plemel JR. Oligodendrocyte death and myelin loss in the cuprizone model: an updated overview of the intrinsic and extrinsic causes of cuprizone demyelination. Mol Neurodegener 2022; 17:34. [PMID: 35526004 PMCID: PMC9077942 DOI: 10.1186/s13024-022-00538-8] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 04/08/2022] [Indexed: 12/15/2022] Open
Abstract
The dietary consumption of cuprizone – a copper chelator – has long been known to induce demyelination of specific brain structures and is widely used as model of multiple sclerosis. Despite the extensive use of cuprizone, the mechanism by which it induces demyelination are still unknown. With this review we provide an updated understanding of this model, by showcasing two distinct yet overlapping modes of action for cuprizone-induced demyelination; 1) damage originating from within the oligodendrocyte, caused by mitochondrial dysfunction or reduced myelin protein synthesis. We term this mode of action ‘intrinsic cell damage’. And 2) damage to the oligodendrocyte exerted by inflammatory molecules, brain resident cells, such as oligodendrocytes, astrocytes, and microglia or peripheral immune cells – neutrophils or T-cells. We term this mode of action ‘extrinsic cellular damage’. Lastly, we summarize recent developments in research on different forms of cell death induced by cuprizone, which could add valuable insights into the mechanisms of cuprizone toxicity. With this review we hope to provide a modern understanding of cuprizone-induced demyelination to understand the causes behind the demyelination in MS.
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Affiliation(s)
- Martin Zirngibl
- Faculty of Medicine & Dentistry, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Peggy Assinck
- Wellcome Trust- MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.,Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK
| | - Anastasia Sizov
- Faculty of Medicine & Dentistry, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Andrew V Caprariello
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Cumming School of Medicine, Calgary, Canada
| | - Jason R Plemel
- Faculty of Medicine & Dentistry, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada. .,Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, Canada. .,Department of Medicine, Division of Neurology, University of Alberta, Edmonton, Canada.
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32
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Scaroni F, Visconte C, Serpente M, Golia MT, Gabrielli M, Huiskamp M, Hulst HE, Carandini T, De Riz M, Pietroboni A, Rotondo E, Scarpini E, Galimberti D, Teunissen CE, van Dam M, de Jong BA, Fenoglio C, Verderio C. miR-150-5p and let-7b-5p in Blood Myeloid Extracellular Vesicles Track Cognitive Symptoms in Patients with Multiple Sclerosis. Cells 2022; 11:cells11091551. [PMID: 35563859 PMCID: PMC9104242 DOI: 10.3390/cells11091551] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 02/04/2023] Open
Abstract
Cognitive deficits strongly affect the quality of life of patients with multiple sclerosis (MS). However, no cognitive MS biomarkers are currently available. Extracellular vesicles (EVs) contain markers of parental cells and are able to pass from the brain into blood, representing a source of disease biomarkers. The aim of this study was to investigate whether small non-coding microRNAs (miRNAs) targeting synaptic genes and packaged in plasma EVs may reflect cognitive deficits in MS patients. Total EVs were precipitated by Exoquick from the plasma of twenty-six cognitively preserved (CP) and twenty-three cognitively impaired (CI) MS patients belonging to two independent cohorts. Myeloid EVs were extracted by affinity capture from total EVs using Isolectin B4 (IB4). Fourteen miRNAs targeting synaptic genes were selected and measured by RT-PCR in both total and myeloid EVs. Myeloid EVs from CI patients expressed higher levels of miR-150-5p and lower levels of let-7b-5p compared to CP patients. Stratification for progressive MS (PMS) and relapsing-remitting MS (RRMS) and correlation with clinical parameters suggested that these alterations might be attributable to cognitive deficits rather than disease progression. This study identifies miR-150-5p and let-7b-5p packaged in blood myeloid EVs as possible biomarkers for cognitive deficits in MS.
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Affiliation(s)
- Federica Scaroni
- Institute of Neuroscience, CNR, Via Follereau 3, 20854 Vedano al Lambro, Italy; (F.S.); (M.T.G.); (M.G.)
| | - Caterina Visconte
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Via F. Sforza 35, 20122 Milan, Italy; (C.V.); (E.S.); (D.G.)
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
| | - Maria Serpente
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Maria Teresa Golia
- Institute of Neuroscience, CNR, Via Follereau 3, 20854 Vedano al Lambro, Italy; (F.S.); (M.T.G.); (M.G.)
| | - Martina Gabrielli
- Institute of Neuroscience, CNR, Via Follereau 3, 20854 Vedano al Lambro, Italy; (F.S.); (M.T.G.); (M.G.)
| | - Marijn Huiskamp
- MS Center Amsterdam, Amsterdam Neuroscience, Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam UMC, De Boelelaan 1117, 1081 Amsterdam, The Netherlands; (M.H.); (M.v.D.)
| | - Hanneke E. Hulst
- Health-, Medical- and Neuropsychology Unit, Institute of Psychology, Leiden University, 2300 Leiden, The Netherlands;
| | - Tiziana Carandini
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Milena De Riz
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Anna Pietroboni
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Emanuela Rotondo
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Elio Scarpini
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Via F. Sforza 35, 20122 Milan, Italy; (C.V.); (E.S.); (D.G.)
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Via F. Sforza 35, 20122 Milan, Italy; (C.V.); (E.S.); (D.G.)
- Centro Dino Ferrari, University of Milan, 20122 Milan, Italy; (M.S.); (T.C.); (M.D.R.); (A.P.); (E.R.)
- Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, 20122 Milan, Italy
| | - Charlotte E. Teunissen
- MS Center Amsterdam, Amsterdam Neuroscience, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 Amsterdam, The Netherlands; (C.E.T.); (B.A.d.J.)
| | - Maureen van Dam
- MS Center Amsterdam, Amsterdam Neuroscience, Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam UMC, De Boelelaan 1117, 1081 Amsterdam, The Netherlands; (M.H.); (M.v.D.)
| | - Brigit A. de Jong
- MS Center Amsterdam, Amsterdam Neuroscience, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 Amsterdam, The Netherlands; (C.E.T.); (B.A.d.J.)
| | - Chiara Fenoglio
- MS Center Amsterdam, Amsterdam Neuroscience, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 Amsterdam, The Netherlands; (C.E.T.); (B.A.d.J.)
- Department of Neuropathology and Transplantation, University of Milan, Via F. Sforza 35, 20122 Milan, Italy
- Correspondence: (C.F.); (C.V.); Tel.: +39-0264488386 (C.V.)
| | - Claudia Verderio
- Institute of Neuroscience, CNR, Via Follereau 3, 20854 Vedano al Lambro, Italy; (F.S.); (M.T.G.); (M.G.)
- Correspondence: (C.F.); (C.V.); Tel.: +39-0264488386 (C.V.)
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Carolus K, Fuchs TA, Bergsland N, Ramasamy D, Tran H, Uher T, Horakova D, Vaneckova M, Havrdova E, Benedict RHB, Zivadinov R, Dwyer MG. Time course of lesion-induced atrophy in multiple sclerosis. J Neurol 2022; 269:4478-4487. [PMID: 35394170 DOI: 10.1007/s00415-022-11094-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND PURPOSE White matter (WM) tract disruption impacts volume loss in connected deep gray matter (DGM) over 5 years in people with multiple sclerosis (PwMS). However, the timeline of this phenomenon remains poorly characterized. MATERIALS AND METHODS Annual serial MRI for 181 PwMS was retrospectively analyzed from a 10-year clinical trial database. Annualized thalamic atrophy, DGM atrophy, and disruption of connected WM tracts were measured. For time series analysis, ~700 epochs were collated using a sliding 5-year window, and regression models predicting 1-year atrophy were applied to characterize the influence of new tract disruption from preceding years, while controlling for whole brain atrophy and other relevant factors. RESULTS Disruptions of WM tracts connected to the thalamus were significantly associated with thalamic atrophy 1 year later (β: 0.048-0.103). This effect was not observed for thalamic tract disruption concurrent with the time of atrophy nor for thalamic tract disruption preceding the atrophy by 2-4 years. Similarly, disruptions of white matter tracts connected to the DGM were significantly associated with DGM atrophy 1 year later (β: 0.078-0.111), but not for tract disruption concurrent with, nor preceding the atrophy by 2-4 years. CONCLUSION Increased rates of thalamic and DGM atrophy were restricted to 1 year following newly developed disruption in connected WM tracts. In research and clinical settings, additional gray matter atrophy may be expected 1 year following new lesion growth in connected white matter.
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Affiliation(s)
- Keith Carolus
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Tom A Fuchs
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Deepa Ramasamy
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Hoan Tran
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University, General University Hospital, Prague, Czech Republic
| | - Eva Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Ralph H B Benedict
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, 100 High Street, Buffalo, NY, 14203, USA
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, 100 High Street, Buffalo, NY, 14203, USA.
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Arji G, Rezaeizadeh H, Moghadasi AN, Sahraian MA, Karimi M, Alizadeh M. Complementary and alternative therapies in multiple sclerosis: a systematic literature classification and analysis. Acta Neurol Belg 2022; 122:281-303. [PMID: 35060096 DOI: 10.1007/s13760-021-01847-3] [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: 05/09/2021] [Accepted: 12/06/2021] [Indexed: 11/25/2022]
Abstract
INTRODUCTION AND AIM Multiple Sclerosis (MS) is a disease determined by inflammatory demyelination and neurodegeneration in the Central Nervous System (CNS). Despite the extensive utilization of Complementary and Alternative Medicine (CAM) in MS, there is a need to have comprehensive evidence regarding their application in the management of MS symptoms. This manuscript is a Systematic Literature Review and classification (SLR) of CAM therapies for the management of MS symptoms based on the International Classification of Functioning Disability and Health (ICF) model. METHOD Studies published between 1990 and 2020 IN PubMed, Science Direct, Scopus, Pro-Quest, and Google Scholar using CAM therapies for the management of MS symptoms were analyzed. RESULTS Thirty-one papers on the subject were analyzed and classified. The findings of this review clearly show that mindfulness, yoga, and reflexology were frequently used for managing MS symptoms. Moreover, most of the papers used mindfulness and yoga as a CAM therapy for the management of MS symptoms, which mostly devoted to mental functions such as fatigue, depression, cognition, neuromuscular functions such as gait, muscle strength, and spasticity, and sensory function such as balance, in addition to, reflexology is vastly used to management of mental functions of MS patients. CONCLUSION Evidence suggested that CAM therapies in patients with MS have the potential to target and enhancement numerous elements outlined in the ICF model. Although the use of CAM therapies in MS symptom management is promising, there is a need for strict clinical trials. Future research direction should concentrate on methodologically powerful studies to find out the potential efficacy of CAM intervention.
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Affiliation(s)
- Goli Arji
- School of Nursing and Midwifery, Health Information Technology Department, Saveh University of Medical Sciences, Saveh, Iran
| | - Hossein Rezaeizadeh
- Department of Persian Medicine, Tehran University of Medical Science, Tehran, Iran
| | - Abdolrreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Sahraian
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mehrdad Karimi
- Department of Persian Medicine, Tehran University of Medical Science, Tehran, Iran
| | - Mojtaba Alizadeh
- Department of Computer Engineering, Lorestan University, Khorramabad, Iran.
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Bouman PM, Steenwijk MD, Geurts JJG, Jonkman LE. Artificial double inversion recovery images can substitute conventionally acquired images: an MRI-histology study. Sci Rep 2022; 12:2620. [PMID: 35173226 PMCID: PMC8850613 DOI: 10.1038/s41598-022-06546-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/28/2022] [Indexed: 11/09/2022] Open
Abstract
Cortical multiple sclerosis lesions are disease-specific, yet inconspicuous on magnetic resonance images (MRI). Double inversion recovery (DIR) images are sensitive, but often unavailable in clinical routine and clinical trials. Artificially generated images can mitigate this issue, but lack histopathological validation. In this work, artificial DIR images were generated from postmortem 3D-T1 and proton-density (PD)/T2 or 3D-T1 and 3D fluid-inversion recovery (FLAIR) images, using a generative adversarial network. All sequences were scored for cortical lesions, blinded to histopathology. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesions type I-IV (leukocortical, intracortical, subpial and cortex-spanning, respectively). Histopathological scorings were then (unblinded) compared to MRI using linear mixed models. Images from 38 patients (26 female, mean age 64.3 ± 10.7) were included. A total of 142 cortical lesions were detected, predominantly subpial. Histopathology-blinded/unblinded sensitivity was 13.4/35.2% for artificial DIR generated from T1-PD/T2, 14.1/41.5% for artificial DIR from T1-FLAIR, 17.6/49.3% for conventional DIR and 10.6/34.5% for 3D-T1. When blinded to histopathology, there were no differences; with histopathological feedback at hand, conventional DIR and artificial DIR from T1-FLAIR outperformed the other sequences. Differences between histopathology-blinded/unblinded sensitivity could be minified through adjustment of the scoring criteria. In conclusion, artificial DIR images, particularly generated from T1-FLAIR could potentially substitute conventional DIR images when these are unavailable.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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36
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Lie IA, Weeda MM, Mattiesing RM, Mol MAE, Pouwels PJW, Barkhof F, Torkildsen Ø, Bø L, Myhr KM, Vrenken H. Relationship Between White Matter Lesions and Gray Matter Atrophy in Multiple Sclerosis: A Systematic Review. Neurology 2022; 98:e1562-e1573. [PMID: 35173016 PMCID: PMC9038199 DOI: 10.1212/wnl.0000000000200006] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 01/03/2022] [Indexed: 11/20/2022] Open
Abstract
Background and Objectives There is currently no consensus about the extent of gray matter (GM) atrophy that can be attributed to secondary changes after white matter (WM) lesions or the temporal and spatial relationships between the 2 phenomena. Elucidating this interplay will broaden the understanding of the combined inflammatory and neurodegenerative pathophysiology of multiple sclerosis (MS), and separating atrophic changes due to primary and secondary neurodegenerative mechanisms will then be pivotal to properly evaluate treatment effects, especially if these treatments target the different processes individually. To untangle these complex pathologic mechanisms, this systematic review provides an essential first step: an objective and comprehensive overview of the existing in vivo knowledge of the relationship between brain WM lesions and GM atrophy in patients diagnosed with MS. The overall aim was to clarify the extent to which WM lesions are associated with both global and regional GM atrophy and how this may differ in the different disease subtypes. Methods We searched MEDLINE (through PubMed) and Embase for reports containing direct associations between brain GM and WM lesion measures obtained by conventional MRI sequences in patients with clinically isolated syndrome and MS. No restriction was applied for publication date. The quality and risk of bias in included studies were evaluated with the Quality Assessment Tool for observational cohort and cross-sectional studies (NIH, Bethesda, MA). Qualitative and descriptive analyses were performed. Results A total of 90 articles were included. WM lesion volumes were related mostly to global, cortical and deep GM volumes, and those significant associations were almost without exception negative, indicating that higher WM lesion volumes were associated with lower GM volumes or lower cortical thicknesses. The most consistent relationship between WM lesions and GM atrophy was seen in early (relapsing) disease and less so in progressive MS. Discussion The findings suggest that GM neurodegeneration is mostly secondary to damage in the WM during early disease stages while becoming more detached and dominated by other, possibly primary neurodegenerative disease mechanisms in progressive MS.
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Affiliation(s)
- Ingrid Anne Lie
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Merlin M Weeda
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Rozemarijn M Mattiesing
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Marijke A E Mol
- Medical Library, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL London, London, UK
| | - Øivind Torkildsen
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Lars Bø
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Kjell-Morten Myhr
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
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Mueller C, Baird JF, Motl RW. Whole-Brain Metabolic Abnormalities Are Associated With Mobility in Older Adults With Multiple Sclerosis. Neurorehabil Neural Repair 2022; 36:286-297. [PMID: 35164595 DOI: 10.1177/15459683221076461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Older adults with multiple sclerosis (MS) experience mobility impairments, but conventional brain imaging is a poor predictor of walking abilities in this population. OBJECTIVE To test whether brain metabolites measured with Magnetic Resonance Spectroscopy (MRS) are associated with walking performance in older adults with MS. METHODS Fifteen older adults with MS (mean age: 60.9, SD: 5.1) and 22 age-matched healthy controls (mean age: 64.2, SD: 5.7) underwent whole-brain MRS and mobility testing. Levels of N-acetylaspartate (NAA), myo-inositol (MI), choline (CHO), and temperature in 47 brain regions were compared between groups and correlated with walking speed (Timed 25 Foot Walk) and walking endurance (Six-Minute Walk). RESULTS Older adults with MS had higher MI in 23 areas, including the bilateral frontal (right: t (21.449) = -2.605, P = .016; left: t (35) = -2.434, P = .020), temporal (right: t (35) = -3.063, P = .004; left: t (35) = -3.026, P = .005), and parietal lobes (right: t (21.100) = -2.886, P = .009; left: t (35) = -2.507, P = .017), and right thalamus (t (35) = -2.840, P = .007). MI in eleven regions correlated with walking speed, and MI in twelve regions correlated with walking endurance. NAA was lower in MS in the bilateral thalami (right: t (35) = 3.449, P < .001; left: t (35) = 2.061, P = .047), caudate nuclei (right: t (33) = 2.828, P = .008; left: t (32) = 2.132, P = .041), and posterior cingulum (right: t (35) = 3.077, P = .004; left: t (35) = 2.972, P = .005). NAA in four regions correlated with walking speed and endurance. Brain temperature was higher in MS patients in four regions, but did not correlate with mobility measures. There were no group differences in CHO. CONCLUSION MI and NAA may be useful imaging end-points for walking ability as a clinical outcome in older adults with MS.
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Affiliation(s)
- Christina Mueller
- Department of Neurology, 9967University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jessica F Baird
- Department of Physical Therapy, 9968University of Alabama at Birmingham, Birmingham, AL, United States
| | - Robert W Motl
- Department of Physical Therapy, 9968University of Alabama at Birmingham, Birmingham, AL, United States
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Giurgola S, Casati C, Stampatori C, Perucca L, Mattioli F, Vallar G, Bolognini N. Abnormal multisensory integration in relapsing–remitting multiple sclerosis. Exp Brain Res 2022; 240:953-968. [PMID: 35094114 PMCID: PMC8918188 DOI: 10.1007/s00221-022-06310-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/15/2022] [Indexed: 12/22/2022]
Abstract
Temporal Binding Window (TBW) represents a reliable index of efficient multisensory integration process, which allows individuals to infer which sensory inputs from different modalities pertain to the same event. TBW alterations have been reported in some neurological and neuropsychiatric disorders and seem to negatively affects cognition and behavior. So far, it is still unknown whether deficits of multisensory integration, as indexed by an abnormal TBW, are present even in Multiple Sclerosis. We addressed this issue by testing 25 participants affected by relapsing–remitting Multiple Sclerosis (RRMS) and 30 age-matched healthy controls. Participants completed a simultaneity judgment task (SJ2) to assess the audio-visual TBW; two unimodal SJ2 versions were used as control tasks. Individuals with RRMS showed an enlarged audio-visual TBW (width range = from − 166 ms to + 198 ms), as compared to healthy controls (width range = − 177/ + 66 ms), thus showing an increased tendency to integrate temporally asynchronous visual and auditory stimuli. Instead, simultaneity perception of unimodal (visual or auditory) events overall did not differ from that of controls. These results provide first evidence of a selective deficit of multisensory integration in individuals affected by RRMS, besides the well-known motor and cognitive impairments. The reduced multisensory temporal acuity is likely caused by a disruption of the neural interplay between different sensory systems caused by multiple sclerosis.
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Affiliation(s)
- Serena Giurgola
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
| | - Carlotta Casati
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
- Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | | | - Laura Perucca
- Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Flavia Mattioli
- Neuropsychology Unit, Spedali Civili of Brescia, Brescia, Italy
| | - Giuseppe Vallar
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Nadia Bolognini
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
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Pontillo G, Penna S, Cocozza S, Quarantelli M, Gravina M, Lanzillo R, Marrone S, Costabile T, Inglese M, Morra VB, Riccio D, Elefante A, Petracca M, Sansone C, Brunetti A. Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach. Eur Radiol 2022; 32:5382-5391. [PMID: 35284989 PMCID: PMC9279232 DOI: 10.1007/s00330-022-08610-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/30/2021] [Accepted: 01/23/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVES To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived volumetric features using unsupervised machine learning. METHODS The 3-T brain MRIs of relapsing-remitting pwMS including 3D-T1w and FLAIR-T2w sequences were retrospectively collected, along with Expanded Disability Status Scale (EDSS) scores and long-term (10 ± 2 years) clinical outcomes (EDSS, cognition, and progressive course). From the MRIs, volumes of demyelinating lesions and 116 atlas-defined gray matter regions were automatically segmented and expressed as z-scores referenced to external populations. Following feature selection, baseline MRI-derived biomarkers entered the Subtype and Stage Inference (SuStaIn) algorithm, which estimates subgroups characterized by distinct patterns of biomarker evolution and stages within subgroups. The trained model was then applied to longitudinal MRIs. Stability of subtypes and stage change over time were assessed via Krippendorf's α and multilevel linear regression models, respectively. The prognostic relevance of SuStaIn classification was assessed with ordinal/logistic regression analyses. RESULTS We selected 425 pwMS (35.9 ± 9.9 years; F/M: 301/124), corresponding to 1129 MRI scans, along with healthy controls (N = 148; 35.9 ± 13.0 years; F/M: 77/71) and external pwMS (N = 80; 40.4 ± 11.9 years; F/M: 56/24) as reference populations. Based on 11 biomarkers surviving feature selection, two subtypes were identified, designated as "deep gray matter (DGM)-first" subtype (N = 238) and "cortex-first" subtype (N = 187) according to the atrophy pattern. Subtypes were consistent over time (α = 0.806), with significant annual stage increase (b = 0.20; p < 0.001). EDSS was associated with stage and DGM-first subtype (p ≤ 0.02). Baseline stage predicted long-term disability, transition to progressive course, and cognitive impairment (p ≤ 0.03), with the latter also associated with DGM-first subtype (p = 0.005). CONCLUSIONS Unsupervised learning modelling of brain MRI-derived volumetric features provides a biologically reliable and prognostically meaningful stratification of pwMS. KEY POINTS • The unsupervised modelling of brain MRI-derived volumetric features can provide a single-visit stratification of multiple sclerosis patients. • The so-obtained classification tends to be consistent over time and captures disease-related brain damage progression, supporting the biological reliability of the model. • Baseline stratification predicts long-term clinical disability, cognition, and transition to secondary progressive course.
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Affiliation(s)
- Giuseppe Pontillo
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy ,grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Simone Penna
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Mario Quarantelli
- grid.5326.20000 0001 1940 4177Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Michela Gravina
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Roberta Lanzillo
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Stefano Marrone
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Teresa Costabile
- Multiple Sclerosis Centre, II Division of Neurology, Department of Clinical and Experimental Medicine, “Luigi Vanvitelli” University, Naples, Italy
| | - Matilde Inglese
- grid.5606.50000 0001 2151 3065Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy ,grid.410345.70000 0004 1756 7871Ospedale Policlinico San Martino IRCCS, Genoa, Italy
| | - Vincenzo Brescia Morra
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Daniele Riccio
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Andrea Elefante
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Maria Petracca
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Carlo Sansone
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
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Yavari F, Oliazadeh P, Radfar M, Foroughipour M, Nikkhah K, Heidari Bakavoli A, Saeidi M. Safety and Efficacy of Fingolimod in Iranian Patients with Relapsing-remitting Multiple Sclerosis. Basic Clin Neurosci 2021; 12:233-242. [PMID: 34925720 PMCID: PMC8672667 DOI: 10.32598/bcn.12.2.1681.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 03/14/2020] [Accepted: 12/01/2020] [Indexed: 11/21/2022] Open
Abstract
Introduction: Fingolimod is the first confirmed oral immune-modulator to treat Relapsing-Remitting Multiple Sclerosis (RRMS). This study aimed to investigate the safety and efficacy of fingolimod therapy in Iranian patients with RRMS. Methods: In our trial, 50 patients resistant to conventional interferon therapy were assigned to receive fingolimod 0.5 mg per day for 12 months. The number of Dadolinium (Gd)-enhanced lesions, enlarged T2 lesions, and relapses over 12 months were considered as endpoints and compared to baseline. Liver biochemical evaluations and lymphocyte count were done at baseline and in months 3, 6, and 12 of the study. Patients were also monitored for possible cardiovascular events within the first 24 h and other side effects routinely. Results: Among the patients who completed the trial, the number of Gd-enhanced and enlarged T2 lesions over 12 months significantly decreased (P=0.03 and P<0.001, respectively). The proportion of relapse-free patients was higher compared to the onset of fingolimod administration. There were no significant alterations in the Expanded Disability Status Scale (EDSS) scores. A slight, transient increase was recorded in liver enzymes among the participants. Lymphocyte count reduced by 61% at month 1 and displayed a gradual increase until month 12. No bradycardia and macular edema were recorded. Conclusion: These findings indicate an effective first-line fingolimod therapy for the first time in Iranian patients with RRMS. The decrease in the number of new attacks and the amelioration of MRI lesions were the benefits of fingolimod therapy, suggesting that it is preferred to other medicines to treat RRMS in Iran.
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Affiliation(s)
- Fatemeh Yavari
- Department of Neurology, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Pardis Oliazadeh
- School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Meisam Radfar
- Department of Biotechnology and Plant Breeding, Gorgan University of Agricultural Sciences and Natural Recourses, Golestan, Iran
| | - Mohsen Foroughipour
- Department of Neurology, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Karim Nikkhah
- Department of Neurology, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Alireza Heidari Bakavoli
- Department of Cardiology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Morteza Saeidi
- Department of Neurology, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
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Neuroprotective Effect of Glatiramer Acetate on Neurofilament Light Chain Leakage and Glutamate Excess in an Animal Model of Multiple Sclerosis. Int J Mol Sci 2021; 22:ijms222413419. [PMID: 34948217 PMCID: PMC8707261 DOI: 10.3390/ijms222413419] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/06/2021] [Accepted: 12/09/2021] [Indexed: 11/29/2022] Open
Abstract
Axonal and neuronal pathologies are a central constituent of multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE), induced by the myelin oligodendrocyte glycoprotein (MOG) 35–55 peptide. In this study, we investigated neurodegenerative manifestations in chronic MOG 35–55 induced EAE and the effect of glatiramer acetate (GA) treatment on these manifestations. We report that the neuronal loss seen in this model is not attributed to apoptotic neuronal cell death. In EAE-affected mice, axonal damage prevails from the early disease phase, as revealed by analysis of neurofilament light (NFL) leakage into the sera along the disease duration, as well as by immunohistological examination. Elevation of interstitial glutamate concentrations measured in the cerebrospinal fluid (CSF) implies that glutamate excess plays a role in the damage processes inflicted by this disease. GA applied as a therapeutic regimen to mice with apparent clinical symptoms significantly reduces the pathological manifestations, namely apoptotic cell death, NFL leakage, histological tissue damage, and glutamate excess, thus corroborating the neuroprotective consequences of this treatment.
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42
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Cortese R, Giorgio A, Severa G, De Stefano N. MRI Prognostic Factors in Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, and Myelin Oligodendrocyte Antibody Disease. Front Neurol 2021; 12:679881. [PMID: 34867701 PMCID: PMC8636325 DOI: 10.3389/fneur.2021.679881] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 10/08/2021] [Indexed: 11/25/2022] Open
Abstract
Several MRI measures have been developed in the last couple of decades, providing a number of imaging biomarkers that can capture the complexity of the pathological processes occurring in multiple sclerosis (MS) brains. Such measures have provided more specific information on the heterogeneous pathologic substrate of MS-related tissue damage, being able to detect, and quantify the evolution of structural changes both within and outside focal lesions. In clinical practise, MRI is increasingly used in the MS field to help to assess patients during follow-up, guide treatment decisions and, importantly, predict the disease course. Moreover, the process of identifying new effective therapies for MS patients has been supported by the use of serial MRI examinations in order to sensitively detect the sub-clinical effects of disease-modifying treatments at an earlier stage than is possible using measures based on clinical disease activity. However, despite this has been largely demonstrated in the relapsing forms of MS, a poor understanding of the underlying pathologic mechanisms leading to either progression or tissue repair in MS as well as the lack of sensitive outcome measures for the progressive phases of the disease and repair therapies makes the development of effective treatments a big challenge. Finally, the role of MRI biomarkers in the monitoring of disease activity and the assessment of treatment response in other inflammatory demyelinating diseases of the central nervous system, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte antibody disease (MOGAD) is still marginal, and advanced MRI studies have shown conflicting results. Against this background, this review focused on recently developed MRI measures, which were sensitive to pathological changes, and that could best contribute in the future to provide prognostic information and monitor patients with MS and other inflammatory demyelinating diseases, in particular, NMOSD and MOGAD.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Gianmarco Severa
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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43
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Huang J, Xu J, Lai JHC, Chen Z, Lee CY, Mak HKF, Chan KH, Chan KWY. Relayed nuclear Overhauser effect weighted (rNOEw) imaging identifies multiple sclerosis. NEUROIMAGE-CLINICAL 2021; 32:102867. [PMID: 34751151 PMCID: PMC8569719 DOI: 10.1016/j.nicl.2021.102867] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 10/12/2021] [Accepted: 10/25/2021] [Indexed: 10/25/2022]
Abstract
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system in which the immune system attacks the myelin and axons, consequently leading to demyelination and axonal injury. Magnetic resonance imaging (MRI) plays a pivotal role in the diagnosis of MS, and currently various types of MRI techniques have been used to detect the pathology of MS based on unique mechanisms. In this study, we applied the relayed nuclear Overhauser effect weighted (rNOEw) imaging to study human MS at clinical 3T. Three groups of subjects, including 20 normal control (NC) subjects, 14 neuromyelitis optica spectrum disorders (NMOSD) patients and 21 MS patients, were examined at a clinical 3T MRI scanner. Whole-brain rNOEw images of each subject were obtained by acquiring a control and a labeled image within four minutes. Significantly lower brain rNOEw contrast was detected in MS group compared to NC (P = 0.008) and NMOSD (P = 0.014) groups, while no significant difference was found between NC and NMOSD groups (P = 0.939). The lower rNOEw contrast of MS group compared to NC/NMOSD group was significant in white matter (P = 0.041/0.021), gray matter (P = 0.004/0.020) and brain parenchyma (P = 0.015/0.021). Moreover, MS lesions showed higher number and larger size but lower rNOEw contrast than NMOSD lesions (P = 0.002). Our proposed rNOEw imaging scheme has potential to serve as a new method for assisting MS diagnosis. Importantly, it may be used to identify MS from NMOSD.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joseph H C Lai
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Zilin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Chi Yan Lee
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Henry K F Mak
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Koon Ho Chan
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Kannie W Y Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; City University of Hong Kong Shenzhen Research Institute, Shenzhen, China; Hong Kong Centre for Cerebro-Cardiovascular Health Engineering, Hong Kong, China.
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44
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Nucleic Acids as Novel Therapeutic Modalities to Address Multiple Sclerosis Onset and Progression. Cell Mol Neurobiol 2021; 42:2611-2627. [PMID: 34694513 DOI: 10.1007/s10571-021-01158-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 10/17/2021] [Indexed: 02/07/2023]
Abstract
The issue of treating Multiple Sclerosis (MS) begins with disease-modifying treatments (DMTs) which may cause lymphopenia, dyspnea, and many other adverse effects. Consequently, further identification and evaluation of alternative treatments are crucial to monitoring their long-term outcomes and hopefully, moving toward personalized approaches that can be translated into clinical treatments. In this article, we focused on the novel therapeutic modalities that alter the interaction between the cellular constituents contributing to MS onset and progression. Furthermore, the studies that have been performed to evaluate and optimize drugs' efficacy, and particularly, to show their limitations and strengths are also presented. The preclinical trials of novel approaches for multiple sclerosis treatment provide promising prospects to cure the disease with pinpoint precision. Considering the fact that not a single treatment could be effective enough to cover all aspects of MS treatment, additional researches and therapies need to be developed in the future. Since the pathophysiology of MS resembles a jigsaw puzzle, researchers need to put a host of pieces together to create a promising window towards MS treatment. Thus, a combination therapy encompassing all these modules is highly likely to succeed in dealing with the disease. The use of different therapeutic approaches to re-induce self-tolerance in autoreactive cells contributing to MS pathogenesis is presented. A Combination therapy using these tools may help to deal with the clinical disabilities and symptoms of the disease in the future.
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Rayatpour A, Farhangi S, Verdaguer E, Olloquequi J, Ureña J, Auladell C, Javan M. The Cross Talk between Underlying Mechanisms of Multiple Sclerosis and Epilepsy May Provide New Insights for More Efficient Therapies. Pharmaceuticals (Basel) 2021; 14:ph14101031. [PMID: 34681255 PMCID: PMC8541630 DOI: 10.3390/ph14101031] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 12/17/2022] Open
Abstract
Despite the significant differences in pathological background of neurodegenerative diseases, epileptic seizures are a comorbidity in many disorders such as Huntington disease (HD), Alzheimer's disease (AD), and multiple sclerosis (MS). Regarding the last one, specifically, it has been shown that the risk of developing epilepsy is three to six times higher in patients with MS compared to the general population. In this context, understanding the pathological processes underlying this connection will allow for the targeting of the common and shared pathological pathways involved in both conditions, which may provide a new avenue in the management of neurological disorders. This review provides an outlook of what is known so far about the bidirectional association between epilepsy and MS.
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Affiliation(s)
- Atefeh Rayatpour
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran 14117-13116, Iran; (A.R.); (S.F.)
- Institute for Brain and Cognition, Tarbiat Modares University, Tehran 14117-13116, Iran
| | - Sahar Farhangi
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran 14117-13116, Iran; (A.R.); (S.F.)
- Institute for Brain and Cognition, Tarbiat Modares University, Tehran 14117-13116, Iran
| | - Ester Verdaguer
- Department of Cell Biology, Physiology and Immunology, Biology Faculty, Universitat de Barcelona, 08028 Barcelona, Spain; (E.V.); (J.U.)
- Centre for Biomedical Research of Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035 Barcelona, Spain
| | - Jordi Olloquequi
- Laboratory of Cellular and Molecular Pathology, Biomedical Sciences Institute, Health Sciences Faculty, Universidad Autónoma de Chile, Talca 3460000, Chile;
| | - Jesus Ureña
- Department of Cell Biology, Physiology and Immunology, Biology Faculty, Universitat de Barcelona, 08028 Barcelona, Spain; (E.V.); (J.U.)
- Centre for Biomedical Research of Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035 Barcelona, Spain
| | - Carme Auladell
- Department of Cell Biology, Physiology and Immunology, Biology Faculty, Universitat de Barcelona, 08028 Barcelona, Spain; (E.V.); (J.U.)
- Centre for Biomedical Research of Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035 Barcelona, Spain
- Correspondence: (C.A.); (M.J.)
| | - Mohammad Javan
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran 14117-13116, Iran; (A.R.); (S.F.)
- Institute for Brain and Cognition, Tarbiat Modares University, Tehran 14117-13116, Iran
- Cell Science Research Center, Department of Brain and Cognitive Sciences, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran 14117-13116, Iran
- Correspondence: (C.A.); (M.J.)
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Bussas M, Grahl S, Pongratz V, Berthele A, Gasperi C, Andlauer T, Gaser C, Kirschke JS, Wiestler B, Zimmer C, Hemmer B, Mühlau M. Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers. Mult Scler 2021; 28:900-909. [PMID: 34591698 PMCID: PMC9024016 DOI: 10.1177/13524585211044957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Lesions of brain white matter (WM) and atrophy of brain gray matter (GM) are well-established surrogate parameters in multiple sclerosis (MS), but it is unclear how closely these parameters relate to each other. Objective: To assess across the whole cerebrum whether GM atrophy can be explained by lesions in connecting WM tracts. Methods: GM images of 600 patients with relapsing-remitting MS (women = 68%; median age = 33.0 years, median expanded disability status scale score = 1.5) were converted to atrophy maps by data from a healthy control cohort. An atlas of WM tracts from the Human Connectome Project and individual lesion maps were merged to identify potentially disconnected GM regions, leading to individual disconnectome maps. Across the whole cerebrum, GM atrophy and potentially disconnected GM were tested for association both cross-sectionally and longitudinally. Results: We found highly significant correlations between disconnection and atrophy across most of the cerebrum. Longitudinal analysis demonstrated a close temporal relation of WM lesion formation and GM atrophy in connecting fibers. Conclusion: GM atrophy is associated with WM lesions in connecting fibers. Caution is warranted when interpreting group differences in GM atrophy exclusively as differences in early neurodegeneration independent of WM lesion formation.
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Affiliation(s)
- Matthias Bussas
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Grahl
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christiane Gasperi
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Till Andlauer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry and Department of Neurology, Jena University Hospital, Jena, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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47
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Khan H, Sami MB, Litvak V. The utility of Magnetoencephalography in multiple sclerosis - A systematic review. NEUROIMAGE-CLINICAL 2021; 32:102814. [PMID: 34537682 PMCID: PMC8455859 DOI: 10.1016/j.nicl.2021.102814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 01/29/2023]
Abstract
We conducted a Systematic Review of studies, looking at 30 studies from 13 centres. MS patients had reduced power in some induced responses (motor beta, visual gamma). Increased latency and reduced connectivity were seen for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive function. MEG shows promise, although work is too preliminary to recommend current clinical use.
Introduction Magnetoencephalography (MEG), allows for a high degree temporal and spatial accuracy in recording cortical oscillatory activity and evoked fields. To date, no review has been undertaken to synthesise all MEG studies in Multiple Sclerosis (MS). We undertook a Systematic Review of the utility of MEG in MS. Methods We identified MEG studies carried out in MS using EMBASE, Medline, Cochrane, TRIP and Psychinfo databases. We included original research articles with a cohort of minimum of five multiple sclerosis patients and quantifying of at least one MEG parameter. We used a modified version of the JBI (mJBI) for case-control studies to assess for risk of bias. Results We identified 30 studies from 13 centres involving at least 433 MS patients and 347 controls. We found evidence that MEG shows perturbed activity (most commonly reduced power modulations), reduced connectivity and association with altered clinical function in Multiple Sclerosis. Specific replicated findings were decreased motor induced responses in the beta band, diminished increase of gamma power after visual stimulation, increased latency and reduced connectivity for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive measures in people with MS. Overall studies were of moderate quality (mean mJBI score 6.7). Discussion We find evidence for the utility of MEG in Multiple Sclerosis. Event-related designs are of particular value and show replicability between centres. At this stage, it is not clear whether these changes are specific to Multiple Sclerosis or are also observable in other diseases. Further studies should look to explore cognitive control in more depth using in-task designs and undertake longitudinal studies to determine whether these changes have prognostic value.
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Affiliation(s)
- H Khan
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom; Queen's Medical Centre Nottingham, Clifton Boulevard, Derby Rd, Nottingham NG7 2UH, United Kingdom.
| | - M B Sami
- Institute of Mental Health, Jubilee Campus, University of Nottingham Innovation Park, Triumph Road, Nottingham NG7 2TU, United Kingdom
| | - V Litvak
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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48
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De Vito F, Musella A, Fresegna D, Rizzo FR, Gentile A, Stampanoni Bassi M, Gilio L, Buttari F, Procaccini C, Colamatteo A, Bullitta S, Guadalupi L, Caioli S, Vanni V, Balletta S, Sanna K, Bruno A, Dolcetti E, Furlan R, Finardi A, Licursi V, Drulovic J, Pekmezovic T, Fusco C, Bruzzaniti S, Hornstein E, Uccelli A, Salvetti M, Matarese G, Centonze D, Mandolesi G. MiR-142-3p regulates synaptopathy-driven disease progression in multiple sclerosis. Neuropathol Appl Neurobiol 2021; 48:e12765. [PMID: 34490928 PMCID: PMC9291627 DOI: 10.1111/nan.12765] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 08/11/2021] [Accepted: 08/15/2021] [Indexed: 11/30/2022]
Abstract
Aim We recently proposed miR‐142‐3p as a molecular player in inflammatory synaptopathy, a new pathogenic hallmark of multiple sclerosis (MS) and of its mouse model experimental autoimmune encephalomyelitis (EAE), that leads to neuronal loss independently of demyelination. MiR‐142‐3p seems to be unique among potential biomarker candidates in MS, since it is an inflammatory miRNA playing a dual role in the immune and central nervous systems. Here, we aimed to verify the impact of miR‐142‐3p circulating in the cerebrospinal fluid (CSF) of MS patients on clinical parameters, neuronal excitability and its potential interaction with disease modifying therapies (DMTs). Methods and Results In a cohort of 151 MS patients, we found positive correlations between CSF miR‐142‐3p levels and clinical progression, IL‐1β signalling as well as synaptic excitability measured by transcranial magnetic stimulation. Furthermore, therapy response of patients with ‘low miR‐142‐3p’ to dimethyl fumarate (DMF), an established disease‐modifying treatment (DMT), was superior to that of patients with ‘high miR‐142‐3p’ levels. Accordingly, the EAE clinical course of heterozygous miR‐142 mice was ameliorated by peripheral DMF treatment with a greater impact relative to their wild type littermates. In addition, a central protective effect of this drug was observed following intracerebroventricular and ex vivo acute treatments of EAE wild type mice, showing a rescue of miR‐142‐3p‐dependent glutamatergic alterations. By means of electrophysiology, molecular and biochemical analysis, we suggest miR‐142‐3p as a molecular target of DMF. Conclusion MiR‐142‐3p is a novel and potential negative prognostic CSF marker of MS and a promising tool for identifying personalised therapies.
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Affiliation(s)
| | - Alessandra Musella
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy.,Department of Human Sciences and Quality of Life Promotion, University of Rome, San Raffaele, Italy
| | - Diego Fresegna
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy
| | | | | | | | - Luana Gilio
- Unit of Neurology, IRCCS Neuromed, Pozzilli, Italy
| | | | - Claudio Procaccini
- Laboratorio di Immunologia, Istituto per l'Endocrinologia e l'Oncologia Sperimentale "G. Salvatore", Consiglio Nazionale delle Ricerche, Naples, Italy.,Unit of Neuroimmunology, IRCCS-Fondazione Santa Lucia, Rome, Italy
| | - Alessandra Colamatteo
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli "Federico II", Naples, Italy
| | - Silvia Bullitta
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Livia Guadalupi
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | | | - Valentina Vanni
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Sara Balletta
- Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Krizia Sanna
- Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Antonio Bruno
- Unit of Neurology, IRCCS Neuromed, Pozzilli, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Ettore Dolcetti
- Unit of Neurology, IRCCS Neuromed, Pozzilli, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Roberto Furlan
- Neuroimmunology Unit, Institute of Experimental Neurology (INSpe), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Annamaria Finardi
- Neuroimmunology Unit, Institute of Experimental Neurology (INSpe), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Valerio Licursi
- Department of Biology and Biotechnologies "C. Darwin," Laboratory of Functional Genomics and Proteomics of Model Systems, University of Rome "Sapienza", Rome, Italy
| | - Jelena Drulovic
- Clinic of Neurology, Clinical Center of Serbia, Belgrade, Serbia.,Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Tatjana Pekmezovic
- Faculty of Medicine, Institute of Epidemiology, University of Belgrade, Belgrade, Serbia
| | - Clorinda Fusco
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli "Federico II", Naples, Italy
| | - Sara Bruzzaniti
- Laboratorio di Immunologia, Istituto per l'Endocrinologia e l'Oncologia Sperimentale "G. Salvatore", Consiglio Nazionale delle Ricerche, Naples, Italy.,Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli "Federico II", Naples, Italy
| | - Eran Hornstein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Antonio Uccelli
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health Unit and Center of Excellence for Biomedical Research, University of Genova, Genoa, Italy.,IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Marco Salvetti
- Unit of Neurology, IRCCS Neuromed, Pozzilli, Italy.,Center for Experimental Neurological Therapies, Sant'Andrea Hospital, Department of Neurosciences, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Giuseppe Matarese
- Laboratorio di Immunologia, Istituto per l'Endocrinologia e l'Oncologia Sperimentale "G. Salvatore", Consiglio Nazionale delle Ricerche, Naples, Italy.,Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli "Federico II", Naples, Italy
| | - Diego Centonze
- Unit of Neurology, IRCCS Neuromed, Pozzilli, Italy.,Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Georgia Mandolesi
- Synaptic Immunopathology Lab, IRCCS San Raffaele Roma, Italy.,Department of Human Sciences and Quality of Life Promotion, University of Rome, San Raffaele, Italy
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49
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van Wageningen TA, Gerrits E, Palacin I Bonson S, Huitinga I, Eggen BJL, van Dam AM. Exploring reported genes of microglia RNA-sequencing data: Uses and considerations. Glia 2021; 69:2933-2946. [PMID: 34409652 PMCID: PMC9291850 DOI: 10.1002/glia.24078] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 01/16/2023]
Abstract
The advent of RNA‐sequencing techniques has made it possible to generate large, unbiased gene expression datasets of tissues and cell types. Several studies describing gene expression data of microglia from Alzheimer's disease or multiple sclerosis have been published, aiming to generate more insight into the role of microglia in these neurological diseases. Though the raw sequencing data are often deposited in open access databases, the most accessible source of data for scientists is what is reported in published manuscripts. We observed a relatively limited overlap in reported differentially expressed genes between various microglia RNA‐sequencing studies from multiple sclerosis or Alzheimer's diseases. It was clear that differences in experimental set up influenced the number of overlapping reported genes. However, even when the experimental set up was very similar, we observed that overlap in reported genes could be low. We identified that papers reporting large numbers of differentially expressed microglial genes generally showed higher overlap with other papers. In addition, though the pathology present within the tissue used for sequencing can greatly influence microglia gene expression, often the pathology present in samples used for sequencing was underreported, leaving it difficult to assess the data. Whereas reanalyzing every raw dataset could reduce the variation that contributes to the observed limited overlap in reported genes, this is not feasible for labs without (access to) bioinformatic expertise. In this study, we thus provide an overview of data present in manuscripts and their supplementary files and how these data can be interpreted.
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Affiliation(s)
- Thecla A van Wageningen
- Department Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Emma Gerrits
- Department of Biomedical Sciences of Cells & Systems, section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Sara Palacin I Bonson
- Department Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Inge Huitinga
- Neuroimmunology Research Group, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
| | - Bart J L Eggen
- Department of Biomedical Sciences of Cells & Systems, section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Anne-Marie van Dam
- Department Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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50
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Bouman PM, Strijbis VI, Jonkman LE, Hulst HE, Geurts JJ, Steenwijk MD. Artificial double inversion recovery images for (juxta)cortical lesion visualization in multiple sclerosis. Mult Scler 2021; 28:541-549. [PMID: 34259591 PMCID: PMC8961242 DOI: 10.1177/13524585211029860] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Background: Cortical lesions are highly inconspicuous on magnetic resonance imaging
(MRI). Double inversion recovery (DIR) has a higher sensitivity than
conventional clinical sequences (i.e. T1, T2, FLAIR) but is difficult to
acquire, leading to overseen cortical lesions in clinical care and clinical
trials. Objective: To evaluate the usability of artificially generated DIR (aDIR) images for
cortical lesion detection compared to conventionally acquired DIR
(cDIR). Methods: The dataset consisted of 3D-T1 and 2D-proton density (PD) T2 images of 73
patients (49RR, 20SP, 4PP) at 1.5 T. Using a 4:1 train:test-ratio, a fully
convolutional neural network was trained to predict 3D-aDIR from 3D-T1 and
2D-PD/T2 images. Randomized blind scoring of the test set was used to
determine detection reliability, precision and recall. Results: A total of 626 vs 696 cortical lesions were detected on 15 aDIR vs cDIR
images (intraclass correlation coefficient (ICC) = 0.92). Compared to cDIR,
precision and recall were 0.84 ± 0.06 and 0.76 ± 0.09, respectively. The
frontal and temporal lobes showed the largest differences in
discernibility. Conclusion: Cortical lesions can be detected with good reliability on artificial DIR. The
technique has potential to broaden the availability of DIR in clinical care
and provides the opportunity of ex post facto implementation of cortical
lesions imaging in existing clinical trial data.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Victor Ij Strijbis
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen Jg Geurts
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy & Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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