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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 PMCID: PMC11409727 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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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; 66:1709-1719. [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] [MESH Headings] [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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Comi G, Dalla Costa G, Stankoff B, Hartung HP, Soelberg Sørensen P, Vermersch P, Leocani L. Assessing disease progression and treatment response in progressive multiple sclerosis. Nat Rev Neurol 2024:10.1038/s41582-024-01006-1. [PMID: 39251843 DOI: 10.1038/s41582-024-01006-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/30/2024] [Indexed: 09/11/2024]
Abstract
Progressive multiple sclerosis poses a considerable challenge in the evaluation of disease progression and treatment response owing to its multifaceted pathophysiology. Traditional clinical measures such as the Expanded Disability Status Scale are limited in capturing the full scope of disease and treatment effects. Advanced imaging techniques, including MRI and PET scans, have emerged as valuable tools for the assessment of neurodegenerative processes, including the respective role of adaptive and innate immunity, detailed insights into brain and spinal cord atrophy, lesion dynamics and grey matter damage. The potential of cerebrospinal fluid and blood biomarkers is increasingly recognized, with neurofilament light chain levels being a notable indicator of neuro-axonal damage. Moreover, patient-reported outcomes are crucial for reflecting the subjective experience of disease progression and treatment efficacy, covering aspects such as fatigue, cognitive function and overall quality of life. The future incorporation of digital technologies and wearable devices in research and clinical practice promises to enhance our understanding of functional impairments and disease progression. This Review offers a comprehensive examination of these diverse evaluation tools, highlighting their combined use in accurately assessing disease progression and treatment efficacy in progressive multiple sclerosis, thereby guiding more effective therapeutic strategies.
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Affiliation(s)
- Giancarlo Comi
- Department of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
| | | | - Bruno Stankoff
- Sorbonne Université, Paris Brain Institute, Institut du Cerveau et de la Moelle Épinière, Centre National de la Recherche Scientifique, Inserm, Paris, France
| | - Hans-Peter Hartung
- Brain and Mind Center, University of Sydney, Sydney, Australia
- Department of Neurology, Palacky University Olomouc, Olomouc, Czech Republic
- Department of Neurology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Per Soelberg Sørensen
- Department of Neurology, Danish Multiple Sclerosis Center, University of Copenhagen, Rigshospitalet, Copenhagen, Denmark
| | - Patrick Vermersch
- University of Lille, Inserm U1172, Lille Neuroscience & Cognition, Centre Hospitalier Universitaire de Lille, Fédération Hospitalo-Universitaire Precision Medicine in Psychiatry, Lille, France
| | - Letizia Leocani
- Vita-Salute San Raffaele University, Milan, Italy
- Multiple Sclerosis Center, Casa di Cura Igea, Milan, Italy
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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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Bianchi A, Cortese R, Prados F, Tur C, Kanber B, Yiannakas MC, Samson R, De Angelis F, Magnollay L, Jacob A, Brownlee W, Trip A, Nicholas R, Hacohen Y, Barkhof F, Ciccarelli O, Toosy AT. Optic chiasm involvement in multiple sclerosis, aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein-associated disease. Mult Scler 2024; 30:674-686. [PMID: 38646958 PMCID: PMC11103893 DOI: 10.1177/13524585241240420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/27/2024] [Accepted: 03/01/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Optic neuritis (ON) is a common feature of inflammatory demyelinating diseases (IDDs) such as multiple sclerosis (MS), aquaporin 4-antibody neuromyelitis optica spectrum disorder (AQP4 + NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). However, the involvement of the optic chiasm (OC) in IDD has not been fully investigated. AIMS To examine OC differences in non-acute IDD patients with (ON+) and without ON (ON-) using magnetisation transfer ratio (MTR), to compare differences between MS, AQP4 + NMOSD and MOGAD and understand their associations with other neuro-ophthalmological markers. METHODS Twenty-eight relapsing-remitting multiple sclerosis (RRMS), 24 AQP4 + NMOSD, 28 MOGAD patients and 32 healthy controls (HCs) underwent clinical evaluation, MRI and optical coherence tomography (OCT) scan. Multivariable linear regression models were applied. RESULTS ON + IDD patients showed lower OC MTR than HCs (28.87 ± 4.58 vs 31.65 ± 4.93; p = 0.004). When compared with HCs, lower OC MTR was found in ON + AQP4 + NMOSD (28.55 ± 4.18 vs 31.65 ± 4.93; p = 0.020) and MOGAD (28.73 ± 4.99 vs 31.65 ± 4.93; p = 0.007) and in ON- AQP4 + NMOSD (28.37 ± 7.27 vs 31.65 ± 4.93; p = 0.035). ON+ RRMS had lower MTR than ON- RRMS (28.87 ± 4.58 vs 30.99 ± 4.76; p = 0.038). Lower OC MTR was associated with higher number of ON (regression coefficient (RC) = -1.15, 95% confidence interval (CI) = -1.819 to -0.490, p = 0.001), worse visual acuity (RC = -0.026, 95% CI = -0.041 to -0.011, p = 0.001) and lower peripapillary retinal nerve fibre layer (pRNFL) thickness (RC = 1.129, 95% CI = 0.199 to 2.059, p = 0.018) when considering the whole IDD group. CONCLUSION OC microstructural damage indicates prior ON in IDD and is linked to reduced vision and thinner pRNFL.
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Affiliation(s)
- Alessia Bianchi
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Rosa Cortese
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Ferran Prados
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
- eHealth Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Carmen Tur
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- MS Centre of Catalonia (Cemcat), Vall d’Hebron Institute of Research, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Baris Kanber
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marios C Yiannakas
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Rebecca Samson
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Floriana De Angelis
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Lise Magnollay
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Anu Jacob
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, UK
- Department of Neurology, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Wallace Brownlee
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Anand Trip
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Richard Nicholas
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Yael Hacohen
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Neurology, Great Ormond Street Hospital For Children NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Ahmed T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
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6
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Lazzarotto A, Hamzaoui M, Tonietto M, Dubessy AL, Khalil M, Pirpamer L, Ropele S, Enzinger C, Battaglini M, Stromillo ML, De Stefano N, Filippi M, Rocca MA, Gallo P, Gasperini C, Stankoff B, Bodini B. Time is myelin: early cortical myelin repair prevents atrophy and clinical progression in multiple sclerosis. Brain 2024; 147:1331-1343. [PMID: 38267729 PMCID: PMC10994569 DOI: 10.1093/brain/awae024] [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: 07/07/2023] [Revised: 12/15/2023] [Accepted: 01/13/2024] [Indexed: 01/26/2024] Open
Abstract
Cortical myelin loss and repair in multiple sclerosis (MS) have been explored in neuropathological studies, but the impact of these processes on neurodegeneration and the irreversible clinical progression of the disease remains unknown. Here, we evaluated in vivo cortical demyelination and remyelination in a large cohort of people with all clinical phenotypes of MS followed up for 5 years using magnetization transfer imaging (MTI), a technique that has been shown to be sensitive to myelin content changes in the cortex. We investigated 140 people with MS (37 clinically isolated syndrome, 71 relapsing-MS, 32 progressive-MS), who were clinically assessed at baseline and after 5 years and, along with 84 healthy controls, underwent a 3 T-MRI protocol including MTI at baseline and after 1 year. Changes in cortical volume over the radiological follow-up were computed with a Jacobian integration method. Magnetization transfer ratio was employed to calculate for each patient an index of cortical demyelination at baseline and of dynamic cortical demyelination and remyelination over the follow-up period. The three indices of cortical myelin content change were heterogeneous across patients but did not significantly differ across clinical phenotypes or treatment groups. Cortical remyelination, which tended to fail in the regions closer to CSF (-11%, P < 0.001), was extensive in half of the cohort and occurred independently of age, disease duration and clinical phenotype. Higher indices of cortical dynamic demyelination (β = 0.23, P = 0.024) and lower indices of cortical remyelination (β = -0.18, P = 0.03) were significantly associated with greater cortical atrophy after 1 year, independently of age and MS phenotype. While the extent of cortical demyelination predicted a higher probability of clinical progression after 5 years in the entire cohort [odds ratio (OR) = 1.2; P = 0.043], the impact of cortical remyelination in reducing the risk of accumulating clinical disability after 5 years was significant only in the subgroup of patients with shorter disease duration and limited extent of demyelination in cortical regions (OR = 0.86, P = 0.015, area under the curve = 0.93). In this subgroup, a 30% increase in cortical remyelination nearly halved the risk of clinical progression at 5 years, independently of clinical relapses. Overall, our results highlight the critical role of cortical myelin dynamics in the cascade of events leading to neurodegeneration and to the subsequent accumulation of irreversible disability in MS. Our findings suggest that early-stage myelin repair compensating for cortical myelin loss has the potential to prevent neuro-axonal loss and its long-term irreversible clinical consequences in people with MS.
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Affiliation(s)
- Andrea Lazzarotto
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
- Padova Neuroscience Center, University of Padua, 35122 Padua, Italy
| | - Mariem Hamzaoui
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
| | - Matteo Tonietto
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, 91400 Orsay, France
- Roche Pharma Research & Early Development, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland
| | | | - Michael Khalil
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
- Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, CH-4051 Basel, Switzerland
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | | | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Maria Laura Stromillo
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Paolo Gallo
- Padova Neuroscience Center, University of Padua, 35122 Padua, Italy
- Multiple Sclerosis Centre of Veneto Region, 35128 Padua, Italy
| | | | - Bruno Stankoff
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
| | - Benedetta Bodini
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
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7
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Preisner F, Pitarokoili K, Lueling B, Motte J, Fisse AL, Grüter T, Godel T, Schwarz D, Heiland S, Gold R, Bendszus M, Kronlage M. Quantitative magnetic resonance neurography in chronic inflammatory demyelinating polyradiculoneuropathy: A longitudinal study over 6 years. Ann Clin Transl Neurol 2024; 11:593-606. [PMID: 38111964 DOI: 10.1002/acn3.51978] [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: 09/09/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 12/20/2023] Open
Abstract
OBJECTIVE To evaluate magnetic resonance neurography (MRN) for the longitudinal assessment of patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). METHODS Prospective examination of twelve CIDP patients by neurological assessment, MRN, and nerve conduction studies in 2016 and 6 years later in 2022. Imaging parameters were compared with matched healthy controls and correlated with clinical and electrophysiological markers. The MRN protocol included T2-weighted imaging, diffusion tensor imaging (DTI), T2 relaxometry, and magnetization transfer imaging (MTI). RESULTS Nerve cross-sectional area (CSA) was increased in CIDP patients compared to controls (plexus: p = 0.003; sciatic nerve: p < 0.001). Over 6 years, nerve CSA decreased in CIDP patients, most pronounced at the lumbosacral plexus (p = 0.015). Longitudinally, changes in CSA correlated with changes in the inflammatory neuropathy cause and treatment validated overall disability sum score (INCAT/ODSS) (p = 0.006). High initial nerve CSA was inversely correlated with changes in the INCAT/ODSS over 6 years (p < 0.05). The DTI parameter fractional anisotropy (FA) showed robust correlations with electrodiagnostic testing both cross-sectionally and longitudinally (p < 0.05). MTI as a newly added imaging technique revealed a significantly reduced magnetization transfer ratio (MTR) in CIDP patients (p < 0.01), suggesting underlying changes in macromolecular tissue composition, and correlated significantly with electrophysiological parameters of demyelination (p < 0.05). INTERPRETATION This study provides evidence that changes in nerve CSA and FA reflect the clinical and electrophysiological course of CIDP patients. Initial nerve hypertrophy might predict a rather benign course or better therapy response.
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Affiliation(s)
- Fabian Preisner
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Kalliopi Pitarokoili
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Benjamin Lueling
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Jeremias Motte
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Anna Lena Fisse
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Thomas Grüter
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Tim Godel
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Daniel Schwarz
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef Hospital, Ruhr University of Bochum, 44791, Bochum, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Moritz Kronlage
- Department of Neuroradiology, Neurological Clinic, Heidelberg University Hospital, 69120, Heidelberg, Germany
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8
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Gloor M, Andelova M, Gaetano L, Papadopoulou A, Burguet Villena F, Sprenger T, Radue EW, Kappos L, Bieri O, Garcia M. Longitudinal analysis of new multiple sclerosis lesions with magnetization transfer and diffusion tensor imaging. Eur Radiol 2024; 34:1680-1691. [PMID: 37658894 PMCID: PMC10873225 DOI: 10.1007/s00330-023-10173-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/02/2023] [Accepted: 07/12/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVE The potential of magnetization transfer imaging (MTI) and diffusion tensor imaging (DTI) for the detection and evolution of new multiple sclerosis (MS) lesions was analyzed. METHODS Nineteen patients with MS obtained conventional MRI, MTI, and DTI examinations bimonthly for 12 months and again after 24 months at 1.5 T MRI. MTI was acquired with balanced steady-state free precession (bSSFP) in 10 min (1.3 mm3 isotropic resolution) yielding both magnetization transfer ratio (MTR) and quantitative magnetization transfer (qMT) parameters (pool size ratio (F), exchange rate (kf), and relaxation times (T1/T2)). DTI provided fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). RESULTS At the time of their appearance on MRI, the 21 newly detected MS lesions showed significantly reduced MTR/F/kf and prolonged T1/T2 parameters, as well as significantly reduced FA and increased AD/MD/RD. Significant differences were already observed for MTR 4 months and for qMT parameters 2 months prior to lesions' detection on MRI. DTI did not show any significant pre-lesional differences. Slightly reversed trends were observed for most lesions up to 8 months after their detection for qMT and less pronounced for MTR and three diffusion parameters, while appearing unchanged on MRI. CONCLUSIONS MTI provides more information than DTI in MS lesions and detects tissue changes 2 to 4 months prior to their appearance on MRI. After lesions' detection, qMT parameter changes promise to be more sensitive than MTR for the lesions' evolutional assessment. Overall, bSSFP-based MTI adumbrates to be more sensitive than MRI and DTI for the early detection and follow-up assessment of MS lesions. CLINICAL RELEVANCE STATEMENT When additionally acquired in routine MRI, fast bSSFP-based MTI can complement the MRI/DTI longitudinal lesion assessment by detecting MS lesions 2-4 months earlier than with MRI, which could implicate earlier clinical decisions and better follow-up/treatment assessment in MS patients. KEY POINTS • Magnetization transfer imaging provides more information than DTI in multiple sclerosis lesions and can detect tissue changes 2 to 4 months prior to their appearance on MRI. • After lesions' detection, quantitative magnetization transfer changes are more pronounced than magnetization transfer ratio changes and therefore promise to be more sensitive for the lesions' evolutional assessment. • Balanced steady-state free precession-based magnetization transfer imaging is more sensitive than MRI and DTI for the early detection and follow-up assessment of multiple sclerosis lesions.
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Affiliation(s)
- Monika Gloor
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Michaela Andelova
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Laura Gaetano
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC) AG, Basel, Switzerland
- Novartis Institutes for BioMedical Research Basel, Basel, Switzerland
| | - Athina Papadopoulou
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Federico Burguet Villena
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Till Sprenger
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- University Hospital Zürich, Zurich, Switzerland
| | | | - Ludwig Kappos
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Meritxell Garcia
- Division of Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland.
- Department of Neuroradiology, University Hospital Zürich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
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9
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Franklin RJM, Bodini B, Goldman SA. Remyelination in the Central Nervous System. Cold Spring Harb Perspect Biol 2024; 16:a041371. [PMID: 38316552 PMCID: PMC10910446 DOI: 10.1101/cshperspect.a041371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
The inability of the mammalian central nervous system (CNS) to undergo spontaneous regeneration has long been regarded as a central tenet of neurobiology. However, while this is largely true of the neuronal elements of the adult mammalian CNS, save for discrete populations of granule neurons, the same is not true of its glial elements. In particular, the loss of oligodendrocytes, which results in demyelination, triggers a spontaneous and often highly efficient regenerative response, remyelination, in which new oligodendrocytes are generated and myelin sheaths are restored to denuded axons. Yet remyelination in humans is not without limitation, and a variety of demyelinating conditions are associated with sustained and disabling myelin loss. In this work, we will (1) review the biology of remyelination, including the cells and signals involved; (2) describe when remyelination occurs and when and why it fails, including the consequences of its failure; and (3) discuss approaches for therapeutically enhancing remyelination in demyelinating diseases of both children and adults, both by stimulating endogenous oligodendrocyte progenitor cells and by transplanting these cells into demyelinated brain.
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Affiliation(s)
- Robin J M Franklin
- Altos Labs Cambridge Institute of Science, Cambridge CB21 6GH, United Kingdom
| | - Benedetta Bodini
- Sorbonne Université, Paris Brain Institute, CNRS, INSERM, Paris 75013, France
- Saint-Antoine Hospital, APHP, Paris 75012, France
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York 14642, USA
- University of Copenhagen Faculty of Medicine, Copenhagen 2200, Denmark
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10
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Morrissey ZD, Gao J, Shetti A, Li W, Zhan L, Li W, Fortel I, Saido T, Saito T, Ajilore O, Cologna SM, Lazarov O, Leow AD. Temporal Alterations in White Matter in An App Knock-In Mouse Model of Alzheimer's Disease. eNeuro 2024; 11:ENEURO.0496-23.2024. [PMID: 38290851 PMCID: PMC10897532 DOI: 10.1523/eneuro.0496-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/05/2024] [Accepted: 01/17/2024] [Indexed: 02/01/2024] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia and results in neurodegeneration and cognitive impairment. White matter (WM) is affected in AD and has implications for neural circuitry and cognitive function. The trajectory of these changes across age, however, is still not well understood, especially at earlier stages in life. To address this, we used the AppNL-G-F/NL-G-F knock-in (APPKI) mouse model that harbors a single copy knock-in of the human amyloid precursor protein (APP) gene with three familial AD mutations. We performed in vivo diffusion tensor imaging (DTI) to study how the structural properties of the brain change across age in the context of AD. In late age APPKI mice, we observed reduced fractional anisotropy (FA), a proxy of WM integrity, in multiple brain regions, including the hippocampus, anterior commissure (AC), neocortex, and hypothalamus. At the cellular level, we observed greater numbers of oligodendrocytes in middle age (prior to observations in DTI) in both the AC, a major interhemispheric WM tract, and the hippocampus, which is involved in memory and heavily affected in AD, prior to observations in DTI. Proteomics analysis of the hippocampus also revealed altered expression of oligodendrocyte-related proteins with age and in APPKI mice. Together, these results help to improve our understanding of the development of AD pathology with age, and imply that middle age may be an important temporal window for potential therapeutic intervention.
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Affiliation(s)
- Zachery D Morrissey
- Graduate Program in Neuroscience, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Jin Gao
- Department of Electrical & Computer Engineering, University of Illinois Chicago, Chicago, Illinois 60607
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
| | - Aashutosh Shetti
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Wenping Li
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Liang Zhan
- Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
| | - Weiguo Li
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Radiology, Northwestern University, Chicago, Illinois 60611
| | - Igor Fortel
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
| | - Takaomi Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako 351-0198, Japan
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Nagoya 467-8601, Japan
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
| | - Stephanie M Cologna
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Orly Lazarov
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Alex D Leow
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Computer Science, University of Illinois Chicago, Chicago, Illinois 60607
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11
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Khormi I, Al-Iedani O, Alshehri A, Ramadan S, Lechner-Scott J. MR myelin imaging in multiple sclerosis: A scoping review. J Neurol Sci 2023; 455:122807. [PMID: 38035651 DOI: 10.1016/j.jns.2023.122807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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12
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Margoni M, Pagani E, Preziosa P, Gueye M, Azzimonti M, Rocca MA, Filippi M. Unraveling the heterogeneous pathological substrates of relapse-onset multiple sclerosis: a multiparametric voxel-wise 3 T MRI study. J Neurol 2023:10.1007/s00415-023-11736-9. [PMID: 37093395 DOI: 10.1007/s00415-023-11736-9] [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: 03/02/2023] [Revised: 04/17/2023] [Accepted: 04/17/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND In multiple sclerosis (MS), pathological processes affecting brain gray (GM) and white matter (WM) are heterogeneous. OBJECTIVE To apply a multimodal MRI approach to investigate the regional distribution of the different pathological processes occurring in the brain WM and GM of relapse-onset MS patients. METHODS Fifty-seven MS patients (forty-two relapsing remitting [RR], fifteen secondary progressive [SP]) and forty-seven age- and sex-matched healthy controls (HC) underwent a multimodal 3 T MRI acquisition. Between-group voxel-wise differences of brain WM and GM volumes, magnetization transfer ratio (MTR), T1-weighted(w)/T2w ratio, intracellular volume fraction (ICV_f), and quantitative susceptibility mapping (QSM) maps were investigated. RESULTS Compared to HC, RRMS showed significant WM, deep GM and cortical atrophy, significantly lower MTR and T1w/T2w ratio of periventricular and infratentorial WM, deep GM and several cortical areas, lower ICV_f in supratentorial and cerebellar WM and in some cortical areas, and lower QSM values in bilateral periventricular WM (p < 0.001). Compared to RRMS, SPMS patients showed significant deep GM and widespread cortical atrophy, significantly lower MTR of periventricular WM, deep GM and cerebellum, lower T1w/T2w ratio of fronto-temporal WM regions, lower ICV_f of some fronto-tempo-occipital WM and cortical areas. They also had increased QSM and T1w/T2w ratio in the pallidum, bilaterally (p < 0.001). CONCLUSION A periventricular pattern of demyelination and widespread GM and WM neuro-axonal loss are detectable in RRMS and are more severe in SPMS. Higher T1w/T2w ratio and QSM in the pallidum, possibly reflecting iron accumulation and neurodegeneration, may represent a relevant MRI marker to differentiate SPMS from RRMS.
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Affiliation(s)
- Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Mor Gueye
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Matteo Azzimonti
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, 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, Via Olgettina, 60, 20132, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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13
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In vivo characterization of microglia and myelin relation in multiple sclerosis by combined 11C-PBR28 PET and synthetic MRI. J Neurol 2023; 270:3091-3102. [PMID: 36859627 DOI: 10.1007/s00415-023-11621-5] [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: 02/07/2023] [Accepted: 02/08/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND The in vivo relation between microglia activation and demyelination in multiple sclerosis is still unclear. OBJECTIVE We combined 11C-PBR28 positron emission tomography and rapid estimation of myelin for diagnostic imaging (REMyDI) to characterize the relation between these pathological processes in a heterogeneous MS cohort. METHODS 11C-PBR28 standardized uptake values normalized by a pseudo-reference region (SUVR) were used to measure activated microglia. A voxelwise analysis compared 11C-PBR28 SUVR in the white matter of 38 MS patients and 16 matched healthy controls. The relative difference in SUVR served as a threshold to classify patients' lesioned, perilesional and normal-appearing white matter as active or inactive. REMyDI was acquired in 27 MS patients for assessing myelin content in active and inactive white matter and its relationship with SUVR. Finally, we investigated the contribution of radiological metrics to clinical outcomes. RESULTS 11C-PBR28 SUVR were abnormally higher in several white matter areas in MS. Myelin content was lower in active compared to inactive corresponding white matter regions. An inverse correlation between SUVR and myelin content was found. Radiological metrics correlated with both neurological and cognitive impairment. CONCLUSION our data suggest an inverse relation of microglia activation and myelination, particularly in perilesional white matter tissue.
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14
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Kuhlmann T, Moccia M, Coetzee T, Cohen JA, Correale J, Graves J, Marrie RA, Montalban X, Yong VW, Thompson AJ, Reich DS. Multiple sclerosis progression: time for a new mechanism-driven framework. Lancet Neurol 2023; 22:78-88. [PMID: 36410373 PMCID: PMC10463558 DOI: 10.1016/s1474-4422(22)00289-7] [Citation(s) in RCA: 163] [Impact Index Per Article: 163.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 05/29/2022] [Accepted: 06/29/2022] [Indexed: 11/20/2022]
Abstract
Traditionally, multiple sclerosis has been categorised by distinct clinical descriptors-relapsing-remitting, secondary progressive, and primary progressive-for patient care, research, and regulatory approval of medications. Accumulating evidence suggests that the clinical course of multiple sclerosis is better considered as a continuum, with contributions from concurrent pathophysiological processes that vary across individuals and over time. The apparent evolution to a progressive course reflects a partial shift from predominantly localised acute injury to widespread inflammation and neurodegeneration, coupled with failure of compensatory mechanisms, such as neuroplasticity and remyelination. Ageing increases neural susceptibility to injury and decreases resilience. These observations encourage a new consideration of the course of multiple sclerosis as a spectrum defined by the relative contributions of overlapping pathological and reparative or compensatory processes. New understanding of key mechanisms underlying progression and measures to quantify progressive pathology will potentially have important and beneficial implications for clinical care, treatment targets, and regulatory decision-making.
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Affiliation(s)
- Tanja Kuhlmann
- Institute of Neuropathology, University Hospital Münster, Münster, Germany; Neuroimmunology Unit, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Marcello Moccia
- Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences, Federico II University of Naples, Naples, Italy
| | - Timothy Coetzee
- National Multiple Sclerosis Society (USA), New York, NY, USA
| | - Jeffrey A Cohen
- Department of Neurology, Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jorge Correale
- Fleni, Department of Neurology, Buenos Aires, Argentina; Institute of Biological Chemistry and Biophysics (IQUIFIB), CONICET/UBA, Buenos Aires, Argentina
| | - Jennifer Graves
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Ruth Ann Marrie
- Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia and Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - V Wee Yong
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Alan J Thompson
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, NIHR University College London Hospitals Biomedical Research Centre, Faculty of Brain Sciences, University College London, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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15
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Brown JWL, Prados F, Altmann DR, Kanber B, Stutters J, Cunniffe NG, Jones JL, Georgieva ZG, Needham EJ, Daruwalla C, Wheeler‐Kingshott CG, Connick P, Chandran S, Franklin R, MacManus D, Samson R, Coles A, Chard D. Remyelination varies between and within lesions in multiple sclerosis following bexarotene. Ann Clin Transl Neurol 2022; 9:1626-1642. [PMID: 36116011 PMCID: PMC9539389 DOI: 10.1002/acn3.51662] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/16/2022] [Accepted: 08/22/2022] [Indexed: 12/01/2022] Open
Abstract
OBJECTIVE In multiple sclerosis chronic demyelination is associated with axonal loss, and ultimately contributes to irreversible progressive disability. Enhancing remyelination may slow, or even reverse, disability. We recently trialled bexarotene versus placebo in 49 people with multiple sclerosis. While the primary MRI outcome was negative, there was converging neurophysiological and MRI evidence of efficacy. Multiple factors influence lesion remyelination. In this study we undertook a systematic exploratory analysis to determine whether treatment response - measured by change in magnetisation transfer ratio - is influenced by location (tissue type and proximity to CSF) or the degree of abnormality (using baseline magnetisation transfer ratio and T1 values). METHODS We examined treatment effects at the whole lesion level, the lesion component level (core, rim and perilesional tissues) and at the individual lesion voxel level. RESULTS At the whole lesion level, significant treatment effects were seen in GM but not WM lesions. Voxel-level analyses detected significant treatment effects in WM lesion voxels with the lowest baseline MTR, and uncovered gradients of treatment effect in both WM and CGM lesional voxels, suggesting that treatment effects were lower near CSF spaces. Finally, larger treatment effects were seen in the outer and surrounding components of GM lesions compared to inner cores. INTERPRETATION Remyelination varies markedly within and between lesions. The greater remyelinating effect in GM lesions is congruent with neuropathological observations. For future remyelination trials, whole GM lesion measures require less complex post-processing compared to WM lesions (which require voxel level analyses) and markedly reduce sample sizes.
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Affiliation(s)
- J. William L. Brown
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
- Clinical Outcomes Research Unit (CORe)University of MelbourneMelbourneAustralia
| | - Ferran Prados
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
- e‐Health Center, Universitat Oberta de CatalunyaBarcelonaSpain
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Daniel R. Altmann
- Medical Statistics DepartmentLondon School of Hygiene & Tropical MedicineLondonUK
| | - Baris Kanber
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image ComputingUniversity College LondonLondonUK
- National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College LondonLondonUK
| | - Jonathan Stutters
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
| | - Nick G. Cunniffe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Joanne L. Jones
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Zoya G. Georgieva
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Edward J. Needham
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Cyrus Daruwalla
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Claudia Gandini Wheeler‐Kingshott
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
- Brain Connectivity Centre, IRCCS Mondino FoundationPaviaItaly
- Department of Brain and Behavioural SciencesUniversity of PaviaPaviaItaly
| | - Peter Connick
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Siddharthan Chandran
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research Institute, University of EdinburghEdinburghUK
| | - Robin Franklin
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wellcome‐MRC Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - David MacManus
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
| | - Rebecca Samson
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
| | - Alasdair Coles
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Declan Chard
- NMR Research UnitQueen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of NeurologyLondonUK
- National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College LondonLondonUK
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16
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Kolb H, Al-Louzi O, Beck ES, Sati P, Absinta M, Reich DS. From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions. Neuroimage Clin 2022; 36:103194. [PMID: 36170753 PMCID: PMC9668624 DOI: 10.1016/j.nicl.2022.103194] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 12/14/2022]
Abstract
Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.
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Affiliation(s)
- Hadar Kolb
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel,Corresponding author at: Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel.
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Institute of Experimental Neurology (INSPE), IRCSS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy,Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
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17
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Rahmanzadeh R, Weigel M, Lu PJ, Melie-Garcia L, Nguyen TD, Cagol A, La Rosa F, Barakovic M, Lutti A, Wang Y, Bach Cuadra M, Radue EW, Gaetano L, Kappos L, Kuhle J, Magon S, Granziera C. A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects. Neuroimage Clin 2022; 36:103177. [PMID: 36067611 PMCID: PMC9468574 DOI: 10.1016/j.nicl.2022.103177] [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: 03/01/2022] [Revised: 08/22/2022] [Accepted: 08/27/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM). Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients. METHODS We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels. The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM. RESULTS qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P < 0.0001), although QSM also showed the highest variance when applied to lesions. MWF and MTsat exhibited the highest sensitivity to NAWM pathology (P < 0.01). On the other hand, qT1 appeared to be the most sensitive measure to NAGM pathology (P < 0.01). All myelin-sensitive qMRI measures exhibited high inter/intra sessional ICCs in various WM and deep GM ROIs, in NAWM and in NAGM (ICC 0.82 ± 0.12). CONCLUSION This work shows that the applied qT1, MWF, MTsat and QSM are highly reproducible and exhibit differential sensitivity to focal and diffuse WM and GM pathology in MS patients.
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Affiliation(s)
- Reza Rahmanzadeh
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Alessandro Cagol
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | | | - Ludwig Kappos
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Stefano Magon
- Pharmaceutical Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland,Corresponding author.
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18
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Tagge IJ, Leppert IR, Fetco D, Campbell JS, Rudko DA, Brown RA, Stikov N, Pike GB, Giacomini PS, Arnold DL, Narayanan S. Permanent tissue damage in multiple sclerosis lesions is associated with reduced pre-lesion myelin and axon volume fractions. Mult Scler 2022; 28:2027-2037. [PMID: 35903888 PMCID: PMC9574230 DOI: 10.1177/13524585221110585] [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: 11/17/2022]
Abstract
BACKGROUND The use of advanced magnetic resonance imaging (MRI) techniques in MS research has led to new insights in lesion evolution and disease outcomes. It has not yet been determined if, or how, pre-lesional abnormalities in normal-appearing white matter (NAWM) relate to the long-term evolution of new lesions. OBJECTIVE To investigate the relationship between abnormalities in MRI measures of axonal and myelin volume fractions (AVF and MVF) in NAWM preceding development of black-hole (BH) and non-BH lesions in people with MS. METHODS We obtained magnetization transfer and diffusion MRI at 6-month intervals in patients with MS to estimate MVF and AVF during lesion evolution. Lesions were classified as either BH or non-BH on the final imaging visit using T1 maps. RESULTS Longitudinal data from 97 new T2 lesions from 9 participants were analyzed; 25 lesions in 8 participants were classified as BH 6-12 months after initial appearance. Pre-lesion MVF, AVF, and MVF/AVF were significantly lower, and T1 was significantly higher, in the lesions that later became BHs (p < 0.001) compared to those that did not. No significant pre-lesion abnormalities were found in non-BH lesions (p > 0.05). CONCLUSION The present work demonstrated that pre-lesion abnormalities are associated with worse long-term lesion-level outcome.
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Affiliation(s)
- Ian J Tagge
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Dumitru Fetco
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Jennifer Sw Campbell
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - David A Rudko
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Robert A Brown
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Nikola Stikov
- Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Paul S Giacomini
- Neurology and Neurosurgery, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
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19
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Lazzarotto A, Tonietto M, Poirion E, Battaglini M, Palladino R, Benoit C, Ricigliano VA, Maillart E, De Stefano N, Stankoff B, Bodini B. Clinically relevant profiles of myelin content changes in patients with multiple sclerosis: A multimodal and multicompartment imaging study. Mult Scler 2022; 28:1881-1890. [PMID: 35708126 DOI: 10.1177/13524585221096975] [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: 11/17/2022]
Abstract
OBJECTIVE To investigate the clinical relevance of individual profiles of cortical and white matter lesion myelin content changes combining magnetisation transfer imaging (MTI) and 11C-PiB-positron emission tomography (PET) in patients with multiple sclerosis (MS). METHODS MTI and [11C]PiB-PET acquired in 19 patients with MS followed up over 2-4 months and in seven healthy controls (HCs), were employed to generate individual maps of cortical and white matter (WM) lesion myelin content changes, respectively. These maps were used to calculate individual indices of demyelination and remyelination, and to investigate their association with clinical scores. RESULTS Cortical remyelination ranged between 1% and 5% of the total cortical volume (17%-45% of the cortical volume demyelinated at baseline). WM lesion remyelination ranged between 8% and 22% of the lesional volume. An extensive cortical remyelination was associated with a shorter disease duration (rho = -0.63, p = 0.01) and, in combination with WM lesion remyelination, explained 68%-70% of the variance of clinical scores (p < 0.01). CONCLUSION Our multimodal and multicompartment approach allows us to explore single-patient cortical and WM lesion demyelination and remyelination, and to generate clinically relevant indices of myelin repair. These indices may be used as outcome measures in clinical trials, thus increasing the chance to identify successful promyelinating treatments in patients with MS.
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Affiliation(s)
- Andrea Lazzarotto
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/Padova Neuroscience Center, University of Padua, Padua, Italy; AP-HP, Hôpital Saint-Antoine, Paris, France
| | - Matteo Tonietto
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Université Paris-Saclay, Orsay, France
| | - Emilie Poirion
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France; Hospital Foundation A. de Rothschild, Imaging department, Paris, France
| | - Marco Battaglini
- Department of Neurological and Behavioural Sciences, University of Siena, Siena, Italy
| | - Raffaele Palladino
- Department of Primary Care and Public Health, School of Public Health, Imperial College of London, London, UK/Department of Public Health, University 'Federico II' of Naples, Naples, Italy
| | - Charline Benoit
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France
| | - Vito Ag Ricigliano
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/AP-HP, Hôpital Saint-Antoine, Paris, France
| | - Elisabeth Maillart
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/AP-HP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Nicola De Stefano
- Department of Neurological and Behavioural Sciences, University of Siena, Siena, Italy
| | - Bruno Stankoff
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/AP-HP, Hôpital Saint-Antoine, Paris, France
| | - Benedetta Bodini
- Sorbonne Université, Paris Brain Institute, CNRS, Inserm, Paris, France/AP-HP, Hôpital Saint-Antoine, Paris, France/Institut du Cerveau et de la moelle épinière, ICM, UPMC Univ Paris 06, UMR S 1127, and CNRS UMR 7225, Hopital Pitié-Salpêtrière, Paris, France
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20
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Periventricular magnetisation transfer abnormalities in early multiple sclerosis. Neuroimage Clin 2022; 34:103012. [PMID: 35487133 PMCID: PMC9125781 DOI: 10.1016/j.nicl.2022.103012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 11/30/2022]
Abstract
Periventricular-MTR gradients are present from the earliest stage of MS and become steeper in advanced disease. Lower MTR in periventricular-NAWM was positively associated with reduced cortical-mean-thickness. MTR in periventricular-lesions scaled with cortical-mean-thickness, while non-periventricular lesions were unrelated. These findings suggest a common pathophysiologic mechanism between CSF-adjacent cortical and periventricular areas.
Objective Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. Methods We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. Results Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. Conclusion PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.
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21
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Jandric D, Parker GJM, Haroon H, Tomassini V, Muhlert N, Lipp I. A tractometry principal component analysis of white matter tract network structure and relationships with cognitive function in relapsing-remitting multiple sclerosis. Neuroimage Clin 2022; 34:102995. [PMID: 35349892 PMCID: PMC8958271 DOI: 10.1016/j.nicl.2022.102995] [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: 12/21/2021] [Revised: 03/04/2022] [Accepted: 03/23/2022] [Indexed: 10/25/2022]
Abstract
Understanding the brain changes underlying cognitive dysfunction is a key priority in multiple sclerosis (MS) to improve monitoring and treatment of this debilitating symptom. Functional connectivity network changes are associated with cognitive dysfunction, but it is less well understood how changes in normal appearing white matter relate to cognitive symptoms. If white matter tracts have network structure it would be expected that tracts within a network share susceptibility to MS pathology. In the present study, we used a tractometry approach to explore patterns of variance in white matter metrics across white matter (WM) tracts, and assessed how such patterns relate to neuropsychological test performance across cognitive domains. A sample of 102 relapsing-remitting MS patients and 27 healthy controls underwent MRI and neuropsychological testing. Tractography was performed on diffusion MRI data to extract 40 WM tracts and microstructural measures were extracted from each tract. Principal component analysis (PCA) was used to decompose metrics from all tracts to assess the presence of any co-variance structure among the tracts. Similarly, PCA was applied to cognitive test scores to identify the main cognitive domains. Finally, we assessed the ability of tract co-variance patterns to predict test performance across cognitive domains. We found that a single co-variance pattern which captured microstructure across all tracts explained the most variance (65% variance explained) and that there was little evidence for separate, smaller network patterns of pathology. Variance in this pattern was explained by effects related to lesions, but one main co-variance pattern persisted after this effect was regressed out. This main WM tract co-variance pattern contributed to explaining a modest degree of variance in one of our four cognitive domains in MS. These findings highlight the need to investigate the relationship between the normal appearing white matter and cognitive impairment further and on a more granular level, to improve the understanding of the network structure of the brain in MS.
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Affiliation(s)
- Danka Jandric
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK; Bioxydyn Limited, Manchester, UK
| | - Hamied Haroon
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Valentina Tomassini
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK; Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy; Multiple Sclerosis Centre, Department of Neurology, SS. Annunziata University Hospital, Chieti, Italy
| | - Nils Muhlert
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Ilona Lipp
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK; Department of Neurophysics, Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany.
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22
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Vaneckova M, Piredda GF, Andelova M, Krasensky J, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Hilbert T, Maréchal B, Fartaria MJ, Ravano V, Kober T. Periventricular gradient of T 1 tissue alterations in multiple sclerosis. Neuroimage Clin 2022; 34:103009. [PMID: 35561554 PMCID: PMC9112026 DOI: 10.1016/j.nicl.2022.103009] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/24/2022] [Accepted: 04/12/2022] [Indexed: 01/12/2023]
Abstract
T1 relaxation times alterations were assessed based on a study-specific atlas. T1 alterations depend on distance from lateral ventricles (“periventricular gradient”). Gradient parameters correlate better with disability compared to conventional MRI.
Objective Pathology in multiple sclerosis is not homogenously distributed. Recently, it has been shown that structures adjacent to CSF are more severely affected. A gradient of brain tissue involvement was shown with more severe pathology in periventricular areas and in proximity to brain surfaces such as the subarachnoid spaces and ependyma, and hence termed the “surface–in” gradient. Here, we study whether (i) the surface-in gradient of periventricular tissue alteration measured by T1 relaxometry is already present in early multiple sclerosis patients, (ii) how it differs between early and progressive multiple sclerosis patients, and (iii) whether the gradient-derived metrics in normal-appearing white matter and lesions correlate better with physical disability than conventional MRI-based metrics. Methods Forty-seven patients with early multiple sclerosis, 52 with progressive multiple sclerosis, and 92 healthy controls were included in the study. Isotropic 3D T1 relaxometry maps were obtained using the Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes sequence at 3 T. After spatially normalizing the T1 maps into a study-specific common space, T1 inter-subject variability within the healthy cohort was modelled voxel-wise, yielding a normative T1 atlas. Individual comparisons of each multiple sclerosis patient against the atlas were performed by computing z-scores. Equidistant bands of voxels were defined around the ventricles in the supratentorial white matter; the z-scores in these bands were analysed and compared between the early and progressive multiple sclerosis cohorts. Correlations between both conventional and z-score-gradient-derived MRI metrics and the Expanded Disability Status Scale were assessed. Results Patients with early and progressive multiple sclerosis demonstrated a periventricular gradient of T1 relaxation time z-scores. In progressive multiple sclerosis, z-score-derived metrics reflecting the gradient of tissue abnormality in normal-appearing white matter were more strongly correlated with disability (maximal rho = 0.374) than the conventional lesion volume and count (maximal rho = 0.189 and 0.21 respectively). In early multiple sclerosis, the gradient of normal-appearing white matter volume with z-scores > 2 at baseline correlated with clinical disability assessed at two years follow-up. Conclusion Our results suggest that the surface-in white matter gradient of tissue alteration is detectable with T1 relaxometry and is already present at clinical disease onset. The periventricular gradients correlate with clinical disability. The periventricular gradient in normal-appearing white matter may thus qualify as a promising biomarker for monitoring of disease activity from an early stage in all phenotypes of multiple sclerosis.
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Affiliation(s)
- Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- 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
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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23
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Arnold DL, Piani-Meier D, Bar-Or A, Benedict RH, Cree BA, Giovannoni G, Gold R, Vermersch P, Arnould S, Dahlke F, Hach T, Ritter S, Karlsson G, Kappos L, Fox RJ. Effect of siponimod on magnetic resonance imaging measures of neurodegeneration and myelination in secondary progressive multiple sclerosis: Gray matter atrophy and magnetization transfer ratio analyses from the EXPAND phase 3 trial. Mult Scler 2022; 28:1526-1540. [PMID: 35261318 PMCID: PMC9315182 DOI: 10.1177/13524585221076717] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) measurements of gray matter (GM) atrophy and magnetization transfer ratio (MTR; correlate of myelination) may provide better insights than conventional MRI regarding brain tissue integrity/myelination in multiple sclerosis (MS). OBJECTIVE To examine the effect of siponimod in the EXPAND trial on whole-brain and GM atrophy, newly formed normalized magnetization transfer ratio (nMTR) lesions, and nMTR-assessed integrity of normal-appearing brain tissue (NABT), cortical GM (cGM), and normal-appearing white matter (NAWM). METHODS Patients with secondary progressive multiple sclerosis (SPMS) received siponimod (2 mg/day; n =1037) or placebo (n = 523). Endpoints included percentage change from baseline to months 12/24 in whole-brain, cGM, and thalamic volumes; change in nMTR from baseline to months 12/24 in NABT, cGM, and NAWM; MTR recovery in newly formed lesions. RESULTS Compared with placebo, siponimod significantly reduced progression of whole-brain and GM atrophy over 12/24 months, and was associated with improvements in brain tissue integrity/myelination within newly formed nMTR lesions and across NABT, cGM, and NAWM over 24 months. Effects were consistent across age, disease duration, inflammatory activity subgroups, and disease severity. CONCLUSION Siponimod reduced brain tissue damage in patients with SPMS as evidenced by objective measures of brain tissue integrity/myelination. This is consistent with central nervous system (CNS) effects observed in preclinical models. ClinicalTrials.gov number: NCT01665144.
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Affiliation(s)
- Douglas L Arnold
- NeuroRx, Montreal, QC, Canada/Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bruce Ac Cree
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gavin Giovannoni
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ralf Gold
- Department of Neurology, St Josef-Hospital/Ruhr-University Bochum, Bochum, Germany
| | - Patrick Vermersch
- Univ. Lille, Inserm U1172 LilNCog, CHU Lille, FHU Precise, Lille, France
| | - Sophie Arnould
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Frank Dahlke
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Thomas Hach
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Shannon Ritter
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Göril Karlsson
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) and MS Center, Departments of Head, Spine and Neuromedicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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24
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Demir S, Clifford B, Lo WC, Tabari A, Goncalves Filho ALM, Lang M, Cauley SF, Setsompop K, Bilgic B, Lev MH, Schaefer PW, Rapalino O, Huang SY, Hilbert T, Feiweier T, Conklin J. Optimization of magnetization transfer contrast for EPI FLAIR brain imaging. Magn Reson Med 2022; 87:2380-2387. [PMID: 34985151 PMCID: PMC8847235 DOI: 10.1002/mrm.29141] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/10/2021] [Accepted: 12/11/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE To evaluate the impact of magnetization transfer (MT) on brain tissue contrast in turbo-spin-echo (TSE) and EPI fluid-attenuated inversion recovery (FLAIR) images, and to optimize an MT-prepared EPI FLAIR pulse sequence to match the tissue contrast of a clinical reference TSE FLAIR protocol. METHODS Five healthy volunteers underwent 3T brain MRI, including single slice TSE FLAIR, multi-slice TSE FLAIR, EPI FLAIR without MT-preparation, and MT-prepared EPI FLAIR with variations of the MT-preparation parameters, including number of preparation pulses, pulse amplitude, and resonance offset. Automated co-registration and gray matter (GM) versus white matter (WM) segmentation was performed using a T1-MPRAGE acquisition, and the GM versus WM signal intensity ratio (contrast ratio) was calculated for each FLAIR acquisition. RESULTS Without MT preparation, EPI FLAIR showed poor tissue contrast (contrast ratio = 0.98), as did single slice TSE FLAIR. Multi-slice TSE FLAIR provided high tissue contrast (contrast ratio = 1.14). MT-prepared EPI FLAIR closely approximated the contrast of the multi-slice TSE FLAIR images for two combinations of the MT-preparation parameters (contrast ratio = 1.14). Optimized MT-prepared EPI FLAIR provided a 50% reduction in scan time compared to the reference TSE FLAIR acquisition. CONCLUSION Optimized MT-prepared EPI FLAIR provides comparable brain tissue contrast to the multi-slice TSE FLAIR images used in clinical practice.
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Affiliation(s)
- Serdest Demir
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Bryan Clifford
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Stephen F Cauley
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Berkin Bilgic
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
| | | | | | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
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25
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Myelin imaging measures as predictors of cognitive impairment in MS patients: A hybrid PET-MRI study. Mult Scler Relat Disord 2022; 57:103331. [PMID: 35158445 DOI: 10.1016/j.msard.2021.103331] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/01/2021] [Accepted: 10/11/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND Cognitive impairment is one of the concerns of Multiple Sclerosis (MS) and has been related to myelin loss. Different neuroimaging methods have been used to quantify myelin and relate it to cognitive dysfunctions, among them Magnetization Transfer Ratio (MTR), Diffusion Tensor Imaging (DTI), and, more recently, Positron Emission Tomography (PET) with 11C-PIB. OBJECTIVE To investigate different myelin imaging modalities as predictors of cognitive dysfunction. METHODS Fifty-one MS patients and 24 healthy controls underwent clinical and neuropsychological assessment and MTR, DTI (Axial Diffusion-AD and Fractional Anisotropy-FA maps), and 11C-PIB PET images in a PET/MR hybrid system. RESULTS MTR and DTI(FA) differed in patients with or without cognitive impairment. There was an association of DTI(FA) and DTI(AD) with cognition and psychomotor speed for progressive MS, and of 11C-PIB uptake and MTR for relapsing-remitting MS. MTR in the Thalamus (β= -0.51, p = 0.021) and Corpus Callosum (β= -0.24, p = 0.033) were predictive of cognitive impairment. DTI-FA in the Caudate (β= -26.93, p = 0.006) presented abnormal predictive result. CONCLUSION Lower myelin content by 11C-PIB uptake was associated with worse cognitive status. MTR was predictive of cognitive impairment in MS.
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26
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Moccia M, Haider L, Eshaghi A, van de Pavert SHP, Brescia Morra V, Patel A, Wheeler-Kingshott CAM, Barkhof F, Ciccarelli O. B Cells in the CNS at Postmortem Are Associated With Worse Outcome and Cell Types in Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:e1108. [PMID: 34759021 PMCID: PMC8587731 DOI: 10.1212/nxi.0000000000001108] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 09/08/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND OBJECTIVES To define the clinical and pathologic correlations of compartmentalized perivascular B cells in postmortem progressive multiple sclerosis (MS) brains. METHODS Brain slices were acquired from 11 people with secondary progressive (SP) MS, 5 people with primary progressive (PP) MS, and 4 controls. Brain slices were immunostained for B lymphocytes (CD20), T lymphocytes (CD3), cytotoxic T lymphocytes (CD8), neuronal neurofilaments (NF200), myelin (SMI94), macrophages/microglia (CD68 and IBA1), astrocytes (glial fibrillary acidic protein [GFAP]), and mitochondria (voltage-dependent anion channel and cytochrome c oxidase subunit 4). Differences in CD20 immunostaining intensity between disease groups and associations between CD20 immunostaining intensity and both clinical variables and other immunostaining intensities were explored with linear mixed regression models and Cox regression models, as appropriate. RESULTS CD20 immunostaining intensity was higher in PPMS (Coeff = 0.410; 95% confidence interval [CI] = 0.046, 0.774; p = 0.027) and SPMS (Coeff = 0.302; 95% CI = 0.020, 0.585; p = 0.036) compared with controls. CD20 immunostaining intensity was higher in cerebellar, spinal cord, and pyramidal onset (Coeff = 0.274; 95% CI = 0.039, 0.510; p = 0.022) compared with optic neuritis and sensory onset. Higher CD20 immunostaining intensity was associated with younger age at onset (hazard ratio [HR] = 1.033; 95% CI = 1.013, 1.053; p = 0.001), SP conversion (HR = 1.056; 95% CI = 1.022, 1.091; p = 0.001), wheelchair dependence (HR = 1.472; 95% CI = 1.108, 1.954; p = 0.008), and death (HR = 1.684; 95% CI = 1.238, 2.291; p = 0.001). Higher immunostaining intensity for CD20 was associated with higher immunostaining intensity for CD3 (Coeff = 0.114; 95% CI = 0.005, 0.224; p = 0.040), CD8 (Coeff = 0.275; 95% CI = 0.200, 0.350; p < 0.001), CD68 (Coeff = 0.084; 95% CI = 0.023, 0.144; p = 0.006), GFAP (Coeff = 0.002; 95% CI = 0.001, 0.004; p = 0.030), and damaged mitochondria (Coeff = 3.902; 95% CI = 0.891, 6.914; p = 0.011). DISCUSSION Perivascular B cells were associated with worse clinical outcomes and CNS-compartmentalized inflammation. Our findings further support the concept of targeting compartmentalized B-cell inflammation in progressive MS.
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Affiliation(s)
- Marcello Moccia
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Lukas Haider
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Arman Eshaghi
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Steven Harry Pieter van de Pavert
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Vincenzo Brescia Morra
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Amy Patel
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Claudia Angela Michela Wheeler-Kingshott
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Frederik Barkhof
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Olga Ciccarelli
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
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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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28
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Potential Biomarkers Associated with Multiple Sclerosis Pathology. Int J Mol Sci 2021; 22:ijms221910323. [PMID: 34638664 PMCID: PMC8508638 DOI: 10.3390/ijms221910323] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/21/2021] [Accepted: 09/23/2021] [Indexed: 12/15/2022] Open
Abstract
Multiple sclerosis (MS) is a complex disease of the central nervous system (CNS) that involves an intricate and aberrant interaction of immune cells leading to inflammation, demyelination, and neurodegeneration. Due to the heterogeneity of clinical subtypes, their diagnosis becomes challenging and the best treatment cannot be easily provided to patients. Biomarkers have been used to simplify the diagnosis and prognosis of MS, as well as to evaluate the results of clinical treatments. In recent years, research on biomarkers has advanced rapidly due to their ability to be easily and promptly measured, their specificity, and their reproducibility. Biomarkers are classified into several categories depending on whether they address personal or predictive susceptibility, diagnosis, prognosis, disease activity, or response to treatment in different clinical courses of MS. The identified members indicate a variety of pathological processes of MS, such as neuroaxonal damage, gliosis, demyelination, progression of disability, and remyelination, among others. The present review analyzes biomarkers in cerebrospinal fluid (CSF) and blood serum, the most promising imaging biomarkers used in clinical practice. Furthermore, it aims to shed light on the criteria and challenges that a biomarker must face to be considered as a standard in daily clinical practice.
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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30
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Preisner F, Behnisch R, Foesleitner O, Schwarz D, Wehrstein M, Meredig H, Friedmann-Bette B, Heiland S, Bendszus M, Kronlage M. Reliability and reproducibility of sciatic nerve magnetization transfer imaging and T2 relaxometry. Eur Radiol 2021; 31:9120-9130. [PMID: 34104997 PMCID: PMC8589742 DOI: 10.1007/s00330-021-08072-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 04/08/2021] [Accepted: 05/11/2021] [Indexed: 12/19/2022]
Abstract
Objectives To assess the interreader and test-retest reliability of magnetization transfer imaging (MTI) and T2 relaxometry in sciatic nerve MR neurography (MRN). Materials and methods In this prospective study, 21 healthy volunteers were examined three times on separate days by a standardized MRN protocol at 3 Tesla, consisting of an MTI sequence, a multi-echo T2 relaxometry sequence, and a high-resolution T2-weighted sequence. Magnetization transfer ratio (MTR), T2 relaxation time, and proton spin density (PSD) of the sciatic nerve were assessed by two independent observers, and both interreader and test-retest reliability for all readout parameters were reported by intraclass correlation coefficients (ICCs) and standard error of measurement (SEM). Results For the sciatic nerve, overall mean ± standard deviation MTR was 26.75 ± 3.5%, T2 was 64.54 ± 8.2 ms, and PSD was 340.93 ± 78.8. ICCs ranged between 0.81 (MTR) and 0.94 (PSD) for interreader reliability and between 0.75 (MTR) and 0.94 (PSD) for test-retest reliability. SEM for interreader reliability was 1.7% for MTR, 2.67 ms for T2, and 21.3 for PSD. SEM for test-retest reliability was 1.7% for MTR, 2.66 ms for T2, and 20.1 for PSD. Conclusions MTI and T2 relaxometry of the sciatic nerve are reliable and reproducible. The values of measurement imprecision reported here may serve as a guide for correct interpretation of quantitative MRN biomarkers in future studies. Key Points • Magnetization transfer imaging (MTI) and T2 relaxometry of the sciatic nerve are reliable and reproducible. • The imprecision that is unavoidably associated with different scans or different readers can be estimated by the here presented SEM values for the biomarkers T2, PSD, and MTR. • These values may serve as a guide for correct interpretation of quantitative MRN biomarkers in future studies and possible clinical applications. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-08072-9.
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Affiliation(s)
- Fabian Preisner
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Rouven Behnisch
- Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Olivia Foesleitner
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Daniel Schwarz
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Michaela Wehrstein
- Department of Sports Medicine (Internal Medicine VII), Medical Clinic, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
| | - Hagen Meredig
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Birgit Friedmann-Bette
- Department of Sports Medicine (Internal Medicine VII), Medical Clinic, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Moritz Kronlage
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
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31
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Haase S, Linker RA. Inflammation in multiple sclerosis. Ther Adv Neurol Disord 2021; 14:17562864211007687. [PMID: 33948118 PMCID: PMC8053832 DOI: 10.1177/17562864211007687] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/15/2021] [Indexed: 12/24/2022] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) that is characterised pathologically by demyelination, gliosis, neuro-axonal damage and inflammation. Despite intense research, the underlying pathomechanisms driving inflammatory demyelination in MS still remain incompletely understood. It is thought to be caused by an autoimmune response towards CNS self-antigens in genetically susceptible individuals, assuming autoreactive T cells as disease-initiating immune cells. Yet, B cells were recognized as crucial immune cells in disease pathology, including antibody-dependent and independent effects. Moreover, myeloid cells are important contributors to MS pathology, and it is becoming increasingly evident that different cell types act in concert during MS immunopathology. This is supported by the finding that the beneficial effects of actual existing disease-modifying therapies cannot be attributed to one single immune cell-type, but rather involve immunological cooperation. The current strategy of MS therapies thus aims to shift the immune cell repertoire from a pro-inflammatory towards an anti-inflammatory phenotype, involving regulatory T and B cells and anti-inflammatory macrophages. Although no existing therapy actually exists that directly induces an enhanced regulatory immune cell pool, numerous studies identified potential net effects on these cell types. This review gives a conceptual overview on T cells, B cells and myeloid cells in the immunopathology of relapsing-remitting MS and discusses potential contributions of actual disease-modifying therapies on these immune cell phenotypes.
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Affiliation(s)
- Stefanie Haase
- Neuroimmunologie, Klinik und Poliklinik für Neurologie, Universitätsklinik Regensburg, Franz-Josef-Strauss Allee, Regensburg, 93053, Germany
| | - Ralf A Linker
- Department of Neurology, University Hospital Regensburg, Regensburg, Germany
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32
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Preziosa P, Storelli L, Meani A, Moiola L, Rodegher M, Filippi M, Rocca MA. Effects of Fingolimod and Natalizumab on Brain T1-/T2-Weighted and Magnetization Transfer Ratios: a 2-Year Study. Neurotherapeutics 2021; 18:878-888. [PMID: 33483938 PMCID: PMC8423925 DOI: 10.1007/s13311-020-00997-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2020] [Indexed: 11/26/2022] Open
Abstract
Fingolimod and natalizumab significantly reduce disease activity in relapsing-remitting multiple sclerosis (RRMS) and could promote tissue repair and neuroprotection. The ratio between conventional T1- and T2-weighted sequences (T1w/T2w-ratio) and magnetization transfer ratio (MTR) allow to quantify brain microstructural tissue abnormalities. Here, we compared fingolimod and natalizumab effects on brain T1w/T2w-ratio and MTR in RRMS over 2 years of treatment. RRMS patients starting fingolimod (n = 25) or natalizumab (n = 30) underwent 3T brain MRI scans at baseline (T0), month 6 (M6), month 12 (M12), and month 24 (M24). White matter (WM) lesions, normal-appearing (NA) WM, and gray matter (GM) T1w/T2w-ratio and MTR were estimated and compared between groups using linear mixed models. No baseline demographic, clinical, and MRI difference was found between groups. In natalizumab patients, lesion T1w/T2w-ratio and MTR significantly increased at M6 vs. T0 (p ≤ 0.035) and decreased at subsequent timepoints (p ≤ 0.037). In fingolimod patients, lesion T1w/T2w-ratio increased at M12 vs. T0 (p = 0.010), while MTR gradually increased at subsequent timepoints vs. T0 (p ≤ 0.027). Natalizumab stabilized NAWM and GM T1w/T2w-ratio and MTR. In fingolimod patients, NAWM T1w/T2w-ratio and MTR significantly increased at M24 vs. M12 (p ≤ 0.001). A significant GM T1w/T2w-ratio decrease at M6 vs. T0 (p = 0.014) and increase at M24 vs. M6 (p = 0.008) occurred, whereas GM MTR was significantly higher at M24 vs. previous timepoints (p ≤ 0.017) with significant between-group differences (p ≤ 0.034). Natalizumab may promote an early recovery of lesional damage and prevent microstructural damage accumulation in NAWM and GM during the first 2 years of treatment. Fingolimod enhances tissue damage recovery being visible after 6 months in lesions and after 2 years in NAWM and GM.
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Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucia Moiola
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 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
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy.
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