1
|
Oh J, Bar-Or A. Precision neuroimmunology in multiple sclerosis - the horizon is near. Nat Rev Neurol 2024; 20:507-508. [PMID: 38965380 DOI: 10.1038/s41582-024-00992-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Affiliation(s)
- Jiwon Oh
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Multiple Sclerosis Division, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| |
Collapse
|
2
|
Krieger S, Zarif M, Bumstead B, Buhse M, Kaczmarek O, Srinivasan J, Barros N, Sima D, Ribbens A, Van Hecke W, Lewin JB, Mendoza JP, Gudesblatt M. Evaluating the effect of dimethyl fumarate on subclinical biomarkers in a real-world patient cohort. J Neuroimmunol 2024; 393:578397. [PMID: 38959783 DOI: 10.1016/j.jneuroim.2024.578397] [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: 02/27/2024] [Revised: 05/24/2024] [Accepted: 06/19/2024] [Indexed: 07/05/2024]
Abstract
OBJECTIVE Evaluate the real-world effect of dimethyl fumarate (DMF) on subclinical biomarkers in patients with relapsing-remitting multiple sclerosis (RRMS) and compare with results from clinical trials. METHODS Magnetic resonance imaging (MRI) data from 102 RRMS patients were retrospectively collected and processed using icobrain to assess brain atrophy and to assist semi-manual lesion count. RESULTS Mean (±SD) annualized percent brain volume change in the first 3 years after DMF-initiation were: -0.33 ± 0.68, -0.10 ± 0.60, and - 0.35 ± 0.71%/year, respectively. No new FLAIR lesions were detected in 73.7%, 77.3%, and 73.3% of the patients during years 1, 2, and 3. CONCLUSIONS Results of this real-world study were consistent with previous DMF phase III clinical trials, supporting the generalizability of the effects observed in clinical trials to the real-world clinical setting.
Collapse
Affiliation(s)
- Stephen Krieger
- Corinne Goldsmith Dickinson Center for MS, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Myassar Zarif
- NYU Langone South Shore Neurologic Associates, Patchogue, NY, United States of America
| | - Barbara Bumstead
- NYU Langone South Shore Neurologic Associates, Patchogue, NY, United States of America
| | - Marijean Buhse
- NYU Langone South Shore Neurologic Associates, Patchogue, NY, United States of America
| | - Olivia Kaczmarek
- NYU Langone South Shore Neurologic Associates, Patchogue, NY, United States of America
| | | | | | | | | | | | | | | | - Mark Gudesblatt
- NYU Langone South Shore Neurologic Associates, Patchogue, NY, United States of America
| |
Collapse
|
3
|
Stys PK, Tsutsui S, Gafson AR, ‘t Hart BA, Belachew S, Geurts JJG. New views on the complex interplay between degeneration and autoimmunity in multiple sclerosis. Front Cell Neurosci 2024; 18:1426231. [PMID: 39161786 PMCID: PMC11330826 DOI: 10.3389/fncel.2024.1426231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 06/14/2024] [Indexed: 08/21/2024] Open
Abstract
Multiple sclerosis (MS) is a frequently disabling neurological disorder characterized by symptoms, clinical signs and imaging abnormalities that typically fluctuate over time, affecting any level of the CNS. Prominent lymphocytic inflammation, many genetic susceptibility variants involving immune pathways, as well as potent responses of the neuroinflammatory component to immunomodulating drugs, have led to the natural conclusion that this disease is driven by a primary autoimmune process. In this Hypothesis and Theory article, we discuss emerging data that cast doubt on this assumption. After three decades of therapeutic experience, what has become clear is that potent immune modulators are highly effective at suppressing inflammatory relapses, yet exhibit very limited effects on the later progressive phase of MS. Moreover, neuropathological examination of MS tissue indicates that degeneration, CNS atrophy, and myelin loss are most prominent in the progressive stage, when lymphocytic inflammation paradoxically wanes. Finally, emerging clinical observations such as "progression independent of relapse activity" and "silent progression," now thought to take hold very early in the course, together argue that an underlying "cytodegenerative" process, likely targeting the myelinating unit, may in fact represent the most proximal step in a complex pathophysiological cascade exacerbated by an autoimmune inflammatory overlay. Parallels are drawn with more traditional neurodegenerative disorders, where a progressive proteopathy with prion-like propagation of toxic misfolded species is now known to play a key role. A potentially pivotal contribution of the Epstein-Barr virus and B cells in this process is also discussed.
Collapse
Affiliation(s)
- Peter K. Stys
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shigeki Tsutsui
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Arie R. Gafson
- Biogen Digital Health, Biogen, Cambridge, MA, United States
| | - Bert A. ‘t Hart
- Department of Anatomy and Neurosciences, Amsterdam University Medical Centers (location VUmc), Amsterdam, Netherlands
| | - Shibeshih Belachew
- TheraPanacea, Paris, France
- Indivi (DBA of Healios AG), Basel, Switzerland
| | - Jeroen J. G. Geurts
- Department of Anatomy and Neurosciences, Amsterdam University Medical Centers (location VUmc), Amsterdam, Netherlands
| |
Collapse
|
4
|
Emeršič A, Karikari TK, Kac PR, Gonzalez-Ortiz F, Dulewicz M, Ashton NJ, Brecl Jakob G, Horvat Ledinek A, Hanrieder J, Zetterberg H, Rot U, Čučnik S, Blennow K. Biomarkers of tau phosphorylation state are associated with the clinical course of multiple sclerosis. Mult Scler Relat Disord 2024; 90:105801. [PMID: 39153429 DOI: 10.1016/j.msard.2024.105801] [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: 03/27/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 08/19/2024]
Abstract
BACKGROUND Mechanisms underlying neurodegeneration in multiple sclerosis (MS) remain poorly understood but mostly implicate molecular pathways that are not unique to MS. Recently detected tau seeding activity in MS brain tissues corroborates previous neuropathological reports of hyperphosphorylated tau (p-tau) accumulation in secondary and primary progressive MS (PPMS). We aimed to investigate whether aberrant tau phosphorylation can be detected in the cerebrospinal fluid (CSF) of MS patients by using novel ultrasensitive immunoassays for different p-tau biomarkers. METHODS CSF samples of patients with MS (n = 55) and non-inflammatory neurological disorders (NIND, n = 31) were analysed with in-house Single molecule array (Simoa) assays targeting different tau phosphorylation sites (p-tau181, p-tau212, p-tau217 and p-tau231). Additionally, neurofilament light (NFL) and glial fibrillary acidic protein (GFAP) were measured with a multiplexed Simoa assay. Patients were diagnosed with clinically isolated syndrome (CIS, n = 10), relapsing-remitting MS (RRMS, n = 21) and PPMS (n = 24) according to the 2017 McDonald criteria and had MRI, EDSS and basic CSF analysis performed at the time of diagnosis. RESULTS Patients with progressive disease course had between 1.4-fold (p-tau217) and 2.2-fold (p-tau212) higher p-tau levels than relapsing MS patients (PPMS compared with CIS + RRMS, p < 0.001 for p-tau181, p-tau212, p-tau231 and p = 0.042 for p-tau217). P-tau biomarkers were associated with disease duration (ρ=0.466-0.622, p < 0.0001), age (ρ=0.318-0.485, p < 0.02, all but p-tau217) and EDSS at diagnosis and follow-up (ρ=0.309-0.440, p < 0.02). In addition, p-tau biomarkers correlated with GFAP (ρ=0.517-0.719, p ≤ 0.0001) but not with the albumin quotient, CSF cell count or NFL. Patients with higher MRI lesion load also had higher p-tau levels p ≤ 0.01 (<10 vs. ≥ 10 lesions, all p ≤ 0.01). CONCLUSION CSF concentrations of novel p-tau biomarkers point to a higher degree of tau phosphorylation in PPMS than in RRMS. Associations with age, disease duration and EDSS suggest this process increases with disease severity; however, replication of these results in larger cohorts is needed to further clarify the relevance of altered tau phosphorylation throughout the disease course in MS.
Collapse
Affiliation(s)
- Andreja Emeršič
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia; Faculty of Pharmacy, University of Ljubljana, Ljubljana 1000, Slovenia.
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15215, USA
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden
| | - Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal 431 80, Sweden
| | - Maciej Dulewicz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg 405 30, Sweden; Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute, King's College London, London SE5 8AF, UK; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London SE5 8AF, UK
| | - Gregor Brecl Jakob
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana 1000, Slovenia
| | - Alenka Horvat Ledinek
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia
| | - Jörg Hanrieder
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal 431 80, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK; UK Dementia Research Institute at UCL, London WC1N 3AR, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong 518172, China; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Uroš Rot
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana 1000, Slovenia
| | - Saša Čučnik
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia; Faculty of Pharmacy, University of Ljubljana, Ljubljana 1000, Slovenia; Department of Rheumatology, University Medical Centre Ljubljana, Ljubljana 1000, Slovenia
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg 413 45, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal 431 80, Sweden; Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris 75013, France; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei 230001, PR China
| |
Collapse
|
5
|
Suwannasak A, Angkurawaranon S, Sangpin P, Chatnuntawech I, Wantanajittikul K, Yarach U. Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement. MAGMA (NEW YORK, N.Y.) 2024; 37:465-475. [PMID: 38758489 DOI: 10.1007/s10334-024-01165-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/27/2024] [Accepted: 04/30/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE This study investigated the feasibility of using deep learning-based super-resolution (DL-SR) technique on low-resolution (LR) images to generate high-resolution (HR) MR images with the aim of scan time reduction. The efficacy of DL-SR was also assessed through the application of brain volume measurement (BVM). MATERIALS AND METHODS In vivo brain images acquired with 3D-T1W from various MRI scanners were utilized. For model training, LR images were generated by downsampling the original 1 mm-2 mm isotropic resolution images. Pairs of LR and HR images were used for training 3D residual dense net (RDN). For model testing, actual scanned 2 mm isotropic resolution 3D-T1W images with one-minute scan time were used. Normalized root-mean-square error (NRMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used for model evaluation. The evaluation also included brain volume measurement, with assessments of subcortical brain regions. RESULTS The results showed that DL-SR model improved the quality of LR images compared with cubic interpolation, as indicated by NRMSE (24.22% vs 30.13%), PSNR (26.19 vs 24.65), and SSIM (0.96 vs 0.95). For volumetric assessments, there were no significant differences between DL-SR and actual HR images (p > 0.05, Pearson's correlation > 0.90) at seven subcortical regions. DISCUSSION The combination of LR MRI and DL-SR enables addressing prolonged scan time in 3D MRI scans while providing sufficient image quality without affecting brain volume measurement.
Collapse
Affiliation(s)
- Atita Suwannasak
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Road, Muang, Chiang Mai, 50200, Thailand
| | - Salita Angkurawaranon
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Intavaroros Road, Muang, Chiang Mai, Thailand
| | - Prapatsorn Sangpin
- Philips (Thailand) Ltd, New Petchburi Road, Bangkapi, Huaykwang, Bangkok, Thailand
| | - Itthi Chatnuntawech
- National Nanotechnology Center (NANOTEC), Phahon Yothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, Thailand
| | - Kittichai Wantanajittikul
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Road, Muang, Chiang Mai, 50200, Thailand
| | - Uten Yarach
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Road, Muang, Chiang Mai, 50200, Thailand.
| |
Collapse
|
6
|
Akaishi T, Fujimori J, Yokote H, Nakashima I. Continuous diffuse brain atrophy independent of relapse as a hallmark of multiple sclerosis beginning from relapsing-remitting stage. Clin Neurol Neurosurg 2024; 242:108342. [PMID: 38772279 DOI: 10.1016/j.clineuro.2024.108342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/23/2024]
Abstract
BACKGROUND Neurodegenerative changes are observed in relapsing-remitting multiple sclerosis (RRMS) and are prominent in secondary progressive MS (SPMS). However, whether neurodegenerative changes accelerate and are altered after the transition into SPMS or in the presence of relapses remains uncertain. METHODS In this study, 73 patients with MS (seven with relapsing RRMS, 56 with relapse-free RRMS, and 10 with relapse-free SPMS) were evaluated for brain segmental volume changes over a 2-year follow-up period. Volume change was calculated using a within-subject unbiased longitudinal image analysis model. RESULTS The rates of brain volume change in the 11 brain regions evaluated were relatively similar among different brain regions. Moreover, they were similar among the relapsing RRMS, relapse-free RRMS, and SPMS groups, even after adjusting for age. CONCLUSIONS The relatively constant brain segmental atrophy rate throughout the disease course, regardless of relapse episodes, suggests that RRMS and SPMS are continuous, uniform, and silent progressing brain atrophy diseases on a spectrum.
Collapse
Affiliation(s)
- Tetsuya Akaishi
- Department of Neurology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Juichi Fujimori
- Division of Neurology, Tohoku Medical and Pharmaceutical University, Sendai, Japan.
| | - Hiroaki Yokote
- Department of Neurology and Neurological Science, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ichiro Nakashima
- Division of Neurology, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| |
Collapse
|
7
|
Krieger S, Cook K, Hersh CM. Understanding multiple sclerosis as a disease spectrum: above and below the clinical threshold. Curr Opin Neurol 2024; 37:189-201. [PMID: 38535979 PMCID: PMC11064902 DOI: 10.1097/wco.0000000000001262] [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: 04/04/2024]
Abstract
PURPOSE OF REVIEW Research in multiple sclerosis (MS) has long been predicated on clinical groupings that do not reflect the underlying biologic heterogeneity apparent within patient populations. This review explicates the various levels of explanation through which the spectrum of disease is described and investigated both above and below the clinical threshold of detection, as framed by the topographical model of MS, to help advance a cogent mechanistic framework. RECENT FINDINGS Contemporary evidence has amended the view of MS as consisting of sequential disease phases in favor of a spectrum of disease with an admixture of interdependent and dynamic pathobiological axes driving tissue injury and progression. Recent studies have shown the presence of acute and compartmentalized inflammation and mechanisms of neurodegeneration beginning early and evolving throughout the disease continuum. Still, the gap between the understanding of immunopathologic processes in MS and the tools used to measure relevant molecular, laboratory, radiologic, and clinical metrics needs attention to enable better prognostication of disease and monitoring for changes along specific pathologic axes and variable treatment outcomes. SUMMARY Aligning on a consistently-applied mechanistic framework at distinct levels of explanation will enable greater precision across bench and clinical research, and inform discourse on drivers of disability progression and delivery of care for individuals with MS.
Collapse
Affiliation(s)
- Stephen Krieger
- Corinne Goldsmith Dickinson Center for MS, Icahn School of Medicine at Mount Sinai
| | - Karin Cook
- Medical Education Director, Neurology at Heartbeat/Publicis Health, New York
| | - Carrie M. Hersh
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland Clinic Lou Ruvo Center for Brain Health, Cleveland Clinic Las Vegas, Nevada, USA
| |
Collapse
|
8
|
Moser T, Trinka E. Epilepsy surgery in multiple sclerosis. Epileptic Disord 2024; 26:267-268. [PMID: 38259084 DOI: 10.1002/epd2.20195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 01/05/2024] [Indexed: 01/24/2024]
Affiliation(s)
- Tobias Moser
- Department of Neurology, Neurological Intensive Care and Neurorehabilitation, Christian Doppler University Hospital, Paracelsus Medical University and Center for Cognitive Neuroscience, Member of the European Reference Network EpiCARE, Salzburg, Austria
| | - Eugen Trinka
- Department of Neurology, Neurological Intensive Care and Neurorehabilitation, Christian Doppler University Hospital, Paracelsus Medical University and Center for Cognitive Neuroscience, Member of the European Reference Network EpiCARE, Salzburg, Austria
- Neuroscience Institute, Christian Doppler University Hospital, Paracelsus Medical University and Center for Cognitive Neuroscience, Salzburg, Austria
- Karl Landsteiner Institute of Neurorehabilitation and Space Neurology, Salzburg, Austria
| |
Collapse
|
9
|
Yazici I, Krieger B, Bellenberg B, Ladopoulos T, Gold R, Schneider R, Lukas C. Automatic estimation of brain parenchymal fraction in patients with multple sclerosis: a comparison between synthetic MRI and an established automated brain segmentation software based on FSL. Neuroradiology 2024; 66:193-205. [PMID: 38110539 PMCID: PMC10805841 DOI: 10.1007/s00234-023-03264-0] [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: 05/16/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023]
Abstract
PURPOSE We aimed to validate the estimation of the brain parenchymal fraction (BPF) in patients with multiple sclerosis (MS) using synthetic magnetic resonance imaging (SyMRI) by comparison with software tools of the FMRIB Software Library (FSL). In addition to a cross-sectional method comparison, longitudinal volume changes were assessed to further elucidate the suitability of SyMRI for quantification of disease-specific changes. METHODS MRI data from 216 patients with MS and 28 control participants were included for volume estimation by SyMRI and FSL-SIENAX. Moreover, longitudinal data from 35 patients with MS were used to compare registration-based percentage brain volume changes estimated using FSL-SIENA to difference-based calculations of volume changes using SyMRI. RESULTS We observed strong correlations of estimated brain volumes between the two methods. While SyMRI overestimated grey matter and BPF compared to FSL-SIENAX, indicating a systematic bias, there was excellent agreement according to intra-class correlation coefficients for grey matter and good agreement for BPF and white matter. Bland-Altman plots suggested that the inter-method differences in BPF were smaller in patients with brain atrophy compared to those without atrophy. Longitudinal analyses revealed a tendency for higher atrophy rates for SyMRI than for SIENA, but SyMRI had a robust correlation and a good agreement with SIENA. CONCLUSION In summary, BPF based on data from SyMRI and FSL-SIENAX is not directly transferable because an overestimation and higher variability of SyMRI values were observed. However, the consistency and correlations between the two methods were satisfactory, and SyMRI was suitable to quantify disease-specific atrophy in MS.
Collapse
Affiliation(s)
- Ilyas Yazici
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstrasse 56, 44791, Bochum, Germany
| | - Britta Krieger
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstrasse 56, 44791, Bochum, Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstrasse 56, 44791, Bochum, Germany
| | - Theodoros Ladopoulos
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791, Bochum, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791, Bochum, Germany
| | - Ruth Schneider
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791, Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstrasse 56, 44791, Bochum, Germany.
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791, Bochum, Germany.
| |
Collapse
|
10
|
Koubiyr I, Krijnen EA, Eijlers AJC, Dekker I, Hulst HE, Uitdehaag BMJ, Barkhof F, Geurts JJG, Schoonheim MM. Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis. Brain Commun 2024; 6:fcae018. [PMID: 38344654 PMCID: PMC10853982 DOI: 10.1093/braincomms/fcae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 12/21/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.
Collapse
Affiliation(s)
- Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Eva A Krijnen
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States
| | - Anand J C Eijlers
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Iris Dekker
- MS Center Amsterdam, Rehabilitation, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Hanneke E Hulst
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden 2333 AK, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Frederik Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| |
Collapse
|
11
|
Kreiter D, Postma AA, Hupperts R, Gerlach O. Hallmarks of spinal cord pathology in multiple sclerosis. J Neurol Sci 2024; 456:122846. [PMID: 38142540 DOI: 10.1016/j.jns.2023.122846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement.
Collapse
Affiliation(s)
- Daniel Kreiter
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Raymond Hupperts
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Oliver Gerlach
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| |
Collapse
|
12
|
Fleischer V, Gonzalez-Escamilla G, Pareto D, Rovira A, Sastre-Garriga J, Sowa P, Høgestøl EA, Harbo HF, Bellenberg B, Lukas C, Ruggieri S, Gasperini C, Uher T, Vaneckova M, Bittner S, Othman AE, Collorone S, Toosy AT, Meuth SG, Zipp F, Barkhof F, Ciccarelli O, Groppa S. Prognostic value of single-subject grey matter networks in early multiple sclerosis. Brain 2024; 147:135-146. [PMID: 37642541 PMCID: PMC10766234 DOI: 10.1093/brain/awad288] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/17/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023] Open
Abstract
The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.
Collapse
Affiliation(s)
- Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia, Hospital Universitari Vall d'Hebron, 08035 Barcelona, Spain
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Einar A Høgestøl
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Hanne F Harbo
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Barbara Bellenberg
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Serena Ruggieri
- Department of Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo-Forlanini Hospital, 00152 Rome, Italy
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Ahmed E Othman
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sara Collorone
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Ahmed T Toosy
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225 Düsseldorf, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Frederik Barkhof
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, 1100 DD Amsterdam, Netherlands
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| |
Collapse
|
13
|
Calvi A, Mendelsohn Z, Hamed W, Chard D, Tur C, Stutters J, MacManus D, Kanber B, Wheeler‐Kingshott CAMG, Barkhof F, Prados F. Treatment reduces the incidence of newly appearing multiple sclerosis lesions evolving into chronic active, slowly expanding lesions: A retrospective analysis. Eur J Neurol 2024; 31:e16092. [PMID: 37823722 PMCID: PMC11236028 DOI: 10.1111/ene.16092] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/05/2023] [Accepted: 09/21/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND AND PURPOSE Newly appearing lesions in multiple sclerosis (MS) may evolve into chronically active, slowly expanding lesions (SELs), leading to sustained disability progression. The aim of this study was to evaluate the incidence of newly appearing lesions developing into SELs, and their correlation to clinical evolution and treatment. METHODS A retrospective analysis of a fingolimod trial in primary progressive MS (PPMS; INFORMS, NCT00731692) was undertaken. Data were available from 324 patients with magnetic resonance imaging scans up to 3 years after screening. New lesions at year 1 were identified with convolutional neural networks, and SELs obtained through a deformation-based method. Clinical disability was assessed annually by Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test, Timed 25-Foot Walk, and Paced Auditory Serial Addition Test. Linear, logistic, and mixed-effect models were used to assess the relationship between the Jacobian expansion in new lesions and SELs, disability scores, and treatment status. RESULTS One hundred seventy patients had ≥1 new lesions at year 1 and had a higher lesion count at screening compared to patients with no new lesions (median = 27 vs. 22, p = 0.007). Among the new lesions (median = 2 per patient), 37% evolved into definite or possible SELs. Higher SEL volume and count were associated with EDSS worsening and confirmed disability progression. Treated patients had lower volume and count of definite SELs (β = -0.04, 95% confidence interval [CI] = -0.07 to -0.01, p = 0.015; β = -0.36, 95% CI = -0.67 to -0.06, p = 0.019, respectively). CONCLUSIONS Incident chronic active lesions are common in PPMS, and fingolimod treatment can reduce their number.
Collapse
Affiliation(s)
- Alberto Calvi
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Fundació Clinic per a la Recerca BiomèdicaBarcelonaSpain
| | - Zoe Mendelsohn
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Department of RadiologyCharité School of Medicine and University Hospital BerlinBerlinGermany
| | - Weaam Hamed
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Department of RadiologyMansoura University HospitalMansouraEgypt
| | - Declan Chard
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- National Institute for Health Research, Biomedical Research CentreUniversity College London HospitalsLondonUK
| | - Carmen Tur
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Neurology‐Neuroimmunology DepartmentMultiple Sclerosis Centre of Catalonia, Vall d'Hebron Barcelona Hospital CampusBarcelonaSpain
| | - Jon Stutters
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
| | - David MacManus
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
| | - Baris Kanber
- National Institute for Health Research, Biomedical Research CentreUniversity College London HospitalsLondonUK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image ComputingUniversity College LondonLondonUK
| | | | - Frederik Barkhof
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image ComputingUniversity College LondonLondonUK
- Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)Vrije UniversiteitAmsterdamthe Netherlands
| | - Ferran Prados
- NMR Research Unit, Institute of NeurologyUniversity College LondonLondonUK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image ComputingUniversity College LondonLondonUK
- e‐Health CentreUniversitat Oberta de CatalunyaBarcelonaSpain
| |
Collapse
|
14
|
Nakamura K, Elliott C, Lee H, Narayanan S, Arnold DL. Brain volume increase after discontinuing natalizumab therapy: Evidence for reversible pseudoatrophy. Mult Scler Relat Disord 2024; 81:105123. [PMID: 37976981 DOI: 10.1016/j.msard.2023.105123] [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: 12/12/2022] [Revised: 09/02/2023] [Accepted: 11/04/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND The phenomenon of pseudoatropy after initiation of anti-inflammatory therapy is believed to be reversible, but a rebound in brain volume following cessation of highly-effective therapy has not been reported. OBJECTIVES To evaluate brain volume change in a treatment interruption study (RESTORE) in which relapsing-remitting multiple sclerosis (RRMS) patients were randomized to switch from natalizumab to placebo, from natalizumab to once-monthly intravenous methylprednisolone (IVMP), or to remain on natalizumab. METHODS T2 lesion volume (T2LV), baseline normalized brain volumes, and follow-up percent brain volume changes (PBVC) were calculated. Approximate T2 relaxation-time (pT2) was calculated within the brain mask and the T2 lesions to estimate changes in water content. Linear mixed effects models were used to detect differences in T2LV, pT2 in whole brain, pT2 in T2-weighted lesions, and PBVC among the placebo, natalizumab, and IVMP groups. We also estimated contributions of T2LV and pT2 (in whole brain and T2 lesions) to PBVC. RESULTS T2LV increased in the placebo group (by 0.66 ml/year, p<0.0001) and IVMP (+1.98 ml/year, p = 0.05) groups relative to the natalizumab group. The rates of PBVC were significantly different: -0.239%/year with continued natalizumab and +0.126 %/year after switch to placebo (p = 0.03), while the IVMP group showed brain volume loss (-0.74 %/ year, p = 0.08). pT2 was not statistically different between the groups (p ≥ 0.29) and did not have significant effects on PBVC (p ≥ 0.25). CONCLUSION The increase in the brain volume in patients witching from natalizumab to placebo is consistent with reversal of so-called pseudoatrophy after starting natalizumab.
Collapse
Affiliation(s)
- Kunio Nakamura
- McConnell Brain Imaging Centre, Montreal Neurological Institute Hospital, and Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, Ohio 44195, USA.
| | - Colm Elliott
- Centre for Intelligent Machines, McGill University, 3480 Rue University, Montréal, QC H3A 2A7, Canada. NeuroRx Research, 3575 Park Avenue, Suite #5322, Montreal, Quebec H2 × 4B3, Canada; NeuroRx Research, 3575 Park Avenue, Suite #5322, Montreal, Quebec H2 × 4B3, Canada
| | - Hyunwoo Lee
- McConnell Brain Imaging Centre, Montreal Neurological Institute Hospital, and Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; Division of Neurology, Department of Medicine, University of British Columbia S154-2211 Wesbrook Mall, Vancouver, BC V6T2B5, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute Hospital, and Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; NeuroRx Research, 3575 Park Avenue, Suite #5322, Montreal, Quebec H2 × 4B3, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute Hospital, and Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; NeuroRx Research, 3575 Park Avenue, Suite #5322, Montreal, Quebec H2 × 4B3, Canada
| |
Collapse
|
15
|
Tahedl M, Wiltgen T, Voon CC, Berthele A, Kirschke JS, Hemmer B, Mühlau M, Zimmer C, Wiestler B. Cortical Thin Patch Fraction Reflects Disease Burden in MS: The Mosaic Approach. AJNR Am J Neuroradiol 2023; 45:82-89. [PMID: 38164526 PMCID: PMC10756581 DOI: 10.3174/ajnr.a8064] [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: 08/04/2023] [Accepted: 10/18/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND PURPOSE GM pathology plays an essential role in MS disability progression, emphasizing the importance of neuroradiologic biomarkers to capture the heterogeneity of cortical disease burden. This study aimed to assess the validity of a patch-wise, individual interpretation of cortical thickness data to identify GM pathology, the "mosaic approach," which was previously suggested as a biomarker for assessing and localizing atrophy. MATERIALS AND METHODS We investigated the mosaic approach in a cohort of 501 patients with MS with respect to 89 internal and 651 external controls. The resulting metric of the mosaic approach is the so-called thin patch fraction, which is an estimate of overall cortical disease burden per patient. We evaluated the mosaic approach with respect to the following: 1) discrimination between patients with MS and controls, 2) classification between different MS phenotypes, and 3) association with established biomarkers reflecting MS disease burden, using general linear modeling. RESULTS The thin patch fraction varied significantly between patients with MS and healthy controls and discriminated among MS phenotypes. Furthermore, the thin patch fraction was associated with disease burden, including the Expanded Disability Status Scale, cognitive and fatigue scores, and lesion volume. CONCLUSIONS This study demonstrates the validity of the mosaic approach as a neuroradiologic biomarker in MS. The output of the mosaic approach, namely the thin patch fraction, is a candidate biomarker for assessing and localizing cortical GM pathology. The mosaic approach can furthermore enhance the development of a personalized cortical MS biomarker, given that the thin patch fraction provides a feature on which artificial intelligence methods can be trained. Most important, we showed the validity of the mosaic approach when referencing data with respect to external control MR imaging repositories.
Collapse
Affiliation(s)
- Marlene Tahedl
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Tun Wiltgen
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Cui Ci Voon
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (B.H.), Munich, Germany
| | - Mark Mühlau
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| |
Collapse
|
16
|
Colato E, Prados F, Stutters J, Bianchi A, Narayanan S, Arnold DL, Wheeler-Kingshott C, Barkhof F, Ciccarelli O, Chard DT, Eshaghi A. Networks of microstructural damage predict disability in multiple sclerosis. J Neurol Neurosurg Psychiatry 2023; 94:992-1003. [PMID: 37468305 DOI: 10.1136/jnnp-2022-330203] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 06/13/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. METHODS We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. RESULTS We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). CONCLUSIONS GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials.
Collapse
Affiliation(s)
- Elisa Colato
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Jonathan Stutters
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Alessia Bianchi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Claudia Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Vrije Universiteit, Amsterdam, Netherlands
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Declan T Chard
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Arman Eshaghi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| |
Collapse
|
17
|
Nold AK, Wittayer M, Weber CE, Platten M, Gass A, Eisele P. Short-term brain atrophy evolution after initiation of immunotherapy in a real-world multiple sclerosis cohort. J Neuroimaging 2023; 33:904-908. [PMID: 37491626 DOI: 10.1111/jon.13146] [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: 07/11/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND AND PURPOSE In multiple sclerosis (MS), brain atrophy measurements have emerged as an important biomarker reflecting neurodegeneration and disability progression. However, due to several potential confounders, investigation of brain atrophy in clinical routine and even in controlled clinical studies can be challenging. The aim of this study was to investigate the short-term dynamics of brain atrophy development after initiation of disease-modifying therapy (DMT) in a "real-world setting." METHODS In this retrospective study, we included MS patients starting DMT (natalizumab, fingolimod, dimethyl fumarate, or interferon-ß1a) or without DMT, availability of a baseline MRI, and two annual follow-up scans on the same MRI system. Two-timepoint percentage brain volume changes (PBVCs) were calculated. RESULTS Fifty-five MS patients (12 patients starting DMT with natalizumab, 7 fingolimod, 14 dimethyl fumarate, 11 interferon-ß1a, and 11 patients without DMT) were included. We found the highest PBVCs in the first 12 months after initiation of natalizumab treatment. Furthermore, the PBVCs in our study were very much comparable to the results observed by other groups, as well as for fingolimod, dimethyl fumarate, and interferon-ß1a. CONCLUSION We found PBVCs that are comparable to the results of previous studies, suggesting that brain atrophy, assessed on 3D MRI data sets acquired on the same 3T MRI, provides a robust MS biomarker.
Collapse
Affiliation(s)
- Ann-Kathrin Nold
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Claudia E Weber
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Philipp Eisele
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| |
Collapse
|
18
|
Sormani MP, Schiavetti I, Ponzano M, Colato E, De Stefano N. Treatment Effect on Brain Atrophy Correlates with Treatment Effect on Cognition in Multiple Sclerosis. Ann Neurol 2023; 94:925-932. [PMID: 37496368 DOI: 10.1002/ana.26751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 07/09/2023] [Accepted: 07/17/2023] [Indexed: 07/28/2023]
Abstract
OBJECTIVE The purpose of this study was to evaluate the extent to which treatment effect on magnetic resonance imaging (MRI)-derived measures of brain atrophy and focal lesions can mediate, at the trial level, the treatment effect on cognitive outcomes in multiple sclerosis (MS). METHODS We collected all published randomized clinical trials in MS lasting at least 2 years and including as end points: active MRI lesions (defined as new/enlarging T2 lesions), brain atrophy (defined as a change in brain volume between month 12 and month 24), and change in cognitive performance (assessed by the Paced Auditory Serial Addition Test [PASAT]). Relative reductions were used to quantify the treatment effect on MRI markers (lesions and atrophy), whereas the standardized mean difference (Hedges g) between baseline and follow-up cognitive assessment was used to quantify the treatment effects on cognition. A linear regression, weighted for trial size, was used to assess the relationship between the treatment effects on MRI markers and cognition. RESULTS Fourteen trials including more than 8,813 patients with MS were included in the meta-regression. Treatment effect on cognition was strongly associated with the treatment effect on brain atrophy (R2 = 0.79, p < 0.001), but was not correlated with the treatment effect on active MRI lesions (R2 = 0.16, p = 0.14). INTERPRETATION Results reported here suggest that brain atrophy, a well-established MRI marker in MS clinical trials, can be used as a main outcome for clinical trials with drugs targeting cognitive impairment and neurodegeneration. ANN NEUROL 2023;94:925-932.
Collapse
Affiliation(s)
- Maria Pia Sormani
- Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Irene Schiavetti
- Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy
| | - Marta Ponzano
- Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Elisa Colato
- Department of Anatomy and Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Nicola De Stefano
- Department of Medicine Surgery and Neuroscience, University of Siena, Siena, Italy
| |
Collapse
|
19
|
Bazzurri V, Fiore A, Curti E, Tsantes E, Franceschini A, Granella F. Prevalence of 2-year "No evidence of disease activity" (NEDA-3 and NEDA-4) in relapsing-remitting multiple sclerosis. A real-world study. Mult Scler Relat Disord 2023; 79:105015. [PMID: 37769430 DOI: 10.1016/j.msard.2023.105015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/17/2023] [Indexed: 09/30/2023]
Abstract
BACKGROUND No evidence of disease activity (NEDA) is becoming a gold standard in the evaluation of disease modifying therapies (DMT) in relapsing-remitting multiple sclerosis (RRMS). NEDA-3 status is the absence of relapses, new activity on brain MRI, and disability progression. NEDA-4 meets all NEDA-3 criteria plus lack of brain atrophy. OBJECTIVE Aim of this study was to investigate the prevalence of two-year NEDA-3, NEDA-4, six-month delayed NEDA-3 (6mdNEDA-3), and six-month delayed NEDA-4 (6mdNEDA-4) in a cohort of patients with RRMS. Six-month delayed measures were introduced to consider latency of action of drugs. METHODS Observational retrospective monocentric study. All the patients with RRMS starting DMT between 2015 and 2018, and with 2-year of follow-up, were included. Annualized brain volume loss (a-BVL) was calculated by SIENA software. RESULTS We included 108 patients, the majority treated with first line DMT. At 2-year follow-up, 35 % of patients were NEDA-3 (50 % 6mdNEDA-3), and 17 % NEDA-4 (28 % 6mdNEDA-4). Loss of NEDA-3 status was mainly driven by MRI activity (70 %), followed by relapses (56 %), and only minimally by disability progression (7 %). CONCLUSION In our cohort 2-year NEDA status, especially including lack of brain atrophy, was hard to achieve. Further studies are needed to establish the prognostic value of NEDA-3 and NEDA4 in the long-term follow-up.
Collapse
Affiliation(s)
- V Bazzurri
- Neurology Unit, Emergency Department, Guglielmo da Saliceto Hospital, Piacenza, Italy.
| | - A Fiore
- Department of Biomedical Metabolic and Neurosciences, University of Modena and Reggio Emilia, Italy
| | - E Curti
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy
| | - E Tsantes
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy
| | - A Franceschini
- Unit of Neurosciences, Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - F Granella
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy; Unit of Neurosciences, Department of Medicine and Surgery, University of Parma, Parma, Italy
| |
Collapse
|
20
|
Barnett M, Wang D, Beadnall H, Bischof A, Brunacci D, Butzkueven H, Brown JWL, Cabezas M, Das T, Dugal T, Guilfoyle D, Klistorner A, Krieger S, Kyle K, Ly L, Masters L, Shieh A, Tang Z, van der Walt A, Ward K, Wiendl H, Zhan G, Zivadinov R, Barnett Y, Wang C. A real-world clinical validation for AI-based MRI monitoring in multiple sclerosis. NPJ Digit Med 2023; 6:196. [PMID: 37857813 PMCID: PMC10587188 DOI: 10.1038/s41746-023-00940-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/29/2023] [Indexed: 10/21/2023] Open
Abstract
Modern management of MS targets No Evidence of Disease Activity (NEDA): no clinical relapses, no magnetic resonance imaging (MRI) disease activity and no disability worsening. While MRI is the principal tool available to neurologists for monitoring clinically silent MS disease activity and, where appropriate, escalating treatment, standard radiology reports are qualitative and may be insensitive to the development of new or enlarging lesions. Existing quantitative neuroimaging tools lack adequate clinical validation. In 397 multi-center MRI scan pairs acquired in routine practice, we demonstrate superior case-level sensitivity of a clinically integrated AI-based tool over standard radiology reports (93.3% vs 58.3%), relative to a consensus ground truth, with minimal loss of specificity. We also demonstrate equivalence of the AI-tool with a core clinical trial imaging lab for lesion activity and quantitative brain volumetric measures, including percentage brain volume loss (PBVC), an accepted biomarker of neurodegeneration in MS (mean PBVC -0.32% vs -0.36%, respectively), whereas even severe atrophy (>0.8% loss) was not appreciated in radiology reports. Finally, the AI-tool additionally embeds a clinically meaningful, experiential comparator that returns a relevant MS patient centile for lesion burden, revealing, in our cohort, inconsistencies in qualitative descriptors used in radiology reports. AI-based image quantitation enhances the accuracy of, and value-adds to, qualitative radiology reporting. Scaled deployment of these tools will open a path to precision management for patients with MS.
Collapse
Affiliation(s)
- Michael Barnett
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Dongang Wang
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Heidi Beadnall
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Antje Bischof
- Department of Neurology, University Hospital of Muenster, Muenster, Germany
| | - David Brunacci
- Department of Radiology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Helmut Butzkueven
- Department of Neurology, The Alfred Hospital, Melbourne, VIC, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - J William L Brown
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Mariano Cabezas
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Tilak Das
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Tej Dugal
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Synergy Radiology, Sydney, NSW, Australia
| | - Daniel Guilfoyle
- Department of Neurology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Alexander Klistorner
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Save Sight Institute, University of Sydney, Sydney, NSW, Australia
| | - Stephen Krieger
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kain Kyle
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Linda Ly
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
| | | | - Andy Shieh
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
| | - Zihao Tang
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Anneke van der Walt
- Department of Radiology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
- Department of Neurology, The Alfred Hospital, Melbourne, VIC, Australia
| | - Kayla Ward
- Department of Neurology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Heinz Wiendl
- Department of Neurology, University Hospital of Muenster, Muenster, Germany
| | - Geng Zhan
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | | | - Yael Barnett
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia
- Department of Radiology, St Vincent's Hospital, Sydney, NSW, Australia
| | - Chenyu Wang
- Sydney Neuroimaging Analysis Centre, Sydney, NSW, Australia.
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia.
| |
Collapse
|
21
|
Storelli L, Pagani E, Pantano P, Piervincenzi C, Tedeschi G, Gallo A, De Stefano N, Battaglini M, Rocca MA, Filippi M. Methods for Brain Atrophy MR Quantification in Multiple Sclerosis: Application to the Multicenter INNI Dataset. J Magn Reson Imaging 2023; 58:1221-1231. [PMID: 36661195 DOI: 10.1002/jmri.28616] [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: 11/21/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Current therapeutic strategies in multiple sclerosis (MS) target neurodegeneration. However, the integration of atrophy measures into the clinical scenario is still an unmet need. PURPOSE To compare methods for whole-brain and gray matter (GM) atrophy measurements using the Italian Neuroimaging Network Initiative (INNI) dataset. STUDY TYPE Retrospective (data available from INNI). POPULATION A total of 466 patients with relapsing-remitting MS (mean age = 37.3 ± 10 years, 323 women) and 279 healthy controls (HC; mean age = 38.2 ± 13 years, 164 women). FIELD STRENGTH/SEQUENCE A 3.0-T, T1-weighted (spin echo and gradient echo without gadolinium injection) and T2-weighted spin echo scans at baseline and after 1 year (170 MS, 48 HC). ASSESSMENT Structural Image Evaluation using Normalization of Atrophy (SIENA-X/XL; version 5.0.9), Statistical Parametric Mapping (SPM-v12); and Jim-v8 (Xinapse Systems, Colchester, UK) software were applied to all subjects. STATISTICAL TESTS In MS and HC, we evaluated the intraclass correlation coefficient (ICC) among FSL-SIENA(XL), SPM-v12, and Jim-v8 for cross-sectional whole-brain and GM tissue volumes and their longitudinal changes, the effect size according to the Cohen's d at baseline and the sample size requirement for whole-brain and GM atrophy progression at different power levels (lowest = 0.7, 0.05 alpha level). False discovery rate (Benjamini-Hochberg procedure) correction was applied. A P value <0.05 was considered statistically significant. RESULTS SPM-v12 and Jim-v8 showed significant agreement for cross-sectional whole-brain (ICC = 0.93 for HC and ICC = 0.84 for MS) and GM volumes (ICC = 0.66 for HC and ICC = 0.90) and longitudinal assessment of GM atrophy (ICC = 0.35 for HC and ICC = 0.59 for MS), while no significant agreement was found in the comparisons between whole-brain and GM volumes for SIENA-X/XL and both SPM-v12 (P = 0.19 and P = 0.29, respectively) and Jim-v8 (P = 0.21 and P = 0.32, respectively). SPM-v12 and Jim-v8 showed the highest effect size for cross-sectional GM atrophy (Cohen's d = -0.63 and -0.61). Jim-v8 and SIENA(XL) showed the smallest sample size requirements for whole-brain (58) and GM atrophy (152), at 0.7 power level. DATA CONCLUSION The findings obtained in this study should be considered when selecting the appropriate brain atrophy pipeline for MS studies. EVIDENCE LEVEL 4. TECHNICAL EFFICACY Stage 1.
Collapse
Affiliation(s)
- Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS NEUROMED, Pozzilli, Italy
| | | | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, 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, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| |
Collapse
|
22
|
Fuh-Ngwa V, Charlesworth JC, Zhou Y, van der Mei I, Melton PE, Broadley SA, Ponsonby AL, Simpson-Yap S, Lechner-Scott J, Taylor BV. The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study. Sci Rep 2023; 13:11584. [PMID: 37463930 DOI: 10.1038/s41598-023-38415-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023] Open
Abstract
The indirect contribution of multiple sclerosis (MS) relapses to disability worsening outcomes, and vice-versa, remains unclear. Disease modifying therapies (DMTs) are potential modulators of this association. Understanding how these endo-phenotypes interact may provide insights into disease pathogenesis and treatment practice in relapse-onset MS (ROMS). Utilising a unique, prospectively collected clinical data from a longitudinal cohort of 279 first demyelinating event cases followed for up to 15 years post-onset, we examined indirect associations between relapses and treatment and the risk of disability worsening, and vice-versa. Indirect association parameters were estimated using joint models for longitudinal and survival data. Early relapses within 2.5 years of MS onset predicted early disability worsening outcomes (HR = 3.45, C.I 2.29-3.61) per relapse, but did not contribute to long-term disability worsening thereinafter (HR = 0.21, C.I 0.15-0.28). Conversely, disability worsening outcomes significantly contributed to relapse risk each year (HR = 2.96, C.I 2.91-3.02), and persisted over time (HR = 3.34, C.I 2.90-3.86), regardless of DMT treatments. The duration of DMTs significantly reduced the hazards of relapses (1st-line DMTs: HR = 0.68, C.I 0.58-0.79; 3rd-line DMTs: HR = 0.37, C.I 0.32-0.44) and disability worsening events (1st-line DMTs: HR = 0.74, C.I 0.69-0.79; 3rd-line DMTs: HR = 0.90, C.I 0.85-0.95), respectively. Results from time-dynamic survival probabilities further revealed individuals having higher risk of future relapses and disability worsening outcomes, respectively. The study provided evidence that in ROMS, relapses accrued within 2.5 years of MS onset are strong indicators of disability worsening outcomes, but late relapses accrued 2.5 years post onset are not overt risk factors for further disability worsening. In contrast, disability worsening outcomes are strong positive predictors of current and subsequent relapse risk. Long-term DMT use and older age strongly influence the individual outcomes and their associations.
Collapse
Affiliation(s)
- Valery Fuh-Ngwa
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia.
| | - Jac C Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Yuan Zhou
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Ingrid van der Mei
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Phillip E Melton
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Simon A Broadley
- Menzies Health Institute Queensland and School of Medicine, Griffith University, Gold Coast, QLD, 4222, Australia
| | - Anne-Louise Ponsonby
- Florey Institute for Neuroscience and Mental Health, Parkville, VIC, 3052, Australia
| | - Steve Simpson-Yap
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
- Neuroepidemiology Unit, Center for Epidemiology and Biostatistics, The University of Melbourne School of Population & Global Health, Melbourne, VIC, 3053, Australia
| | - Jeannette Lechner-Scott
- School of Medicine and Public Health New Lambton, Hunter New England Health, New Lambton Heights, NSW, Australia
- Department of Neurology, The University of Newcastle Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Bruce V Taylor
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia.
| |
Collapse
|
23
|
Matthews PM, Gupta D, Mittal D, Bai W, Scalfari A, Pollock KG, Sharma V, Hill N. The association between brain volume loss and disability in multiple sclerosis: A systematic review. Mult Scler Relat Disord 2023; 74:104714. [PMID: 37068369 DOI: 10.1016/j.msard.2023.104714] [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: 12/19/2022] [Revised: 03/23/2023] [Accepted: 04/08/2023] [Indexed: 04/19/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, degenerative disease of the central nervous system that affects approximately 2.8 million people worldwide. Compelling evidence from observational studies and clinical trials indicates a strong association between brain volume loss (BVL) and the accumulation of disability in MS. However, the considerable heterogeneity in study designs and methods of assessment of BVL invites questions concerning the generalizability of the reported findings. Therefore, we conducted this systematic review to characterize the relationship between BVL and physical disability in patients with MS. METHODS A systematic literature search of MEDLINE and EMBASE databases was performed supplemented by gray literature searches. The following study designs were included: prospective/retrospective cohort, cross-sectional and case-control. Only English language articles published from 2010 onwards were eligible for final inclusion. There were no restrictions on MS subtype, age, or ethnicity. Of the 1620 citations retrieved by the structured searches, 50 publications met our screening criteria and were included in the final data set. RESULTS Across all BVL measures, there was considerable heterogeneity in studies regarding the underlying study population, the definitions of BVL and image analysis methodologies, the physical disability measure used, the measures of association reported and whether the analysis conducted was univariable or multivariable. A total of 36 primary studies providing data on the association between whole BVL and physical disability in MS collectively suggest that whole brain atrophy is associated with greater physical disability progression in MS patients. Similarly, a total of 15 primary studies providing data on the association between ventricular atrophy and physical disability in MS suggest that ventricular atrophy is associated with greater physical disability progression in MS patients. Along similar lines, the existing evidence based on a total of 13 primary studies suggests that gray matter atrophy is associated with greater physical disability progression in MS patients. Four primary studies suggest that corpus callosum atrophy is associated with greater physical disability progression in MS patients. The majority of the existing evidence (6 primary studies) suggests no association between white matter atrophy and physical disability in MS. It is difficult to assign a relationship between basal ganglia volume loss and physical disability as well as medulla oblongata width and physical disability in MS due to very limited data. CONCLUSION The evidence gathered from this systematic review, although very heterogeneous, suggests that whole brain atrophy is associated with greater physical disability progression in MS patients. Our review can help define future imaging biomarkers for physical disability progression and treatment monitoring in MS.
Collapse
Affiliation(s)
- Paul M Matthews
- Department of Brain Sciences and UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, DuCane Road, London, UK.
| | - Digant Gupta
- Bridge Medical Consulting Limited, 2 Marsault Court, 11 Kew Foot Road, Richmond, London, TW9 2SS, UK
| | - Deepali Mittal
- Bridge Medical Consulting Limited, 2 Marsault Court, 11 Kew Foot Road, Richmond, London, TW9 2SS, UK
| | - Wenjia Bai
- Department of Brain Sciences and UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, DuCane Road, London, UK; Department of Computing, Imperial College London, William Penny Building, South Kensington Campus, London, UK
| | - Antonio Scalfari
- Imperial College Healthcare Trust, Centre of Neuroscience, Department of Medicine, Charing Cross Hospital, Fulham Palace Rd, London W6 8RF, UK
| | - Kevin G Pollock
- Bristol-Myers Squibb, Uxbridge Business Park, Sanderson Road, Uxbridge, UB8 1DH, UK
| | - Vishal Sharma
- Bristol-Myers Squibb, Uxbridge Business Park, Sanderson Road, Uxbridge, UB8 1DH, UK
| | - Nathan Hill
- Bristol-Myers Squibb, Uxbridge Business Park, Sanderson Road, Uxbridge, UB8 1DH, UK
| |
Collapse
|
24
|
Recent Progress in the Identification of Early Transition Biomarkers from Relapsing-Remitting to Progressive Multiple Sclerosis. Int J Mol Sci 2023; 24:ijms24054375. [PMID: 36901807 PMCID: PMC10002756 DOI: 10.3390/ijms24054375] [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: 11/18/2022] [Revised: 02/12/2023] [Accepted: 02/15/2023] [Indexed: 02/25/2023] Open
Abstract
Despite extensive research into the pathophysiology of multiple sclerosis (MS) and recent developments in potent disease-modifying therapies (DMTs), two-thirds of relapsing-remitting MS patients transition to progressive MS (PMS). The main pathogenic mechanism in PMS is represented not by inflammation but by neurodegeneration, which leads to irreversible neurological disability. For this reason, this transition represents a critical factor for the long-term prognosis. Currently, the diagnosis of PMS can only be established retrospectively based on the progressive worsening of the disability over a period of at least 6 months. In some cases, the diagnosis of PMS is delayed for up to 3 years. With the approval of highly effective DMTs, some with proven effects on neurodegeneration, there is an urgent need for reliable biomarkers to identify this transition phase early and to select patients at a high risk of conversion to PMS. The purpose of this review is to discuss the progress made in the last decade in an attempt to find such a biomarker in the molecular field (serum and cerebrospinal fluid) between the magnetic resonance imaging parameters and optical coherence tomography measures.
Collapse
|
25
|
Association of volumetric MRI measures and disability in MS patients of the same age: Descriptions from a birth year cohort. Mult Scler Relat Disord 2023; 71:104568. [PMID: 36805177 DOI: 10.1016/j.msard.2023.104568] [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: 10/13/2022] [Revised: 01/20/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023]
Abstract
BACKGROUND AND OBJECTIVES Although MRI-based markers of neuroinflammation have proven crucial for the diagnosis of multiple sclerosis (MS), predicting clinical progression with inflammation remains difficult. Neurodegenerative markers such as brain volume loss show stronger clinical (predictive) correlations, but also harbor age-related variation that must be disentangled from disease duration. In this study we investigated how clinical disability is related to volumetric MRI measures in a cohort of MS patients and healthy controls (HC) of the same age: Project Y. METHODS This study included 234 MS patients born in 1966 and 112 HC born between 1965 and 1967 in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), nine hole peg test (9HPT), and timed 25 foot walking test (T25FWT). Volumes were quantified on 3T MRI as normalized whole brain (NBV) and regional gray matter (GM) volumes using the same scanner and MRI protocol: cortical (normalized cortical gray matter volume; NCGMV), deep (NDGMV), thalamic (NThalV), and cerebellar (NCbV) GM volumes. In addition, mean upper cervical cord area (MUCCA), white matter lesion volume (LV), and spinal cord lesions were assessed. These measures were compared between patients and HC, and related to disability measures using linear regression. RESULTS Mean age of people with MS (PwMS) was 52.8 years (SD 0.9) and median disease duration 15.8 years (IQR 8.7-24.8). All global and regional brain measures were lower in MS patients compared to HC. Univariate regression models showed that NDGMV (β = -0.20) and MUCCA (β = -0.38) were most strongly related to the EDSS in all PwMS. After subtype stratification, MUCCA was most strongly related to the EDSS (β = -0.60) and 9HPT (β = -0.55) in secondary progressive PwMS. Multivariate regression models demonstrated that in all PwMS, the EDSS was best explained by lower MUCCA, longer disease durations and a progressive disease course (adjusted-R (Sastre-Garriga et al., 2017) = 0.26, p < 0.001). MUCCA was a consistent correlate in separate models of the EDSS for all PwMS, relapsing and progressive onset PwMS. The 9HPT (adjusted-R (Sastre-Garriga et al., 2017) = 0.20, p < 0.001) was best explained by lower MUCCA, higher LV and pack years, while lower limb disability (adjusted-R (Sastre-Garriga et al., 2017) = 0.11, p < 0.001) was best explained by lower MUCCA, progressive onset MS and female sex. DISCUSSION Our results indicate that in a cohort unbiased by age differences, spinal cord and deep gray matter volumes best related to physical disability. Our results support the use of these measures in clinical practice and trials.
Collapse
|
26
|
Cortese R, Battaglini M, Sormani MP, Luchetti L, Gentile G, Inderyas M, Alexandri N, De Stefano N. Reduction in grey matter atrophy in patients with relapsing multiple sclerosis following treatment with cladribine tablets. Eur J Neurol 2023; 30:179-186. [PMID: 36168741 PMCID: PMC10091690 DOI: 10.1111/ene.15579] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/15/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND PURPOSE Measures of atrophy in the whole brain can be used to reliably assess treatment effect in clinical trials of patients with multiple sclerosis (MS). Trials assessing the effect of treatment on grey matter (GM) and white matter (WM) atrophy are very informative, but hindered by technical limitations. This study aimed to measure GM and WM volume changes, using a robust longitudinal method, in patients with relapsing MS randomized to cladribine tablets 3.5 mg/kg or placebo in the CLARITY study. METHODS We analysed T1-weighted magnetic resonance sequences using SIENA-XL, from 0 to 6 months (cladribine, n = 267; placebo, n = 265) and 6 to 24 months (cladribine, n = 184; placebo, n = 186). Mean percentage GM and WM volume changes (PGMVC and PWMVC) were compared using a mixed-effect model. RESULTS More GM and WM volume loss was found in patients taking cladribine versus those taking placebo in the first 6 months of treatment (PGMVC: cladribine: -0.53 vs. placebo: -0.25 [p = 0.045]; PWMVC: cladribine: -0.49 vs. placebo: -0.34 [p = 0.137]), probably due to pseudoatrophy. However, over the period 6 to 24 months, GM volume loss was significantly lower in patients on cladribine than in those on placebo (PGMVC: cladribine: -0.90 vs. placebo: -1.27 [p = 0.026]). In this period, volume changes in WM were similar in the two treatment arms (p = 0.52). CONCLUSIONS After a short period of pseudoatrophy, treatment with cladribine 3.5 mg/kg significantly reduced GM atrophy in comparison with placebo. This supports the relevance of GM damage in MS and may have important implications for physical and cognitive disability progression.
Collapse
Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | - Maria Pia Sormani
- Department of Health Sciences, University of Genoa and Ospedale Policlinico San Martino IRCCS, Genoa, Italy
| | - Ludovico Luchetti
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | - Giordano Gentile
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | - Maira Inderyas
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | | | - Nicola De Stefano
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| |
Collapse
|
27
|
Skorve E, Lundervold AJ, Torkildsen Ø, Riemer F, Grüner R, Myhr KM. Brief international cognitive assessment for MS (BICAMS) and global brain volumes in early stages of MS - A longitudinal correlation study. Mult Scler Relat Disord 2023; 69:104398. [PMID: 36462469 DOI: 10.1016/j.msard.2022.104398] [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: 12/27/2021] [Revised: 08/04/2022] [Accepted: 11/03/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Cognitive impairment is common in patients with multiple sclerosis, even in the early stages of the disease. The Brief International Cognitive Assessment for multiple sclerosis (BICAMS) is a short screening tool developed to assess cognitive function in everyday clinical practice. OBJECTIVE To investigate associations between volumetric brain measures derived from a magnetic resonance imaging (MRI) examination and performance on BICAMS subtests in early stages of multiple sclerosis (MS). METHODS BICAMS was used to assess cognitive function in 49 MS patients at baseline and after one and two years. The patients were separated into two groups (with or without cognitive impairment) based on their performances on BICAMSs subtests. MRI data were analysed by a software tool (MSMetrix), yielding normalized measures of global brain volumes and lesion volumes. Associations between cognitive tests and brain MRI measures were analysed by running correlation analyses, and differences between subgroups and changes over time with independent and paired samples tests, respectively. RESULTS The strongest baseline correlations were found between the BICAMS subtests and normalized whole brain volume (NBV) and grey matter volume (NGV); processing speed r = 0.54/r = 0.48, verbal memory r = 0.49/ r = 0.42, visual memory r = 0.48 /r = 0.39. Only the verbal memory test had significant correlations with T2 and T1 lesion volumes (LV) at both time points; T2LV r = 0.39, T1LV r = 0.38. There were significant loss of grey matter and white matter volume overall (NGV p<0.001, NWV p = 0.003), as well as an increase in T1LV (p = 0.013). The longitudinally defined confirmed cognitively impaired (CCI) and preserved (CCP) patients showed significant group differences on all MRI volume measures at both time points, except for NWV. Only the CCI subgroup showed significant white matter atrophy (p = 0.006) and increase in T2LV (p = 0.029). CONCLUSIONS The present study found strong correlations between whole brain and grey matter volumes and performance on the BICAMS subtests as well as significant changes in global volumes from baseline to follow-up with clear differences between patients defined as cognitively impaired and preserved at both baseline and follow-up.
Collapse
Affiliation(s)
- Ellen Skorve
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway.
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Øivind Torkildsen
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Frank Riemer
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway; Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Renate Grüner
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Physics and Technology, University of Bergen, N-5007 Bergen, Norway
| | - Kjell-Morten Myhr
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| |
Collapse
|
28
|
Younger DS. Multiple sclerosis: Motor dysfunction. HANDBOOK OF CLINICAL NEUROLOGY 2023; 196:119-147. [PMID: 37620066 DOI: 10.1016/b978-0-323-98817-9.00016-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Multiple sclerosis is a chronic neurological disease characterized by inflammation and degeneration within the central nervous system. Over the course of the disease, most MS patients successively accumulate inflammatory lesions, axonal damage, and diffuse CNS pathology, along with an increasing degree of motor disability. While the pharmacological approach to MS targets inflammation to decrease relapse rates and relieve symptoms, disease-modifying therapy and immunosuppressive medications may not prevent the accumulation of pathology in most patients leading to long-term motor disability. This has been met with recent interest in promoting plasticity-guided concepts, enhanced by neurophysiological and neuroimaging approaches to address the preservation of motor function.
Collapse
Affiliation(s)
- David S Younger
- Department of Clinical Medicine and Neuroscience, CUNY School of Medicine, New York, NY, United States; Department of Medicine, Section of Internal Medicine and Neurology, White Plains Hospital, White Plains, NY, United States.
| |
Collapse
|
29
|
Loonstra FC, de Ruiter LRJ, Koel-Simmelink MJA, Schoonheim MM, Strijbis EMM, Moraal B, Barkhof F, Uitdehaag BMJ, Teunissen C, Killestein J. Neuroaxonal and Glial Markers in Patients of the Same Age With Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 10:10/2/e200078. [PMID: 36543540 PMCID: PMC9773420 DOI: 10.1212/nxi.0000000000200078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/01/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND AND OBJECTIVES The specificity of novel blood biomarkers for multiple sclerosis (MS)-related neurodegeneration is unclear because neurodegeneration also occurs during normal aging. To understand which aspects of neurodegeneration the serum biomarkers neurofilament light (sNfL), serum glial fibrillary acidic protein (sGFAP), and serum contactin-1 (sCNTN1) reflect, we here explore their cross-sectional association with disability outcome measures and MRI volumes in a unique cohort of people with MS (PwMS) of the same age. METHODS sNfL, sGFAP (both singe-molecule array technology) and sCNTN1 (Luminex) were measured in serum samples of 288 PwMS and 125 healthy controls (HCs) of the Project Y cohort, a population-based cross-sectional study of PwMS born in the Netherlands in 1966 and age-matched HC. RESULTS sNfL (9.83 pg/mL [interquartile range {IQR}: 7.8-12.0]) and sGFAP (63.7 pg/mL [IQR: 48.5-84.5]) were higher in PwMS compared with HC (sNfL: 8.8 pg/mL [IQR: 7.0-10.5]; sGFAP: 51.7 pg/mL [IQR: 40.1-68.3]) (p < 0.001), whereas contactin-1 (7,461.3 pg/mL [IQR: 5,951.8-9,488.6]) did not significantly differ between PwMS compared with HC (7,891.2 pg/mL [IQR: 6,120.0-10,265.8]) (p = 0.068). sNfL and sGFAP levels were 1.2-fold higher in secondary progressive patients (SPMS) compared with relapsing remitting patients (p = 0.009 and p = 0.043). Stratified by MS subtype, no relations were seen for CNTN1, whereas sNfL and sGFAP correlated with the Expanded Disability Status Scale (ρ = 0.43 and ρ = 0.39), Nine-Hole Peg Test, Timed 25-Foot Walk Test, and Symbol Digit Modalities Test (average ρ = 0.38) only in patients with SPMS. Parallel to these clinical findings, correlations were only found for sNfL and sGFAP with MRI volumes. The strongest correlations were observed between sNfL and thalamic volume (ρ = -0.52) and between sGFAP with deep gray matter volume (ρ = - 0.56) in primary progressive patients. DISCUSSION In our cohort of patients of the same age, we report consistent correlations of sNfL and sGFAP with a range of metrics, especially in progressive MS, whereas contactin-1 was not related to clinical or MRI measures. This demonstrates the potential of sNfL and sGFAP as complementary biomarkers of neurodegeneration, reflected by disability, in progressive MS.
Collapse
Affiliation(s)
- Floor C Loonstra
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom.
| | - Lodewijk R J de Ruiter
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Marleen J A Koel-Simmelink
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Menno M Schoonheim
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Eva M M Strijbis
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Bastiaan Moraal
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Frederik Barkhof
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Bernard M J Uitdehaag
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Charlotte Teunissen
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Joep Killestein
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| |
Collapse
|
30
|
Lauerer M, Bussas M, Pongratz V, Berthele A, Kirschke JS, Wiestler B, Zimmer C, Hemmer B, Mühlau M. Percentage brain volume change in multiple sclerosis mainly reflects white matter and cortical volume. Ann Clin Transl Neurol 2022; 10:130-135. [PMID: 36427289 PMCID: PMC9852382 DOI: 10.1002/acn3.51700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/24/2022] [Accepted: 11/02/2022] [Indexed: 11/26/2022] Open
Abstract
Brain atrophy in multiple sclerosis (MS), as measured by percentage brain volume change (PBVC) from brain magnetic resonance imaging (MRI), has been established as an outcome parameter in clinical trials. It is unknown to what extent volume changes within different brain tissue compartments contribute to PBVC. We analyzed pairs of MRI scans (at least 6 months apart) in 600 patients with relapsing-remitting MS. Multiple regression revealed that PBVC mainly reflects volume loss of white and cortical gray matter, while deep gray matter and white matter lesions were less represented. Our findings aid the interpretation of PBVC changes in MS.
Collapse
Affiliation(s)
- Markus Lauerer
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany,TUM‐Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Matthias Bussas
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany,TUM‐Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Viola Pongratz
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany,TUM‐Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Achim Berthele
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Jan S Kirschke
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Benedikt Wiestler
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Claus Zimmer
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Bernhard Hemmer
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany,Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | - Mark Mühlau
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany,TUM‐Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| |
Collapse
|
31
|
Siger M. Magnetic Resonance Imaging in Primary Progressive Multiple Sclerosis Patients : Review. Clin Neuroradiol 2022; 32:625-641. [PMID: 35258820 PMCID: PMC9424179 DOI: 10.1007/s00062-022-01144-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 11/29/2021] [Indexed: 11/21/2022]
Abstract
The recently developed effective treatment of primary progressive multiple sclerosis (PPMS) requires the accurate diagnosis of patients with this type of disease. Currently, the diagnosis of PPMS is based on the 2017 McDonald criteria, although the contribution of magnetic resonance imaging (MRI) to this process is fundamental. PPMS, one of the clinical types of MS, represents 10%-15% of all MS patients. Compared to relapsing-remitting MS (RRMS), PPMS differs in terms of pathology, clinical presentation and MRI features. Regarding conventional MRI, focal lesions on T2-weighted images and acute inflammatory lesions with contrast enhancement are less common in PPMS than in RRMS. On the other hand, MRI features of chronic inflammation, such as slowly evolving/expanding lesions (SELs) and leptomeningeal enhancement (LME), and brain and spinal cord atrophy are more common MRI characteristics in PPMS than RRMS. Nonconventional MRI also shows differences in subtle white and grey matter damage between PPMS and other clinical types of disease. In this review, we present separate diagnostic criteria, conventional and nonconventional MRI specificity for PPMS, which may support and simplify the diagnosis of this type of MS in daily clinical practice.
Collapse
Affiliation(s)
- Malgorzata Siger
- Department of Neurology, Medical University of Łódź, 22 Kopcinskiego Str., 90-153, Łódź, Poland.
| |
Collapse
|
32
|
Cellular senescence in neuroinflammatory disease: new therapies for old cells? Trends Mol Med 2022; 28:850-863. [DOI: 10.1016/j.molmed.2022.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 07/08/2022] [Accepted: 07/22/2022] [Indexed: 11/23/2022]
|
33
|
Zivadinov R, Bergsland N, Jakimovski D, Weinstock-Guttman B, Benedict RHB, Riolo J, Silva D, Dwyer MG. Thalamic atrophy measured by artificial intelligence in a multicentre clinical routine real-word study is associated with disability progression. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2022-329333. [PMID: 35902228 DOI: 10.1136/jnnp-2022-329333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/28/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND The thalamus is a key grey matter structure, and sensitive marker of neurodegeneration in multiple sclerosis (MS). Previous reports indicated that thalamic volumetry using artificial intelligence (AI) on clinical-quality T2-fluid-attenuated inversion recovery (FLAIR) images alone is fast and reliable. OBJECTIVE To investigate whether thalamic volume (TV) loss, measured longitudinally by AI, is associated with disability progression (DP) in patients with MS, participating in a large multicentre study. METHODS The DeepGRAI (Deep Grey Rating via Artificial Intelligence) Registry is a multicentre (30 USA sites), longitudinal, observational, retrospective, real-word study of relapsing-remitting (RR) MS patients. Each centre enrolled between 30 and 35 patients. Brain MRI exams acquired at baseline and follow-up on 1.5T or 3T scanners with no prior standardisation were collected. TV measurement was performed on T2-FLAIR using DeepGRAI, and on two dimensional (D)-weighted and 3D T1-weighted images (WI) by using FMRIB's Integrated Registration and Segmentation Tool software where possible. RESULTS 1002 RRMS patients were followed for an average of 2.6 years. Longitudinal TV analysis was more readily available on T2-FLAIR (96.1%), compared with 2D-T1-WI (61.8%) or 3D-T1-WI (33.2%). Over the follow-up, DeepGRAI TV loss was significantly higher in patients with DP, compared with those with disability improvement (DI) or disease stability (-1.35% in DP, -0.87% in DI and -0.57% in Stable, p=0.045, Bonferroni-adjusted, age-adjusted and follow-up time-adjusted analysis of covariance). In a regression model including MRI scanner change, age, sex, disease duration and follow-up time, DP was associated with DeepGRAI TV loss (p=0.022). CONCLUSIONS Thalamic atrophy measured by AI in a multicentre clinical routine real-word setting is associated with DP over mid-term follow-up.
Collapse
Affiliation(s)
- Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging at Clinical and Translational Science Institute, University of Buffalo, State University of New York, Buffalo, New York, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
| | - Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
| | - Bianca Weinstock-Guttman
- Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, New Jersey, USA
| | - Ralph H B Benedict
- Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, New Jersey, USA
| | - Jon Riolo
- Bristol Myers Squibb, New Jersey, USA
| | | | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging at Clinical and Translational Science Institute, University of Buffalo, State University of New York, Buffalo, New York, USA
| |
Collapse
|
34
|
Brune S, Høgestøl EA, de Rodez Benavent SA, Berg-Hansen P, Beyer MK, Leikfoss IS, Bos SD, Sowa P, Brunborg C, Andorra M, Pulido Valdeolivas I, Asseyer S, Brandt A, Chien C, Scheel M, Blennow K, Zetterberg H, Kerlero de Rosbo N, Paul F, Uccelli A, Villoslada P, Berge T, Harbo HF. Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis. Mult Scler 2022; 28:1859-1870. [PMID: 35658739 PMCID: PMC9493412 DOI: 10.1177/13524585221097296] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting
neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL
to predict outcomes in real-world MS cohorts requires further
validation. Objective: The aim of the study is to investigate the associations of sNfL
concentration, magnetic resonance imaging (MRI) and retinal optical
coherence tomography (OCT) markers with disease worsening in a longitudinal
European multicentre MS cohort. Methods: MS patients (n = 309) were prospectively enrolled at four
centres and re-examined after 2 years (n = 226). NfL
concentration was measured by single molecule array assay in serum. The
patients’ phenotypes were thoroughly characterized with clinical
examination, retinal OCT and MRI brain scans. The primary outcome was
disease worsening at median 2-year follow-up. Results: Patients with high sNfL concentrations (⩾8 pg/mL) at baseline had increased
risk of disease worsening at median 2-year follow-up (odds ratio (95%
confidence interval) = 2.8 (1.5–5.3), p = 0.001). We found
no significant associations of MRI or OCT measures at baseline with risk of
disease worsening. Conclusion: Serum NfL concentration was the only factor associated with disease
worsening, indicating that sNfL is a useful biomarker in MS that might be
relevant in a clinical setting.
Collapse
Affiliation(s)
- Synne Brune
- Institute of clinical Medicine, University of Oslo, Oslo, Norway/Department of Neurology, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Einar A Høgestøl
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway/Department of Neurology, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Pål Berg-Hansen
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Mona K Beyer
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway/Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ingvild Sørum Leikfoss
- Department of Neurology, Oslo University Hospital, Oslo, Norway/Department of Research, Innovation and Education, Oslo University Hospital, Oslo, Norway
| | - Steffan D Bos
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway/Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Cathrine Brunborg
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Magi Andorra
- Institut d'Investigacions Biomediques August Pi Sunyer, Barcelona, Spain
| | | | - Susanna Asseyer
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Alexander Brandt
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany/NeuroCure Clinical Research Center, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany/NeuroCure Clinical Research Center, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany/Department of Neuroradiology, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden/Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden/Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK/UK Dementia Research Institute at UCL, London, UK/Hong Kong Center for Neurodegenerative Diseases, Shatin, Hong Kong, China
| | - Nicole Kerlero de Rosbo
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany/NeuroCure Clinical Research Center, Charité-Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Antonio Uccelli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy/Center of Excellence for Biomedical Research, University of Genoa, Genoa, Italy/IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Pablo Villoslada
- Institut d'Investigacions Biomediques August Pi Sunyer, Barcelona, Spain
| | - Tone Berge
- Department of Research, Innovation and Education, Oslo University Hospital, Oslo, Norway/Department of Mechanical, Electronic and Chemical Engineering, Oslo Metropolitan University, Oslo, Norway
| | - Hanne F Harbo
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway/Department of Neurology, Oslo University Hospital, Oslo, Norway
| |
Collapse
|
35
|
Calvi A, Tur C, Chard D, Stutters J, Ciccarelli O, Cortese R, Battaglini M, Pietroboni A, De Riz M, Galimberti D, Scarpini E, De Stefano N, Prados F, Barkhof F. Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis. Neuroimage Clin 2022; 35:103048. [PMID: 35598462 PMCID: PMC9130104 DOI: 10.1016/j.nicl.2022.103048] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/25/2022] [Accepted: 05/12/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion's metrics and clinical outcomes in relapse-onset MS has not been widely investigated. OBJECTIVES To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. METHODS 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). RESULTS Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p < 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p < 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI -0.005 to -0.003, p < 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed-effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95%CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). CONCLUSIONS SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity and MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS.
Collapse
Affiliation(s)
- Alberto Calvi
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom,Corresponding author.
| | - Carmen Tur
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom,Neurology-Neuroimmunology Department, Multiple Sclerosis Centre of Catalonia (Cemcat), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Declan Chard
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom
| | - Jonathan Stutters
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom
| | - Rosa Cortese
- Dep. of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Marco Battaglini
- Dep. of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Anna Pietroboni
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, University of Milan, Italy,Department of Biomedical, Surgical and Dental Sciences, University of Milan, Centro Dino Ferrari, Milan, Italy
| | - Milena De Riz
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, University of Milan, Italy,Department of Biomedical, Surgical and Dental Sciences, University of Milan, Centro Dino Ferrari, Milan, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, University of Milan, Italy,Department of Biomedical, Surgical and Dental Sciences, University of Milan, Centro Dino Ferrari, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, University of Milan, Italy,Department of Biomedical, Surgical and Dental Sciences, University of Milan, Centro Dino Ferrari, Milan, Italy
| | - Nicola De Stefano
- Dep. of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Ferran Prados
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom,e-Health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Frederik Barkhof
- Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), United Kingdom,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom,Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| |
Collapse
|
36
|
Cagol A, Schaedelin S, Barakovic M, Benkert P, Todea RA, Rahmanzadeh R, Galbusera R, Lu PJ, Weigel M, Melie-Garcia L, Ruberte E, Siebenborn N, Battaglini M, Radue EW, Yaldizli Ö, Oechtering J, Sinnecker T, Lorscheider J, Fischer-Barnicol B, Müller S, Achtnichts L, Vehoff J, Disanto G, Findling O, Chan A, Salmen A, Pot C, Bridel C, Zecca C, Derfuss T, Lieb JM, Remonda L, Wagner F, Vargas MI, Du Pasquier R, Lalive PH, Pravatà E, Weber J, Cattin PC, Gobbi C, Leppert D, Kappos L, Kuhle J, Granziera C. Association of Brain Atrophy With Disease Progression Independent of Relapse Activity in Patients With Relapsing Multiple Sclerosis. JAMA Neurol 2022; 79:682-692. [PMID: 35575778 DOI: 10.1001/jamaneurol.2022.1025] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance The mechanisms driving neurodegeneration and brain atrophy in relapsing multiple sclerosis (RMS) are not completely understood. Objective To determine whether disability progression independent of relapse activity (PIRA) in patients with RMS is associated with accelerated brain tissue loss. Design, Setting, and Participants In this observational, longitudinal cohort study with median (IQR) follow-up of 3.2 years (2.0-4.9), data were acquired from January 2012 to September 2019 in a consortium of tertiary university and nonuniversity referral hospitals. Patients were included if they had regular clinical follow-up and at least 2 brain magnetic resonance imaging (MRI) scans suitable for volumetric analysis. Data were analyzed between January 2020 and March 2021. Exposures According to the clinical evolution during the entire observation, patients were classified as those presenting (1) relapse activity only, (2) PIRA episodes only, (3) mixed activity, or (4) clinical stability. Main Outcomes and Measures Mean difference in annual percentage change (MD-APC) in brain volume/cortical thickness between groups, calculated after propensity score matching. Brain atrophy rates, and their association with the variables of interest, were explored with linear mixed-effect models. Results Included were 1904 brain MRI scans from 516 patients with RMS (67.4% female; mean [SD] age, 41.4 [11.1] years; median [IQR] Expanded Disability Status Scale score, 2.0 [1.5-3.0]). Scans with insufficient quality were excluded (n = 19). Radiological inflammatory activity was associated with increased atrophy rates in several brain compartments, while an increased annualized relapse rate was linked to accelerated deep gray matter (GM) volume loss. When compared with clinically stable patients, patients with PIRA had an increased rate of brain volume loss (MD-APC, -0.36; 95% CI, -0.60 to -0.12; P = .02), mainly driven by GM loss in the cerebral cortex. Patients who were relapsing presented increased whole brain atrophy (MD-APC, -0.18; 95% CI, -0.34 to -0.02; P = .04) with respect to clinically stable patients, with accelerated GM loss in both cerebral cortex and deep GM. No differences in brain atrophy rates were measured between patients with PIRA and those presenting relapse activity. Conclusions and Relevance Our study shows that patients with RMS and PIRA exhibit accelerated brain atrophy, especially in the cerebral cortex. These results point to the need to recognize the insidious manifestations of PIRA in clinical practice and to further evaluate treatment strategies for patients with PIRA in clinical trials.
Collapse
Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Pascal Benkert
- Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ramona-Alexandra Todea
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Division of Diagnostic and Interventional Neuroradiology, Clinic for Radiology and Nuclear Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Reza Rahmanzadeh
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Medical Image Analysis Center (MIAC) and Quantitative Biomedical Imaging Group, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Nina Siebenborn
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Ernst-Wilhelm Radue
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Özgür Yaldizli
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Johanna Oechtering
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Tim Sinnecker
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Medical Image Analysis Center (MIAC) and Quantitative Biomedical Imaging Group, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Johannes Lorscheider
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Bettina Fischer-Barnicol
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Stefanie Müller
- Department of Neurology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Lutz Achtnichts
- Department of Neurology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Jochen Vehoff
- Department of Neurology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Giulio Disanto
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland
| | - Oliver Findling
- Department of Neurology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Andrew Chan
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Anke Salmen
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Caroline Pot
- Division of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Claire Bridel
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Chiara Zecca
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Tobias Derfuss
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Johanna M Lieb
- Division of Diagnostic and Interventional Neuroradiology, Clinic for Radiology and Nuclear Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Luca Remonda
- Department of Radiology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Franca Wagner
- Department of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Maria I Vargas
- Department of Radiology, Faculty of Medicine, Geneva University Hospital, Geneva, Switzerland
| | - Renaud Du Pasquier
- Division of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland.,Division of Radiology, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Patrice H Lalive
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Emanuele Pravatà
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Department of Neuroradiology, Neurocenter of Southern Switzerland, Lugano, Switzerland
| | - Johannes Weber
- Department of Radiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Philippe C Cattin
- Center for Medical Image, Analysis, and Navigation, Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Claudio Gobbi
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - David Leppert
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, 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, University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| |
Collapse
|
37
|
Cavedo E, Tran P, Thoprakarn U, Martini JB, Movschin A, Delmaire C, Gariel F, Heidelberg D, Pyatigorskaya N, Ströer S, Krolak-Salmon P, Cotton F, Dos Santos CL, Dormont D. Validation of an automatic tool for the rapid measurement of brain atrophy and white matter hyperintensity: QyScore®. Eur Radiol 2022; 32:2949-2961. [PMID: 34973104 PMCID: PMC9038894 DOI: 10.1007/s00330-021-08385-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 09/15/2021] [Accepted: 10/21/2021] [Indexed: 12/05/2022]
Abstract
OBJECTIVES QyScore® is an imaging analysis tool certified in Europe (CE marked) and the US (FDA cleared) for the automatic volumetry of grey and white matter (GM and WM respectively), hippocampus (HP), amygdala (AM), and white matter hyperintensity (WMH). Here we compare QyScore® performances with the consensus of expert neuroradiologists. METHODS Dice similarity coefficient (DSC) and the relative volume difference (RVD) for GM, WM volumes were calculated on 50 3DT1 images. DSC and the F1 metrics were calculated for WMH on 130 3DT1 and FLAIR images. For each index, we identified thresholds of reliability based on current literature review results. We hypothesized that DSC/F1 scores obtained using QyScore® markers would be higher than the threshold. In contrast, RVD scores would be lower. Regression analysis and Bland-Altman plots were obtained to evaluate QyScore® performance in comparison to the consensus of three expert neuroradiologists. RESULTS The lower bound of the DSC/F1 confidence intervals was higher than the threshold for the GM, WM, HP, AM, and WMH, and the higher bounds of the RVD confidence interval were below the threshold for the WM, GM, HP, and AM. QyScore®, compared with the consensus of three expert neuroradiologists, provides reliable performance for the automatic segmentation of the GM and WM volumes, and HP and AM volumes, as well as WMH volumes. CONCLUSIONS QyScore® represents a reliable medical device in comparison with the consensus of expert neuroradiologists. Therefore, QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases. KEY POINTS • QyScore® provides reliable automatic segmentation of brain structures in comparison with the consensus of three expert neuroradiologists. • QyScore® automatic segmentation could be performed on MRI images using different vendors and protocols of acquisition. In addition, the fast segmentation process saves time over manual and semi-automatic methods. • QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases.
Collapse
Affiliation(s)
- Enrica Cavedo
- Qynapse SAS, 130 rue de Lourmel, 75015, Paris, France.
| | - Philippe Tran
- Qynapse SAS, 130 rue de Lourmel, 75015, Paris, France
- Equipe-Projet ARAMIS, ICM, CNRS UMR 7225, Inserm U1117, Sorbonne Université UMR_S 1127, Centre Inria de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, Faculté de Médecine Sorbonne Université, Paris, France
| | | | | | | | | | - Florent Gariel
- Department of Neuroradiology, University Hospital of Bordeaux, Bordeaux, France
| | - Damien Heidelberg
- Faculty of Medicine, Claude-Bernard Lyon 1 University, 69000, Lyon, France
- Service de Radiologie and Laboratoire d'anatomie de Rockefeller, centre hospitalier Lyon Sud, hospices civils de Lyon, 69000, Lyon, France
| | - Nadya Pyatigorskaya
- Department of Neuroradiology, Groupe Hospitalier Pitié-Salpêtrière, AP-HP, Sorbonne Université UMR_S 1127, Paris, France
| | - Sébastian Ströer
- Department of Neuroradiology, Groupe Hospitalier Pitié-Salpêtrière, AP-HP, Sorbonne Université UMR_S 1127, Paris, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Centre of Lyon, Hospices Civils de Lyon, Lyon, France
- University of Lyon, Lyon, France
- INSERM, U1028; UMR CNRS 5292, Lyon Neuroscience Research Center, Lyon, France
| | - Francois Cotton
- Radiology Department, centre hospitalier Lyon-Sud, hospices civils de Lyon, 69310, Pierre-Bénite, France
- Inserm U1044, CNRS UMR 5220, CREATIS, Université Lyon-1, 69100, Villeurbanne, France
| | | | - Didier Dormont
- Equipe-Projet ARAMIS, ICM, CNRS UMR 7225, Inserm U1117, Sorbonne Université UMR_S 1127, Centre Inria de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, Faculté de Médecine Sorbonne Université, Paris, France
- Department of Neuroradiology, Groupe Hospitalier Pitié-Salpêtrière, AP-HP, Sorbonne Université UMR_S 1127, Paris, France
| |
Collapse
|
38
|
Calvi A, Carrasco FP, Tur C, Chard DT, Stutters J, De Angelis F, John N, Williams T, Doshi A, Samson RS, MacManus D, Gandini Wheeler-Kingshott CA, Ciccarelli O, Chataway J, Barkhof F. Association of Slowly Expanding Lesions on MRI With Disability in People With Secondary Progressive Multiple Sclerosis. Neurology 2022; 98:e1783-e1793. [PMID: 35277438 DOI: 10.1212/wnl.0000000000200144] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 01/18/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE To explore the relationship between slowly expanding lesions (SELs) on MRI and disability in secondary progressive multiple sclerosis (SPMS). METHODS We retrospectively studied 345 patients with SPMS enrolled in the MS-SMART trial. They underwent brain MRI at baseline and at 24 and 96 weeks. Definite SELs were defined as concentrically expanding T2 lesions, as assessed by nonlinear deformation of volumetric T1-weighted images. Associations of SEL volumes with other MRI metrics and disability were assessed through Pearson correlations and regression analyses. RESULTS Averaged across patients, 29% of T2 lesions were classified as being definite SELs. A greater volume of definite SELs correlated with a higher total baseline T2 lesion volume (r = 0.55, p < 0.001) and percentage brain volume reduction (r = -0.26, p < 0.001), a higher number of new persisting T1 black holes (r = 0.19, p < 0.001), and, in a subset of 106 patients, with a greater reduction in magnetization transfer ratio (adjusted difference 0.52, p < 0.001). In regression analyses, a higher definite SEL volume was associated with increasing disability, as assessed by the Expanded Disability Status Scale (β = 0.23, p = 0.020), z scores of the Multiple Sclerosis Functional Composite (β = -0.47, p = 0.048), Timed 25-Foot Walk Test (β = -2.10, p = 0.001), and Paced Auditory Serial Addition Task (β = -0.27, p = 0.006), and increased risk of disability progression (odds ratio 1.92, p = 0.025). DISCUSSION Definite SELs represent almost one-third of T2 lesions in SPMS. They are associated with neurodegenerative MRI markers and related to clinical worsening, suggesting that they may contribute to disease progression and be a new target for therapeutic interventions.
Collapse
Affiliation(s)
- Alberto Calvi
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Ferran Prados Carrasco
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Carmen Tur
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Declan T Chard
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Jonathan Stutters
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Floriana De Angelis
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Nevin John
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Thomas Williams
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Anisha Doshi
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Rebecca S Samson
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - David MacManus
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Claudia A Gandini Wheeler-Kingshott
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Olga Ciccarelli
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Jeremy Chataway
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Frederik Barkhof
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | | |
Collapse
|
39
|
Nakamura K, Mokliatchouk O, Arnold DL, Yousry TA, Kappos L, Richert N, Ayling-Rouse K, Miller C, Fisher E. Effects of Dimethyl Fumarate on Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: Pooled Analysis Phase 3 DEFINE and CONFIRM Studies. Front Neurol 2022; 13:809273. [PMID: 35370887 PMCID: PMC8973916 DOI: 10.3389/fneur.2022.809273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Objective In the pivotal DEFINE and CONFIRM trials for dimethyl fumarate (DMF), patterns of brain volume changes were different, potentially due to low sample sizes and because MRIs were analyzed at two different reading centers. We evaluated effects of DMF on brain volume change in patients with multiple sclerosis (MS) through reanalysis of pooled images from DEFINE/CONFIRM trials in one reading center. Methods MRIs from DEFINE/CONFIRM at weeks 0, 24, 48, and 96 from patients randomized to twice-daily DMF or placebo (PBO) were reanalyzed at the Cleveland Clinic to measure brain parenchymal fraction (BPF). To account for pseudoatrophy, brain volume estimates were re-baselined to calculate changes for weeks 48–96. Results Across studies, 301 and 314 patients receiving DMF and PBO, respectively, had analyzable MRIs. In weeks 0–48, mean ± SE percentage change in BPF was −0.44 ± 0.04 vs. −0.34 ± 0.04% in DMF vs. PBO, respectively, whereas in weeks 48–96, mean ± SE percentage change in BPF was −0.27 ± 0.03 vs. −0.41 ± 0.04% in DMF vs. PBO, respectively. The mixed-effect model for repeated measures showed similar results: in weeks 48–96, estimated change (95% confidence interval) in BPF was −0.0021 (−0.0027, −0.0016) for DMF vs. −0.0033 (−0.0039, −0.0028) for PBO (35.9% reduction; p = 0.0025). Conclusions The lower rate of whole brain volume loss with DMF in this pooled BPF analysis in the second year vs. PBO is consistent with its effects on relapses, disability, and MRI lesions. Brain volume changes in the first year may be explained by pseudoatrophy effects also described in other MS clinical trials.
Collapse
Affiliation(s)
- Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | | | - Douglas L. Arnold
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Tarek A. Yousry
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Institute of Neurology, London, United Kingdom
| | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland
| | | | | | | | - Elizabeth Fisher
- Biogen, Cambridge, MA, United States
- *Correspondence: Elizabeth Fisher
| |
Collapse
|
40
|
Tommasin S, Iakovleva V, Rocca MA, Giannì C, Tedeschi G, De Stefano N, Pozzilli C, Filippi M, Pantano P. Relation of sensorimotor and cognitive cerebellum functional connectivity with brain structural damage in patients with multiple sclerosis and no disability. Eur J Neurol 2022; 29:2036-2046. [PMID: 35298059 PMCID: PMC9323479 DOI: 10.1111/ene.15329] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/11/2022] [Accepted: 02/27/2022] [Indexed: 12/01/2022]
Abstract
Background and purpose To investigate the relationship between the functional connectivity (FC) of the sensorimotor and cognitive cerebellum and measures of structural damage in patients with multiple sclerosis (MS) and no physical disability. Methods We selected 144 relapsing–remitting MS patients with an Expanded Disability Status Scale score of ≤1.5 and 98 healthy controls from the Italian Neuroimaging Network Initiative database. From multimodal 3T magnetic resonance imaging (MRI), including functional MRI at rest, we calculated lesion load, cortical thickness, and white matter, cortical gray matter, and caudate, putamen, thalamic, and cerebellar volumes. Voxel‐wise FC of the sensorimotor and cognitive cerebellum was assessed with seed‐based analysis, and multiple regression analysis was used to evaluate the relationship between FC and structural damage. Results Whole brain, white matter, caudate, putamen, and thalamic volumes were reduced in patients compared to controls, whereas cortical gray matter was not significantly different in patients versus controls. Both the sensorimotor and cognitive cerebellum showed a widespread pattern of increased and decreased FC that were negatively associated with structural measures, indicating that the lower the FC, the greater the tissue loss. Lastly, among multiple structural measures, cortical gray matter and white matter volumes were the best predictors of cerebellar FC alterations. Conclusions Increased and decreased cerebellar FC with several brain areas coexist in MS patients with no disability. Our data suggest that white matter loss hampers FC, whereas, in the absence of atrophy, cortical volume represents the framework for FC to increase.
Collapse
Affiliation(s)
- Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | | | - Maria Assunta 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
| | | | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences and MRI-Center "SUN-FISM", University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Carlo Pozzilli
- Department of Human Neurosciences, Sapienza University of Rome, Rome, 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.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy.,IRCCS NEUROMED, Pozzilli, Italy
| | | |
Collapse
|
41
|
Gärtner J, Hauser SL, Bar-Or A, Montalban X, Cohen JA, Cross AH, Deiva K, Ganjgahi H, Häring DA, Li B, Pingili R, Ramanathan K, Su W, Willi R, Kieseier B, Kappos L. Efficacy and safety of ofatumumab in recently diagnosed, treatment-naive patients with multiple sclerosis: Results from ASCLEPIOS I and II. Mult Scler 2022; 28:1562-1575. [PMID: 35266417 PMCID: PMC9315184 DOI: 10.1177/13524585221078825] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background: In the phase III ASCLEPIOS I and II trials, participants with relapsing
multiple sclerosis receiving ofatumumab had significantly better clinical
and magnetic resonance imaging (MRI) outcomes than those receiving
teriflunomide. Objectives: To assess the efficacy and safety of ofatumumab versus teriflunomide in
recently diagnosed, treatment-naive (RDTN) participants from ASCLEPIOS. Methods: Participants were randomized to receive ofatumumab (20 mg subcutaneously
every 4 weeks) or teriflunomide (14 mg orally once daily) for up to
30 months. Endpoints analysed post hoc in the protocol-defined RDTN
population included annualized relapse rate (ARR), confirmed disability
worsening (CDW), progression independent of relapse activity (PIRA) and
adverse events. Results: Data were analysed from 615 RDTN participants (ofatumumab:
n = 314; teriflunomide: n = 301). Compared
with teriflunomide, ofatumumab reduced ARR by 50% (rate ratio (95%
confidence interval (CI)): 0.50 (0.33, 0.74);
p < 0.001), and delayed 6-month CDW by 46% (hazard ratio
(HR; 95% CI): 0.54 (0.30, 0.98); p = 0.044) and 6-month
PIRA by 56% (HR: 0.44 (0.20, 1.00); p = 0.049). Safety
findings were manageable and consistent with those of the overall ASCLEPIOS
population. Conclusion: The favourable benefit–risk profile of ofatumumab versus teriflunomide
supports its consideration as a first-line therapy in RDTN patients. ASCLEPIOS I and II are registered at ClinicalTrials.gov (NCT02792218 and
NCT02792231).
Collapse
Affiliation(s)
- Jutta Gärtner
- Department of Paediatrics and Adolescent Medicine, Division of Paediatric Neurology, University Medical Centre Göttingen, Georg August University Göttingen, Göttingen, Germany
| | - Stephen L Hauser
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California - San Francisco, San Francisco, CA, USA
| | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xavier Montalban
- Department of Neurology-Neuroimmunology, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jeffrey A Cohen
- Department of Neurology, Mellen MS Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Anne H Cross
- Department of Neurology, Section of Neuroimmunology, Washington University School of Medicine, St Louis, MO, USA
| | - Kumaran Deiva
- Department of Pediatric Neurology, University Hospitals Paris Saclay, Hôpital Bicêtre, National Reference Center for Rare Inflammatory Brain and Spinal Diseases, Le Kremlin-Bicêtre, France
| | - Habib Ganjgahi
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK/Statistics Department, University of Oxford, Oxford, UK
| | | | - Bingbing Li
- Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA
| | | | | | - Wendy Su
- Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA
| | | | | | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) and MS Center, and Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital of Basel, University of Basel, Basel, Switzerland
| |
Collapse
|
42
|
Newsome SD, Scott TF, Arnold DL, Altincatal A, Naylor ML. Early treatment responses to peginterferon beta-1a are associated with longer-term clinical outcomes in patients with relapsing-remitting multiple sclerosis: Subgroup analyses of ADVANCE and ATTAIN. Mult Scler Relat Disord 2022; 57:103367. [PMID: 35158473 DOI: 10.1016/j.msard.2021.103367] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 09/28/2021] [Accepted: 11/01/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND Early intervention with well-tolerated disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS) is recommended in order to delay disease progression, reduce neurologic damage, preserve brain volume, and optimize long-term patient outcomes. Lack of conversion of new/newly enlarging T2 (NET2) or gadolinium-enhancing (Gd+) lesions to chronic hypointensities (black hole conversion) and achievement of no evidence of disease activity (NEDA) early in the course of treatment are considered potential indicators of treatment effect and predictors of longer-term clinical outcomes. METHODS Patients with RRMS who were treated with peginterferon beta-1a in the 2-year ADVANCE phase 3 clinical trial (NCT0090639) and its 2-year open-label extension study, ATTAIN (NCT01332019), were grouped as newly diagnosed (diagnosed ≤1 year prior to enrollment and DMT naive) or non-newly diagnosed. For analyses of the impact of early treatment and disease activity control, the newly diagnosed and non-newly diagnosed subgroups were further divided based on whether they initiated peginterferon beta-1a every 2 weeks (Q2W) starting in study year 1 (continuously treated) or peginterferon beta-1a Q2W or every 4 weeks in study year 2 (delayed treatment). Patient subgroups were evaluated for conversion of NET2 or Gd+ lesions to persistent black holes (PBHs), brain atrophy (percentage change in whole brain volume [WBV]), achievement of NEDA composite outcomes, and the association of these disease activity measures with longer-term clinical outcomes (annualized relapse rate [ARR] and confirmed disability worsening [CDW]). RESULTS At 2 years, significantly fewer PBHs developed from NET2 lesions or Gd+ lesions in newly diagnosed and non-newly diagnosed patients continuously treated with peginterferon beta-1a than in the corresponding delayed-treatment groups (all p<0.0001). Percentage decrease in WBV from 6 months (rebaselined) to 2 years was significantly lower for newly diagnosed and non-newly diagnosed patients who received continuous peginterferon beta-1a treatment than for patients who received delayed treatment (both p ≤ 0.0442). In study year 1, a higher proportion of newly diagnosed and non-newly diagnosed patients treated with peginterferon beta-1a than those treated with placebo achieved NEDA (newly diagnosed: 28.3% vs 13.5% [p = 0.0010]; non-newly diagnosed: 40.8% vs 15.8% [p<0.0001]). NEDA rates remained stable over study years 2-4 for the newly diagnosed (range: 50.0%-53.9%) and non-newly diagnosed (range: 54.4%-57.0%) subgroups. Patients without PBH conversion had significantly lower ARR at 2 years (newly diagnosed: p = 0.0109; non-newly diagnosed: p = 0.0044) and a lower proportion of patients with 12-week CDW at 2 years (newly diagnosed: p = 0.2787; non-newly diagnosed: p = 0.0045) than the corresponding patient subgroups with PBH conversion. Patients who achieved NEDA in ADVANCE (study years 1-2) had a significantly lower ARR in ATTAIN (study years 3-4) than patients who did not achieve NEDA (newly diagnosed, p = 0.0003; non-newly diagnosed, p = 0.0001). Over 4 years, safety outcomes did not differ for the newly diagnosed and non-newly diagnosed patient subgroups. CONCLUSIONS These results indicate that newly diagnosed and non-newly diagnosed patients treated continuously with peginterferon beta-1a Q2W experienced better disease control over time than those who received delayed treatment. Patients with NEDA or evidence of less radiological disease activity in the first 2 years of treatment had better longer-term clinical outcomes than those with evidence of greater disease activity.
Collapse
Affiliation(s)
- Scott D Newsome
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
| | - Thomas F Scott
- Department of Neurology, Allegheny General Hospital, Pittsburgh, PA, USA
| | - Douglas L Arnold
- Montreal Neurological Institute, McGill University, and NeuroRx Research, Montreal, QC, Canada
| | | | - Maria L Naylor
- Biogen, Cambridge, MA, USA, at the time of these analyses
| |
Collapse
|
43
|
Mangesius S, Haider L, Lenhart L, Steiger R, Prados Carrasco F, Scherfler C, Gizewski ER. Qualitative and Quantitative Comparison of Hippocampal Volumetric Software Applications: Do All Roads Lead to Rome? Biomedicines 2022; 10:biomedicines10020432. [PMID: 35203641 PMCID: PMC8962257 DOI: 10.3390/biomedicines10020432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/30/2022] [Accepted: 02/10/2022] [Indexed: 02/06/2023] Open
Abstract
Brain volumetric software is increasingly suggested for clinical routine. The present study quantifies the agreement across different software applications. Ten cases with and ten gender- and age-adjusted healthy controls without hippocampal atrophy (median age: 70; 25–75% range: 64–77 years and 74; 66–78 years) were retrospectively selected from a previously published cohort of Alzheimer’s dementia patients and normal ageing controls. Hippocampal volumes were computed based on 3 Tesla T1-MPRAGE-sequences with FreeSurfer (FS), Statistical-Parametric-Mapping (SPM; Neuromorphometrics and Hammers atlases), Geodesic-Information-Flows (GIF), Similarity-and-Truth-Estimation-for-Propagated-Segmentations (STEPS), and Quantib™. MTA (medial temporal lobe atrophy) scores were manually rated. Volumetric measures of each individual were compared against the mean of all applications with intraclass correlation coefficients (ICC) and Bland–Altman plots. Comparing against the mean of all methods, moderate to low agreement was present considering categorization of hippocampal volumes into quartiles. ICCs ranged noticeably between applications (left hippocampus (LH): from 0.42 (STEPS) to 0.88 (FS); right hippocampus (RH): from 0.36 (Quantib™) to 0.86 (FS). Mean differences between individual methods and the mean of all methods [mm3] were considerable (LH: FS −209, SPM-Neuromorphometrics −820; SPM-Hammers −1474; Quantib™ −680; GIF 891; STEPS 2218; RH: FS −232, SPM-Neuromorphometrics −745; SPM-Hammers −1547; Quantib™ −723; GIF 982; STEPS 2188). In this clinically relevant sample size with large spread in data ranging from normal aging to severe atrophy, hippocampal volumes derived by well-accepted applications were quantitatively different. Thus, interchangeable use is not recommended.
Collapse
Affiliation(s)
- Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, Russell Square House, Russell Square 10-12, London WC1B 5EH, UK;
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria
- Correspondence:
| | - Lukas Lenhart
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Ruth Steiger
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, Russell Square House, Russell Square 10-12, London WC1B 5EH, UK;
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, UK
- e-Health Centre, Universitat Oberta de Catalunya, Rambla del Poblenou 156, 08018 Barcelona, Spain
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria;
| | - Elke R. Gizewski
- Department of Neuroradiology, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; (S.M.); (L.L.); (R.S.); (E.R.G.)
- Neuroimaging Core Facility, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria
| |
Collapse
|
44
|
Patti F, Chisari CG, Toscano S, Arena S, Finocchiaro C, Cimino V, Milone G. Autologous Hematopoietic Stem Cell Transplantation in Multiple Sclerosis Patients: Monocentric Case Series and Systematic Review of the Literature. J Clin Med 2022; 11:jcm11040942. [PMID: 35207216 PMCID: PMC8875789 DOI: 10.3390/jcm11040942] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/01/2022] [Accepted: 02/02/2022] [Indexed: 02/05/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic, inflammatory and immune-mediated disease of the central nervous system (CNS), commonly affecting young adults and potentially associated with life-long disability. About 14 disease-modifying treatments (DMTs) are currently approved for the treatment of MS. However, despite the use of highly effective therapies, some patients exhibit a highly active disease with an aggressive course from onset and a higher risk of long-term disability accrual. In the last few years, several retrospective studies, clinical trials, meta-analyses and systematic reviews have investigated autologous hematopoietic stem cell transplantation (AHSCT) as a possible therapeutic option in order to address this unmet clinical need. These studies demonstrated that AHSCT is a highly efficacious and relatively safe therapeutic option for the treatment of highly active MS. Particularly, over recent years, the amount of evidence has grown, with significant improvements in the development of patient selection criteria, choice of the most suitable transplant technique and clinical experience. In this paper, we present six patients who received AHSCT in our MS center and we systematically reviewed recent evidence about the long-term efficacy and safety of AHSCT and the placement of AHSCT in the rapidly evolving therapeutic armamentarium for MS.
Collapse
Affiliation(s)
- Francesco Patti
- Department of Medical, Surgical Sciences and Advanced Technologies “G.F. Ingrassia”, University of Catania, 95125 Catania, Italy; (S.T.); (S.A.); (C.F.)
- Correspondence: (F.P.); (C.G.C.); Tel.: +39-09-5378-2620 (F.P.)
| | - Clara Grazia Chisari
- Department of Medical, Surgical Sciences and Advanced Technologies “G.F. Ingrassia”, University of Catania, 95125 Catania, Italy; (S.T.); (S.A.); (C.F.)
- Correspondence: (F.P.); (C.G.C.); Tel.: +39-09-5378-2620 (F.P.)
| | - Simona Toscano
- Department of Medical, Surgical Sciences and Advanced Technologies “G.F. Ingrassia”, University of Catania, 95125 Catania, Italy; (S.T.); (S.A.); (C.F.)
| | - Sebastiano Arena
- Department of Medical, Surgical Sciences and Advanced Technologies “G.F. Ingrassia”, University of Catania, 95125 Catania, Italy; (S.T.); (S.A.); (C.F.)
| | - Chiara Finocchiaro
- Department of Medical, Surgical Sciences and Advanced Technologies “G.F. Ingrassia”, University of Catania, 95125 Catania, Italy; (S.T.); (S.A.); (C.F.)
| | - Vincenzo Cimino
- IRCCS Centro Neurolesi “Bonino Pulejo”, 98124 Messina, Italy;
| | - Giuseppe Milone
- Hematology and Bone Marrow Transplant Unit, Azienda Policlinico-Vittorio Emanuele, 95124 Catania, Italy;
| |
Collapse
|
45
|
No Changes in Functional Connectivity After Dimethyl Fumarate Treatment in Multiple Sclerosis. Neurol Ther 2022; 11:471-479. [PMID: 35119678 PMCID: PMC8857342 DOI: 10.1007/s40120-022-00328-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 01/19/2022] [Indexed: 11/06/2022] Open
Abstract
Introduction Despite the increased availability of disease-modifying therapies (DMTs) for treating relapsing-remitting multiple sclerosis (RR-MS), only a few studies have evaluated DMT-associated brain functional changes. Methods We investigated whether significant resting-state functional connectivity (FC) changes occurred in RR-MS patients after 6 and 12 months of dimethyl fumarate (DMF) treatment using both a seed-based and data-driven approach. Results Thirty patients were followed up after 6 months of therapy, and 27 of them reached a 12-month follow-up. Three patients at baseline and only one after 12 months showed gadolinium-enhancing lesions. We did not find any significant FC changes after therapy at either time point. After 12 months of DMF, we observed relatively modest brain volume loss and a significant improvement in Paced Auditory Serial Addition Test 3 s and 25-Foot Walk Test scores. Conclusion The absence of FC changes could be due to the low degree of baseline inflammation in our patients, though we cannot exclude that more time may be required to observe such changes. No FC changes may reflect a beneficial effect of DMF therapy, as supported by conventional MRI findings and clinical improvement.
Collapse
|
46
|
Giovannoni G, Popescu V, Wuerfel J, Hellwig K, Iacobaeus E, Jensen MB, García-Domínguez JM, Sousa L, De Rossi N, Hupperts R, Fenu G, Bodini B, Kuusisto HM, Stankoff B, Lycke J, Airas L, Granziera C, Scalfari A. Smouldering multiple sclerosis: the 'real MS'. Ther Adv Neurol Disord 2022; 15:17562864211066751. [PMID: 35096143 PMCID: PMC8793117 DOI: 10.1177/17562864211066751] [Citation(s) in RCA: 81] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/28/2021] [Indexed: 12/25/2022] Open
Abstract
Using a philosophical approach or deductive reasoning, we challenge the dominant clinico-radiological worldview that defines multiple sclerosis (MS) as a focal inflammatory disease of the central nervous system (CNS). We provide a range of evidence to argue that the 'real MS' is in fact driven primarily by a smouldering pathological disease process. In natural history studies and clinical trials, relapses and focal activity revealed by magnetic resonance imaging (MRI) in MS patients on placebo or on disease-modifying therapies (DMTs) were found to be poor predictors of long-term disease evolution and were dissociated from disability outcomes. In addition, the progressive accumulation of disability in MS can occur independently of relapse activity from early in the disease course. This scenario is underpinned by a more diffuse smouldering pathological process that may affect the entire CNS. Many putative pathological drivers of smouldering MS can be potentially modified by specific therapeutic strategies, an approach that may have major implications for the management of MS patients. We hypothesise that therapeutically targeting a state of 'no evident inflammatory disease activity' (NEIDA) cannot sufficiently prevent disability accumulation in MS, meaning that treatment should also focus on other brain and spinal cord pathological processes contributing to the slow loss of neurological function. This should also be complemented with a holistic approach to the management of other systemic disease processes that have been shown to worsen MS outcomes.
Collapse
Affiliation(s)
- Gavin Giovannoni
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark St., Whitechapel, London E1 2AT, UK
| | - Veronica Popescu
- Universitair MS Centrum, Hasselt, Belgium; Noorderhart Hospital, Pelt, Belgium; Hasselt University, Hasselt, Belgium
| | - Jens Wuerfel
- MIAC AG, Department of Biomedical Engineering, University of Basel, Basel, Switzerland; Charité - University Medicine Berlin, Berlin, Germany
| | - Kerstin Hellwig
- Katholisches Klinikum Bochum, Klinikum der Ruhr-Universität, Bochum, Germany
| | | | - Michael B Jensen
- Department of Neurology, Nordsjællands Hospital, Hillerød, Denmark
| | | | - Livia Sousa
- Centro Hospitalar e Universitário de Coimbra, Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
| | | | - Raymond Hupperts
- Zuyderland Medisch Centrum, Sittard-Geleen, The Netherlands; Maastricht University Medical Center, Maastricht, The Netherlands
| | - Giuseppe Fenu
- Department of Neurology, Brotzu Hospital, Cagliari, Italy
| | - Benedetta Bodini
- Paris Brain Institute, Sorbonne University, Paris, France; Department of Neurology, APHP, Saint-Antoine Hospital, Paris, France
| | - Hanna-Maija Kuusisto
- Department of Neurology, Tampere University Hospital, Tampere, Finland; Department of Customer and Patient Safety, University of Eastern Finland, Kuopio, Finland
| | - Bruno Stankoff
- Paris Brain Institute, Sorbonne University, ICM, CNRS, Inserm, Paris, France; APHP, Saint-Antoine Hospital, Paris, France
| | - Jan Lycke
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | | | - Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antonio Scalfari
- Centre for Neuroscience, Department of Medicine, Charing Cross Hospital, Imperial College London, London, UK
| |
Collapse
|
47
|
Temmerman J, Van Der Veken F, Engelborghs S, Guldolf K, Nagels G, Smeets D, Allemeersch GJ, Costers L, D’hooghe MB, Vanbinst AM, Van Schependom J, Bjerke M, D’haeseleer M. Brain Volume Loss Can Occur at the Rate of Normal Aging in Patients with Multiple Sclerosis Who Are Free from Disease Activity. J Clin Med 2022; 11:jcm11030523. [PMID: 35159972 PMCID: PMC8836909 DOI: 10.3390/jcm11030523] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 02/05/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory demyelinating and degenerative disorder of the central nervous system. Accelerated brain volume loss (BVL) has emerged as a promising magnetic resonance imaging marker (MRI) of neurodegeneration, correlating with present and future clinical disability. We have systematically selected MS patients fulfilling ‘no evidence of disease activity-3′ (NEDA-3) criteria under high-efficacy disease-modifying treatment (DMT) from the database of two Belgian MS centers. BVL between both MRI scans demarcating the NEDA-3 period was assessed and compared with a group of prospectively recruited healthy volunteers who were matched for age and gender. Annualized whole brain volume percentage change was similar between 29 MS patients achieving NEDA-3 and 24 healthy controls (−0.25 ± 0.49 versus −0.24 ± 0.20, p = 0.9992; median follow-up 21 versus 33 months; respectively). In contrast, we found a mean BVL increase of 72%, as compared with the former, in a second control group of MS patients (n = 21) whom had been excluded from the NEDA-3 group due to disease activity (p = 0.1371). Our results suggest that neurodegeneration in MS can slow down to the rate of normal aging once inflammatory disease activity has been extinguished and advocate for an early introduction of high-efficacy DMT to reduce the risk of future clinical disability.
Collapse
Affiliation(s)
- Joke Temmerman
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Department of Biomedical Sciences, Institute Born-Bunge, Universiteit Antwerpen, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Floris Van Der Veken
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
| | - Sebastiaan Engelborghs
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Department of Biomedical Sciences, Institute Born-Bunge, Universiteit Antwerpen, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Kaat Guldolf
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Department of Neurology, Onze-Lieve-Vrouw Ziekenhuis, Moorselbaan 164, 9300 Aalst, Belgium
| | - Guy Nagels
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Icometrix, Kolonel Begaultlaan 1b, 3012 Leuven, Belgium
| | - Dirk Smeets
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Icometrix, Kolonel Begaultlaan 1b, 3012 Leuven, Belgium
| | - Gert-Jan Allemeersch
- Department of Radiology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (G.-J.A.); (A.-M.V.)
| | - Lars Costers
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Icometrix, Kolonel Begaultlaan 1b, 3012 Leuven, Belgium
| | - Marie B. D’hooghe
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Nationaal Multiple Sclerose Centrum (NMSC), Vanheylenstraat 16, 1820 Melsbroek, Belgium
| | - Anne-Marie Vanbinst
- Department of Radiology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (G.-J.A.); (A.-M.V.)
| | - Jeroen Van Schependom
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
| | - Maria Bjerke
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Department of Biomedical Sciences, Institute Born-Bunge, Universiteit Antwerpen, Universiteitsplein 1, 2610 Antwerp, Belgium
- Laboratory of Clinical Neurochemistry, Department of Clinical Biology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium
| | - Miguel D’haeseleer
- Department of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090 Brussels, Belgium; (J.T.); (F.V.D.V.); (S.E.); (K.G.); (G.N.); (M.B.D.)
- Center for Neurosciences (C4N), NEUR and AIMS, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussel, Belgium; (D.S.); (L.C.); (J.V.S.); (M.B.)
- Nationaal Multiple Sclerose Centrum (NMSC), Vanheylenstraat 16, 1820 Melsbroek, Belgium
- Correspondence:
| |
Collapse
|
48
|
Casanova B, Quintanilla-Bordás C, Gascón F. Escalation vs. Early Intense Therapy in Multiple Sclerosis. J Pers Med 2022; 12:119. [PMID: 35055434 PMCID: PMC8778390 DOI: 10.3390/jpm12010119] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/28/2021] [Accepted: 01/01/2022] [Indexed: 02/01/2023] Open
Abstract
The treatment strategy of multiple sclerosis (MS) is a highly controversial debate. Currently, there are up to 19 drugs approved. However, there is no clear evidence to guide fundamental decisions such as what treatment should be chosen in first place, when treatment failure or suboptimal response should be considered, or what treatment should be considered in these cases. The "escalation strategy" consists of starting treatment with drugs of low side-effect profile and low efficacy, and "escalating" to drugs of higher efficacy-with more potential side-effects-if necessary. This strategy has prevailed over the years. However, the evidence supporting this strategy is based on short-term studies, in hope that the benefits will stand in the long term. These studies usually do not consider the heterogeneity of the disease and the limited effect that relapses have on the long-term. On the other hand, "early intense therapy" strategy refers to starting treatment with drugs of higher efficacy from the beginning, despite having a less favorable side-effect profile. This approach takes advantage of the so-called "window of opportunity" in hope to maximize the clinical benefits in the long-term. At present, the debate remains open. In this review, we will critically review both strategies. We provide a summary of the current evidence for each strategy without aiming to reach a definite conclusion.
Collapse
Affiliation(s)
- Bonaventura Casanova
- Unitat de Neuroimmunologia, Hospital Universitari i Politècnic La Fe. València, la Universitat de València, 46026 Valencia, Spain;
| | - Carlos Quintanilla-Bordás
- Unitat de Neuroimmunologia, Hospital Universitari i Politècnic La Fe. València, la Universitat de València, 46026 Valencia, Spain;
| | - Francisco Gascón
- Unitat de Neuroimmunologia, Hospital Clínic Universitari de València, 46010 Valencia, Spain;
| |
Collapse
|
49
|
Lublin FD, Häring DA, Ganjgahi H, Ocampo A, Hatami F, Čuklina J, Aarden P, Dahlke F, Arnold DL, Wiendl H, Chitnis T, Nichols TE, Kieseier BC, Bermel RA. OUP accepted manuscript. Brain 2022; 145:3147-3161. [PMID: 35104840 PMCID: PMC9536294 DOI: 10.1093/brain/awac016] [Citation(s) in RCA: 136] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/01/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Abstract
Patients with multiple sclerosis acquire disability either through relapse-associated worsening (RAW) or progression independent of relapse activity (PIRA). This study addresses the relative contribution of relapses to disability worsening over the course of the disease, how early progression begins and the extent to which multiple sclerosis therapies delay disability accumulation. Using the Novartis-Oxford multiple sclerosis (NO.MS) data pool spanning all multiple sclerosis phenotypes and paediatric multiple sclerosis, we evaluated ∼200 000 Expanded Disability Status Scale (EDSS) transitions from >27 000 patients with ≤15 years follow-up. We analysed three datasets: (i) A full analysis dataset containing all observational and randomized controlled clinical trials in which disability and relapses were assessed (n = 27 328); (ii) all phase 3 clinical trials (n = 8346); and (iii) all placebo-controlled phase 3 clinical trials (n = 4970). We determined the relative importance of RAW and PIRA, investigated the role of relapses on all-cause disability worsening using Andersen-Gill models and observed the impact of the mechanism of worsening and disease-modifying therapies on the time to reach milestone disability levels using time continuous Markov models. PIRA started early in the disease process, occurred in all phenotypes and became the principal driver of disability accumulation in the progressive phase of the disease. Relapses significantly increased the hazard of all-cause disability worsening events; following a year in which relapses occurred (versus a year without relapses), the hazard increased by 31–48% (all P < 0.001). Pre-existing disability and older age were the principal risk factors for incomplete relapse recovery. For placebo-treated patients with minimal disability (EDSS 1), it took 8.95 years until increased limitation in walking ability (EDSS 4) and 18.48 years to require walking assistance (EDSS 6). Treating patients with disease-modifying therapies delayed these times significantly by 3.51 years (95% confidence limit: 3.19, 3.96) and 3.09 years (2.60, 3.72), respectively. In patients with relapsing-remitting multiple sclerosis, those who worsened exclusively due to RAW events took a similar length of time to reach milestone EDSS values compared with those with PIRA events; the fastest transitions were observed in patients with PIRA and superimposed relapses. Our data confirm that relapses contribute to the accumulation of disability, primarily early in multiple sclerosis. PIRA begins in relapsing-remitting multiple sclerosis and becomes the dominant driver of disability accumulation as the disease evolves. Pre-existing disability and older age are the principal risk factors for further disability accumulation. The use of disease-modifying therapies delays disability accrual by years, with the potential to gain time being highest in the earliest stages of multiple sclerosis.
Collapse
Affiliation(s)
- Fred D Lublin
- Correspondence to: Professor Fred D. Lublin The Corinne Goldsmith Dickinson Center for Multiple Sclerosis Icahn School of Medicine at Mount Sinai 5 East 98th Street, Box 1138 New York, NY 10029-6574, USA E-mail:
| | | | - Habib Ganjgahi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Farhad Hatami
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | | | | | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada
| | - Heinz Wiendl
- Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Tanuja Chitnis
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Robert A Bermel
- Department of Neurology, Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, USA
| |
Collapse
|
50
|
Freeman L, Longbrake EE, Coyle PK, Hendin B, Vollmer T. High-Efficacy Therapies for Treatment-Naïve Individuals with Relapsing-Remitting Multiple Sclerosis. CNS Drugs 2022; 36:1285-1299. [PMID: 36350491 PMCID: PMC9645316 DOI: 10.1007/s40263-022-00965-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/05/2022] [Indexed: 11/11/2022]
Abstract
There are > 18 distinct disease-modifying therapy (DMT) options covering 10 mechanisms of action currently approved by the US Food and Drug Administration for the treatment of relapsing-remitting multiple sclerosis (RRMS). Given the multitude of available treatment options, and recent international consensus guidelines offering differing recommendations, there is broad heterogeneity in how the DMTs are used in clinical practice. Choosing a DMT for newly diagnosed patients with MS is currently a topic of significant debate in MS care. Historically, an escalation approach to DMT was used for newly diagnosed patients with RRMS. However, the evidence for clinical benefits of early treatment with high-efficacy therapies (HETs) in this population is emerging. In this review, we provide an overview of the DMT options and MS treatment strategies, and discuss the clinical benefits of HETs (including ofatumumab, ocrelizumab, natalizumab, alemtuzumab, and cladribine) in the early stages of MS, along with safety concerns associated with these DMTs. By minimizing the accumulation of neurological damage early in the disease course, early treatment with HETs may enhance long-term clinical outcomes over the lifetime of the patient.
Collapse
Affiliation(s)
- Léorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, 1601 Trinity St, Austin, TX, 78701, USA.
| | | | - Patricia K. Coyle
- Department of Neurology, Stony Brook University Medical Center, Stony Brook, NY USA
| | - Barry Hendin
- Banner, University Medicine Neurosciences Clinic, Phoenix, AZ USA
| | - Timothy Vollmer
- Department of Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO USA
| |
Collapse
|