1
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Calabrese M, Preziosa P, Scalfari A, Colato E, Marastoni D, Absinta M, Battaglini M, De Stefano N, Di Filippo M, Hametner S, Howell OW, Inglese M, Lassmann H, Martin R, Nicholas R, Reynolds R, Rocca MA, Tamanti A, Vercellino M, Villar LM, Filippi M, Magliozzi R. Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis. Ann Neurol 2024; 96:1-20. [PMID: 38568026 DOI: 10.1002/ana.26913] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/04/2024] [Accepted: 02/15/2024] [Indexed: 06/20/2024]
Abstract
Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.
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Affiliation(s)
- Massimiliano Calabrese
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Antonio Scalfari
- Centre of Neuroscience, Department of Medicine, Imperial College, London, UK
| | - Elisa Colato
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Damiano Marastoni
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Martina Absinta
- Translational Neuropathology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Battaglini
- Siena Imaging S.r.l., Siena, Italy
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Massimiliano Di Filippo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Simon Hametner
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Owain W Howell
- Institute of Life Sciences, Swansea University Medical School, Swansea, UK
| | - Matilde Inglese
- Dipartimento di neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili - DINOGMI, University of Genova, Genoa, Italy
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Roland Martin
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
- Therapeutic Design Unit, Center for Molecular Medicine, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
- Cellerys AG, Schlieren, Switzerland
| | - Richard Nicholas
- Department of Brain Sciences, Faculty of Medicine, Burlington Danes, Imperial College London, London, UK
| | - Richard Reynolds
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - 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
| | - Agnese Tamanti
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Marco Vercellino
- Multiple Sclerosis Center & Neurologia I U, Department of Neuroscience, University Hospital AOU Città della Salute e della Scienza di Torino, Turin, Italy
| | - Luisa Maria Villar
- Department of Immunology, Ramon y Cajal University Hospital. IRYCIS. REI, Madrid, Spain
| | - 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
| | - Roberta Magliozzi
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
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Alshehri A, Koussis N, Al-Iedani O, Khormi I, Lea R, Ramadan S, Lechner-Scott J. Improvement of the thalamocortical white matter network in people with stable treated relapsing-remitting multiple sclerosis over time. NMR IN BIOMEDICINE 2024; 37:e5119. [PMID: 38383137 DOI: 10.1002/nbm.5119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/28/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024]
Abstract
Advanced imaging techniques (tractography) enable the mapping of white matter (WM) pathways and the understanding of brain connectivity patterns. We combined tractography with a network-based approach to examine WM microstructure on a network level in people with relapsing-remitting multiple sclerosis (pw-RRMS) and healthy controls (HCs) over 2 years. Seventy-six pw-RRMS matched with 43 HCs underwent clinical assessments and 3T MRI scans at baseline (BL) and 2-year follow-up (2-YFU). Probabilistic tractography was performed, accounting for the effect of lesions, producing connectomes of 25 million streamlines. Network differences in fibre density across pw-RRMS and HCs at BL and 2-YFU were quantified using network-based statistics (NBS). Longitudinal network differences in fibre density were quantified using NBS in pw-RRMS, and were tested for correlations with disability, cognition and fatigue scores. Widespread network reductions in fibre density were found in pw-RRMS compared with HCs at BL in cortical regions, with more reductions detected at 2-YFU. Pw-RRMS had reduced fibre density at BL in the thalamocortical network compared to 2-YFU. This effect appeared after correction for age, was robust across different thresholds, and did not correlate with lesion volume or disease duration. Pw-RRMS demonstrated a robust and long-distance improvement in the thalamocortical WM network, regardless of age, disease burden, duration or therapy, suggesting a potential locus of neuroplasticity in MS. This network's role over the disease's lifespan and its potential implications in prognosis and treatment warrants further investigation.
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Affiliation(s)
- Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Radiology, King Fahd University Hospital, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Nikitas Koussis
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Psychological Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
| | - Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Neurology, John Hunter Hospital, New Lambton Heights, NSW, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
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3
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Kenyon KH, Strik M, Noffs G, Morgan A, Kolbe S, Harding IH, Vogel AP, Boonstra FMC, van der Walt A. Volumetric and diffusion MRI abnormalities associated with dysarthria in multiple sclerosis. Brain Commun 2024; 6:fcae177. [PMID: 38846538 PMCID: PMC11154149 DOI: 10.1093/braincomms/fcae177] [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: 12/06/2023] [Revised: 04/16/2024] [Accepted: 05/21/2024] [Indexed: 06/09/2024] Open
Abstract
Up to half of all people with multiple sclerosis experience communication difficulties due to dysarthria, a disorder that impacts the motor aspects of speech production. Dysarthria in multiple sclerosis is linked to cerebellar dysfunction, disease severity and lesion load, but the neuroanatomical substrates of these symptoms remain unclear. In this study, 52 participants with multiple sclerosis and 14 age- and sex-matched healthy controls underwent structural and diffusion MRI, clinical assessment of disease severity and cerebellar dysfunction and a battery of motor speech tasks. Assessments of regional brain volume and white matter integrity, and their relationships with clinical and speech measures, were undertaken. White matter tracts of interest included the interhemispheric sensorimotor tract, cerebello-thalamo-cortical tract and arcuate fasciculus, based on their roles in motor and speech behaviours. Volumetric analyses were targeted to Broca's area, Wernicke's area, the corpus callosum, thalamus and cerebellum. Our results indicated that multiple sclerosis participants scored worse on all motor speech tasks. Fixel-based diffusion MRI analyses showed significant evidence of white matter tract atrophy in each tract of interest. Correlational analyses further indicated that higher speech naturalness-a perceptual measure of dysarthria-and lower reading rate were associated with axonal damage in the interhemispheric sensorimotor tract and left arcuate fasciculus in people with multiple sclerosis. Axonal damage in all tracts of interest also correlated with clinical scales sensitive to cerebellar dysfunction. Participants with multiple sclerosis had lower volumes of the thalamus and corpus callosum compared with controls, although no brain volumetrics correlated with measures of dysarthria. These findings indicate that axonal damage, particularly when measured using diffusion metrics, underpin dysarthria in multiple sclerosis.
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Affiliation(s)
- Katherine H Kenyon
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
| | - Myrte Strik
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
| | - Gustavo Noffs
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
| | - Angela Morgan
- Murdoch Children’s Research Institute, Genomic Medicine, Speech and Language Group, Parkville 3052, Australia
- Department of Speech Pathology and Audiology, University of Melbourne, Parkville 3052, Australia
| | - Scott Kolbe
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Ian H Harding
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Adam P Vogel
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
- Division of Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
- Center for Neurology, University Hospital Tübingen, Tübingen 72076, Germany
- The Bionics Institute, East Melbourne, VIC 3002, Australia
| | - Frederique M C Boonstra
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Anneke van der Walt
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- The Bionics Institute, East Melbourne, VIC 3002, Australia
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4
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Stuart CM, Varatharaj A, Zou Y, Darekar A, Domjan J, Gandini Wheeler-Kingshott CAM, Perry VH, Galea I. Systemic inflammation associates with and precedes cord atrophy in progressive multiple sclerosis. Brain Commun 2024; 6:fcae143. [PMID: 38712323 PMCID: PMC11073756 DOI: 10.1093/braincomms/fcae143] [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: 11/13/2023] [Revised: 02/05/2024] [Accepted: 04/17/2024] [Indexed: 05/08/2024] Open
Abstract
In preclinical models of multiple sclerosis, systemic inflammation has an impact on the compartmentalized inflammatory process within the central nervous system and results in axonal loss. It remains to be shown whether this is the case in humans, specifically whether systemic inflammation contributes to spinal cord or brain atrophy in multiple sclerosis. Hence, an observational longitudinal study was conducted to delineate the relationship between systemic inflammation and atrophy using magnetic resonance imaging: the SIMS (Systemic Inflammation in Multiple Sclerosis) study. Systemic inflammation and progression were assessed in people with progressive multiple sclerosis (n = 50) over two and a half years. Eligibility criteria included: (i) primary or secondary progressive multiple sclerosis; (ii) age ≤ 70; and (iii) Expanded Disability Status Scale ≤ 6.5. First morning urine was collected weekly to quantify systemic inflammation by measuring the urinary neopterin-to-creatinine ratio using a validated ultra-performance liquid chromatography mass spectrometry technique. The urinary neopterin-to-creatinine ratio temporal profile was characterized by short-term responses overlaid on a background level of inflammation, so these two distinct processes were considered as separate variables: background inflammation and inflammatory response. Participants underwent MRI at the start and end of the study, to measure cervical spinal cord and brain atrophy. Brain and cervical cord atrophy occurred on the study, but the most striking change was seen in the cervical spinal cord, in keeping with the corticospinal tract involvement that is typical of progressive disease. Systemic inflammation predicted cervical cord atrophy. An association with brain atrophy was not observed in this cohort. A time lag between systemic inflammation and cord atrophy was evident, suggesting but not proving causation. The association of the inflammatory response with cord atrophy depended on the level of background inflammation, in keeping with experimental data in preclinical models where the effects of a systemic inflammatory challenge on tissue injury depended on prior exposure to inflammation. A higher inflammatory response was associated with accelerated cord atrophy in the presence of background systemic inflammation below the median for the study population. Higher background inflammation, while associated with cervical cord atrophy itself, subdued the association of the inflammatory response with cord atrophy. Findings were robust to sensitivity analyses adjusting for potential confounders and excluding cases with new lesion formation. In conclusion, systemic inflammation associates with, and precedes, multiple sclerosis progression. Further work is needed to prove causation since targeting systemic inflammation may offer novel treatment strategies for slowing neurodegeneration in multiple sclerosis.
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Affiliation(s)
- Charlotte M Stuart
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
| | - Aravinthan Varatharaj
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Yukai Zou
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Department of Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Angela Darekar
- Department of Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Janine Domjan
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- Department of Neuroinflammation, Faculty of Brain Sciences, NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
| | - V Hugh Perry
- School of Biological Sciences, University of Southampton, Southampton SO16 6YD, UK
| | - Ian Galea
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
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5
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Cofré Lizama LE, He X, Kalincik T, Galea MP, Panisset MG. Sample Entropy Improves Assessment of Postural Control in Early-Stage Multiple Sclerosis. SENSORS (BASEL, SWITZERLAND) 2024; 24:872. [PMID: 38339590 PMCID: PMC10857195 DOI: 10.3390/s24030872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/22/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024]
Abstract
Postural impairment in people with multiple sclerosis (pwMS) is an early indicator of disease progression. Common measures of disease assessment are not sensitive to early-stage MS. Sample entropy (SE) may better identify early impairments. We compared the sensitivity and specificity of SE with linear measurements, differentiating pwMS (EDSS 0-4) from healthy controls (HC). 58 pwMS (EDSS ≤ 4) and 23 HC performed quiet standing tasks, combining a hard or foam surface with eyes open or eyes closed as a condition. Sway was recorded at the sternum and lumbar spine. Linear measures, mediolateral acceleration range with eyes open, mediolateral jerk with eyes closed, and SE in the anteroposterior and mediolateral directions were calculated. A multivariate ANOVA and AUC-ROC were used to determine between-groups differences and discriminative ability, respectively. Mild MS (EDSS ≤ 2.0) discriminability was secondarily assessed. Significantly lower SE was observed under most conditions in pwMS compared to HC, except for lumbar and sternum SE when on a hard surface with eyes closed and in the anteroposterior direction, which also offered the strongest discriminability (AUC = 0.747), even for mild MS. Overall, between-groups differences were task-dependent, and SE (anteroposterior, hard surface, eyes closed) was the best pwMS classifier. SE may prove a useful tool to detect subtle MS progression and intervention effectiveness.
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Affiliation(s)
- L. Eduardo Cofré Lizama
- Department of Medicine, The University of Melbourne, Melbourne, VIC 3052, Australia; (X.H.); (M.P.G.); (M.G.P.)
| | - Xiangyu He
- Department of Medicine, The University of Melbourne, Melbourne, VIC 3052, Australia; (X.H.); (M.P.G.); (M.G.P.)
| | - Tomas Kalincik
- Neuroimmunology Centre, Department of Neurology, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia;
- Clinical Outcomes Research Unit, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Mary P. Galea
- Department of Medicine, The University of Melbourne, Melbourne, VIC 3052, Australia; (X.H.); (M.P.G.); (M.G.P.)
- Department of Rehabilitation, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia
- Australian Rehabilitation Research Centre, Royal Melbourne Hospital, Melbourne, VIC 3052, Australia
| | - Maya G. Panisset
- Department of Medicine, The University of Melbourne, Melbourne, VIC 3052, Australia; (X.H.); (M.P.G.); (M.G.P.)
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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.
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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
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7
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Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
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Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
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8
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Strik M, Eijlers AJC, Dekker I, Broeders TAA, Douw L, Killestein J, Kolbe SC, Geurts JJG, Schoonheim MM. Sensorimotor network dynamics predict decline in upper and lower limb function in people with multiple sclerosis. Mult Scler 2023; 29:81-91. [PMID: 36177896 PMCID: PMC9896264 DOI: 10.1177/13524585221125372] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Upper and lower limb disabilities are hypothesized to have partially independent underlying (network) disturbances in multiple sclerosis (MS). OBJECTIVE This study investigated functional network predictors and longitudinal network changes related to upper and lower limb progression in MS. METHODS Two-hundred fourteen MS patients and 58 controls underwent functional magnetic resonance imaging (fMRI), dexterity (9-Hole Peg Test) and mobility (Timed 25-Foot Walk) measurements (baseline and 5 years). Patients were stratified into progressors (>20% decline) or non-progressors. Functional network efficiency was calculated using static (over entire scan) and dynamic (fluctuations during scan) approaches. Baseline measurements were used to predict progression; significant predictors were explored over time. RESULTS In both limbs, progression was related to supplementary motor area and caudate efficiency (dynamic and static, respectively). Upper limb progression showed additional specific predictors; cortical grey matter volume, putamen static efficiency and posterior associative sensory (PAS) cortex, putamen, primary somatosensory cortex and thalamus dynamic efficiency. Additional lower limb predictors included motor network grey matter volume, caudate (dynamic) and PAS (static). Only the caudate showed a decline in efficiency over time in one group (non-progressors). CONCLUSION Disability progression can be predicted using sensorimotor network measures. Upper and lower limb progression showed unique predictors, possibly indicating different network disturbances underlying these types of progression in MS.
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Affiliation(s)
- Myrte Strik
- M Strik Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Melbourne Medical School, Level 1, Kenneth Myer building, 30 Royal Parade, Melbourne, VIC 3010 Australia.
| | - Anand JC Eijlers
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Iris Dekker
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Tommy AA Broeders
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Linda Douw
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Joep Killestein
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Scott C Kolbe
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Jeroen JG Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
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9
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Chen Q, Hattori T, Tomisato H, Ohara M, Hirata K, Yokota T. Turning and multitask gait unmask gait disturbance in mild-to-moderate multiple sclerosis: Underlying specific cortical thinning and connecting fibers damage. Hum Brain Mapp 2022; 44:1193-1208. [PMID: 36409700 PMCID: PMC9875928 DOI: 10.1002/hbm.26151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/08/2022] [Accepted: 11/01/2022] [Indexed: 11/22/2022] Open
Abstract
Multiple sclerosis (MS) causes gait and cognitive impairments that are partially normalized by compensatory mechanisms. We aimed to identify the gait tasks that unmask gait disturbance and the underlying neural correlates in MS. We included 25 patients with MS (Expanded Disability Status Scale score: median 2.0, interquartile range 1.0-2.5) and 19 healthy controls. Fast-paced gait examinations with inertial measurement units were conducted, including straight or circular walking with or without cognitive/motor tasks, and the timed up and go test (TUG). Receiver operating characteristic curve analysis was performed to distinguish both groups by the gait parameters. The correlation between gait parameters and cortical thickness or fractional anisotropy values was examined by using three-dimensional T1-weighted imaging and diffusion tensor imaging, respectively (corrected p < .05). Total TUG duration (>6.0 s, sensitivity 88.0%, specificity 84.2%) and stride velocity during cognitive dual-task circular walking (<1.12 m/s, 84.0%, 84.2%) had the highest discriminative power of the two groups. Deterioration of these gait parameters was correlated with thinner cortical thickness in regional areas, including the left precuneus and left temporoparietal junction, overlapped with parts of the default mode network, ventral attention network, and frontoparietal network. Total TUG duration was negatively correlated with fractional anisotropy values in the deep cerebral white matter areas. Turning and multitask gait may be optimal to unveil partially compensated gait disturbance in patients with mild-to-moderate MS through dynamic balance control and multitask processing, based on the structural damage in functional networks.
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Affiliation(s)
- Qingmeng Chen
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental ScienceTokyo Medical and Dental UniversityTokyoJapan
| | - Takaaki Hattori
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental ScienceTokyo Medical and Dental UniversityTokyoJapan
| | - Hiroshi Tomisato
- Radiology Center, Division of Integrated FacilitiesTokyo Medical and Dental University HospitalTokyoJapan
| | - Masahiro Ohara
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental ScienceTokyo Medical and Dental UniversityTokyoJapan
| | - Kosei Hirata
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental ScienceTokyo Medical and Dental UniversityTokyoJapan
| | - Takanori Yokota
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental ScienceTokyo Medical and Dental UniversityTokyoJapan
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10
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Nooraei A, Khazaeel K, Darvishi M, Ghotbeddin Z, Basir Z. Dimorphic evaluation of hippocampal changes in rat model of demyelination: A comparative functional, morphometric, and histological study. Brain Behav 2022; 12:e32723. [PMID: 35861689 PMCID: PMC9392515 DOI: 10.1002/brb3.2723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 07/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is the most common autoimmune disease. Progressive depletion of the brain and spinal cord tissue appears at the onset of the disease. Several studies have shown the increased size of the ventricles of the brain and decreases in the area of the corpus callosum and the width of the brain. Other important symptoms of this disease are cognitive, learning, and memory disorders. AIM The aim of this study was to compare morphometric, histological, and functional changes in the demyelination model in both sexes. MATERIALS AND METHODS In this experimental study, male and female Wistar rats were studied in four experimental groups. Demyelination was induced by the injection of ethidium bromide in the ventricular region. The chronic effect of demyelination on spatial memory, movement, and coordination was investigated using the Morris Water Maze (MWM), and clinical and balance beam tests, respectively. Myelin degradation, cell death and neurogenesis were estimated using Luxol Fast Blue staining and immunohistochemistry (Caspase-3 and Nestin markers). In addition, morphometric findings were recorded for the brain and hippocampus (weight, volume, length, width). RESULT Demyelination increased the time and distance index and decreased the residence time in the target quarter in the water maze test (p < .001). It also increases the neuromuscular and modified neurological severity score (p < .01). Demyelination increases caspase-3 (p < .05) expression and decreases Nestin expression (p < .001), which are directly related to the extent of damage. CONCLUSION This study showed an interaction between hippocampal structural and functional networks in explaining spatial learning and memory in the early stages of MS.
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Affiliation(s)
- Aref Nooraei
- Faculty of Veterinary Medicine, Department of Basic Sciences, Shahid Chamran University of Ahvaz, Iran
| | - Kaveh Khazaeel
- Faculty of Veterinary Medicine, Department of Basic Sciences, Shahid Chamran University of Ahvaz, Iran.,Stem Cell and Transgenic Technology Research Center, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Marzieh Darvishi
- Faculty of Medicine, Department of Anatomy, Ilam University of Medical Sciences, Ilam, Iran.,Biotechnology and Medicinal Plants Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Zohreh Ghotbeddin
- Faculty of Veterinary Medicine, Department of Basic Sciences, Shahid Chamran University of Ahvaz, Iran.,Stem Cell and Transgenic Technology Research Center, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Zahra Basir
- Faculty of Veterinary Medicine, Department of Basic Sciences, Shahid Chamran University of Ahvaz, Iran
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11
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Cofré Lizama LE, Strik M, Van der Walt A, Kilpatrick TJ, Kolbe SC, Galea MP. Gait stability reflects motor tracts damage at early stages of multiple sclerosis. Mult Scler 2022; 28:1773-1782. [DOI: 10.1177/13524585221094464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Gait in people with multiple sclerosis (PwMS) is affected even when no changes can be observed on clinical examination. A sensitive measure of gait deterioration is stability; however, its correlation with motor tract damage has not yet been established. Objective: To compare stability between PwMS and healthy controls (HCs) and determine associations between stability and diffusion magnetic resonance image (MRI) measures of axonal damage in selected sensorimotor tracts. Methods: Twenty-five PwMS (Expanded Disability Status Scale (EDSS) < 2.5) and 15 HCs walked on a treadmill. Stability from sacrum (LDESAC), shoulder (LDESHO) and cervical (LDECER) was calculated using the local divergence exponent (LDE). Participants underwent a 7T-MRI brain scan to obtain fibre-specific measures of axonal loss within the corticospinal tract (CST), interhemispheric sensorimotor tract (IHST) and cerebellothalamic tract (CTT). Correlation analyses between LDE and fibre density (FD) within tracts, fibre cross-section (FC) and FD modulated by FC (FDC) were conducted. Between-groups LDE differences were analysed using analysis of variance (ANOVA). Results: Correlations between all stability measures with CSTFD, between CSTFDC with LDESAC and LDECER, and LDECER with IHSTFD and IHSTFDC were significant yet moderate ( R < −0.4). Stability was significantly different between groups. Conclusions: Poorer gait stability is associated with corticospinal tract (CST) axonal loss in PwMS with no-to-low disability and is a sensitive indicator of neurodegeneration.
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Affiliation(s)
- L Eduardo Cofré Lizama
- School of Allied Health, Human Services and Sports, La Trobe University, Bundoora, VIC, Australia/Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Myrte Strik
- Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Anneke Van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Trevor J Kilpatrick
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia/Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia/Department of Neurology, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Scott C Kolbe
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Mary P Galea
- Galea Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
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12
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Advanced diffusion-weighted imaging models better characterize white matter neurodegeneration and clinical outcomes in multiple sclerosis. J Neurol 2022; 269:4729-4741. [DOI: 10.1007/s00415-022-11104-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 10/18/2022]
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13
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Boonstra FM, Clough M, Strik M, van der Walt A, Butzkueven H, White OB, Law M, Fielding J, Kolbe SC. Longitudinal tracking of axonal loss using diffusion magnetic resonance imaging in multiple sclerosis. Brain Commun 2022; 4:fcac065. [PMID: 35425898 PMCID: PMC9006042 DOI: 10.1093/braincomms/fcac065] [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: 06/30/2021] [Revised: 10/27/2021] [Accepted: 03/15/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Axonal loss in the CNS is a key driver of progressive neurological impairments in people with multiple sclerosis. Currently, there are no established methods for tracking axonal loss clinically. This study aimed to determine the sensitivity of longitudinal diffusion MRI derived fibre specific measures of axonal loss in people with multiple sclerosis. Fibre measures were derived from diffusion MRI acquired as part of a standard radiological MRI protocol and were compared 1) to established measures of neuro-axonal degeneration: brain parenchymal fraction and retinal nerve fibre layer thickness and 2) between different disease stages: clinically isolated syndrome and early/late relapsing-remitting multiple sclerosis. Retrospectively identified data from fifty-nine people with multiple sclerosis (18 clinically isolated syndrome, 22 early and 19 late relapsing-remitting) who underwent diffusion MRI as part of their routine clinical monitoring were collated and analysed. Twenty-six patients had 1-year and 14 patients had 2-year follow-up. Brain parenchymal fraction was calculated from 3D MRI scans, and fibre-specific measures were calculated from diffusion MRI using multi-tissue constrained spherical deconvolution. At each study visit, patients underwent optical coherence tomography to determine retinal nerve fibre layer thickness, and standard neurological assessment expanded disability status scale. We found a significant annual fibre-specific neuro-axonal degeneration (mean ± SD = −3.49 ± 3.32%, p<0.001) that was approximately seven times larger than the annual change of brain parenchymal fraction (−0.53 ± 0.95%, p<0.001), and more than four times larger than annual retinal nerve fibre layer thinning (−0.75 ± 2.50% p=0.036). Only fibre-specific measures showed a significant difference in annual degeneration between the disease stages (p=0.029). Reduced brain parenchymal fraction, retinal nerve fibre layer thickness and fibre-specific measures were moderately related to higher expanded disability status scale (respectively rho=−0.368, rho=−0.408 and rho=−0.365). Fibre-specific measures can be measured from data collected within a standard radiological multiple sclerosis study and are substantially more sensitive to longitudinal change compared to brain atrophy and retinal nerve fibre layer thinning.
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Affiliation(s)
- Frederique M. Boonstra
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Meaghan Clough
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Anneke van der Walt
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Owen B. White
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
- Department Radiology, Alfred Health, Prahran, Australia
| | - Joanne Fielding
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
| | - Scott C. Kolbe
- Department of Neuroscience, Central Clinical School, Monash University, Prahran, Australia
- Department Radiology, Alfred Health, Prahran, Australia
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14
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Monaghan AS, Monaghan PG, Richmond SB, Roper JA, Fling BW. The effect of shoe cushioning on gait and balance in females with multiple sclerosis. Exp Brain Res 2021; 239:2593-2603. [PMID: 34212220 DOI: 10.1007/s00221-021-06161-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 06/22/2021] [Indexed: 01/28/2023]
Abstract
Gait and balance deficits are significant concerns for people with multiple sclerosis (MS). Shoe cushioning can influence mobility and balance, but its effect on walking and balance remains unknown in MS. This study aimed to determine how shoe cushioning affects gait and balance in females with MS (FwMS). We hypothesized that extra cushioning would improve gait but reduce balance performance. FwMS performed gait (n = 18) and balance (n = 17) assessments instrumented using inertial sensors in two different shoe conditions: a standard-cushioned and an extra-cushioned shoe. Care was taken to ensure minimal differences between shoe types other than midsole cushioning, but shoe construction was not identical between conditions. Spatiotemporal gait parameters were assessed during a 2-min walk test, while postural sway measures were evaluated using the modified Clinical Test of Sensory Interaction and Balance. In the extra-cushioned shoe, FwMS spent less time in the double support and stance phase with more time in the single support and swing phase. No differences in stride length, gait speed, or elevation at midswing were observed between shoe conditions. Decreased path length, RMS sway, and sway velocity were observed in the extra-cushioned shoe. No differences were observed in the gait cycle's spatial composition between shoe conditions, but FwMS demonstrated improvements in the gait cycle's temporal parameters and postural sway in the extra-cushioned shoe. This may suggest a less cautious walking strategy and improved balance when wearing a shoe with extra cushioning.
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Affiliation(s)
- Andrew S Monaghan
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
| | | | - Sutton B Richmond
- Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Jamie A Roper
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | - Brett W Fling
- Department of Health and Exercise Science, Colorado State University, Room 220 Moby Complex, 951 Plum Street, Fort Collins, CO, 80523-1582, USA. .,Molecular, Cellular and Integrative Neurosciences Program, Colorado State University, Fort Collins, CO, USA.
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