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Brasanac J, Chien C. A review on multiple sclerosis prognostic findings from imaging, inflammation, and mental health studies. Front Hum Neurosci 2023; 17:1151531. [PMID: 37250694 PMCID: PMC10213782 DOI: 10.3389/fnhum.2023.1151531] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/21/2023] [Indexed: 05/31/2023] Open
Abstract
Magnetic resonance imaging (MRI) of the brain is commonly used to detect where chronic and active lesions are in multiple sclerosis (MS). MRI is also extensively used as a tool to calculate and extrapolate brain health by way of volumetric analysis or advanced imaging techniques. In MS patients, psychiatric symptoms are common comorbidities, with depression being the main one. Even though these symptoms are a major determinant of quality of life in MS, they are often overlooked and undertreated. There has been evidence of bidirectional interactions between the course of MS and comorbid psychiatric symptoms. In order to mitigate disability progression in MS, treating psychiatric comorbidities should be investigated and optimized. New research for the prediction of disease states or phenotypes of disability have advanced, primarily due to new technologies and a better understanding of the aging brain.
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Affiliation(s)
- Jelena Brasanac
- Charité – Universitätsmedizin Berlin, Klinik für Psychiatrie und Psychotherapie, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Medizinische Klinik m.S. Psychosomatik, Berlin, Germany
| | - Claudia Chien
- Charité – Universitätsmedizin Berlin, Klinik für Psychiatrie und Psychotherapie, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Medizinische Klinik m.S. Psychosomatik, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Experimental and Clinical Research Center, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Neuroscience Clinical Research Center, Berlin, Germany
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2
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An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis. THE CEREBELLUM 2022:10.1007/s12311-022-01435-y. [PMID: 35761144 PMCID: PMC9244122 DOI: 10.1007/s12311-022-01435-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/15/2022] [Indexed: 12/03/2022]
Abstract
Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.
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Rocca MA, Schoonheim MM, Valsasina P, Geurts JJG, Filippi M. Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective. Neuroimage Clin 2022; 35:103076. [PMID: 35691253 PMCID: PMC9194954 DOI: 10.1016/j.nicl.2022.103076] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 01/12/2023]
Abstract
Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages. Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease. Collapse of long-range connections and impaired hub integration characterize MS network reorganization. Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity. New perspectives might be the use of multimodal MRI and artificial intelligence.
Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.
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Affiliation(s)
- 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.
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
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4
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Broeders TA, Douw L, Eijlers AJ, Dekker I, Uitdehaag BM, Barkhof F, Hulst HE, Vinkers CH, Geurts JJ, Schoonheim MM. A more unstable resting-state functional network in cognitively declining multiple sclerosis. Brain Commun 2022; 4:fcac095. [PMID: 35620116 PMCID: PMC9128379 DOI: 10.1093/braincomms/fcac095] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 02/14/2022] [Accepted: 04/11/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive impairment is common in people with multiple sclerosis and strongly
affects their daily functioning. Reports have linked disturbed cognitive
functioning in multiple sclerosis to changes in the organization of the
functional network. In a healthy brain, communication between brain regions and
which network a region belongs to is continuously and dynamically adapted to
enable adequate cognitive function. However, this dynamic network adaptation has
not been investigated in multiple sclerosis, and longitudinal network data
remain particularly rare. Therefore, the aim of this study was to longitudinally
identify patterns of dynamic network reconfigurations that are related to the
worsening of cognitive decline in multiple sclerosis. Resting-state functional
MRI and cognitive scores (expanded Brief Repeatable Battery of
Neuropsychological tests) were acquired in 230 patients with multiple sclerosis
and 59 matched healthy controls, at baseline (mean disease duration: 15 years)
and at 5-year follow-up. A sliding-window approach was used for functional MRI
analyses, where brain regions were dynamically assigned to one of seven
literature-based subnetworks. Dynamic reconfigurations of subnetworks were
characterized using measures of promiscuity (number of subnetworks switched to),
flexibility (number of switches), cohesion (mutual switches) and disjointedness
(independent switches). Cross-sectional differences between cognitive groups and
longitudinal changes were assessed, as well as relations with structural damage
and performance on specific cognitive domains. At baseline, 23% of
patients were cognitively impaired (≥2/7 domains
Z < −2) and 18% were mildly
impaired (≥2/7 domains
Z < −1.5). Longitudinally,
28% of patients declined over time (0.25 yearly change on ≥2/7
domains based on reliable change index). Cognitively impaired patients displayed
more dynamic network reconfigurations across the whole brain compared with
cognitively preserved patients and controls, i.e. showing higher promiscuity
(P = 0.047), flexibility
(P = 0.008) and cohesion
(P = 0.008). Over time, cognitively
declining patients showed a further increase in cohesion
(P = 0.004), which was not seen in stable
patients (P = 0.544). More cohesion was
related to more severe structural damage (average
r = 0.166,
P = 0.015) and worse verbal memory
(r = −0.156,
P = 0.022), information processing speed
(r = −0.202,
P = 0.003) and working memory
(r = −0.163,
P = 0.017). Cognitively impaired multiple
sclerosis patients exhibited a more unstable network reconfiguration compared to
preserved patients, i.e. brain regions switched between subnetworks more often,
which was related to structural damage. This shift to more unstable network
reconfigurations was also demonstrated longitudinally in patients that showed
cognitive decline only. These results indicate the potential relevance of a
progressive destabilization of network topology for understanding cognitive
decline in multiple sclerosis.
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Affiliation(s)
- Tommy A.A. Broeders
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda Douw
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anand J.C. Eijlers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Iris Dekker
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bernard M.J. Uitdehaag
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, UK
| | - Hanneke E. Hulst
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Christiaan H. Vinkers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Departments of Psychiatry, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J.G. Geurts
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno M. Schoonheim
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Strik M, Cofré Lizama LE, Shanahan CJ, van der Walt A, Boonstra FMC, Glarin R, Kilpatrick TJ, Geurts JJG, Cleary JO, Schoonheim MM, Galea MP, Kolbe SC. Axonal loss in major sensorimotor tracts is associated with impaired motor performance in minimally disabled multiple sclerosis patients. Brain Commun 2021; 3:fcab032. [PMID: 34222866 PMCID: PMC8244644 DOI: 10.1093/braincomms/fcab032] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/15/2020] [Accepted: 01/11/2021] [Indexed: 12/13/2022] Open
Abstract
Multiple sclerosis is a neuroinflammatory disease of the CNS that is associated with significant irreversible neuro-axonal loss, leading to permanent disability. There is thus an urgent need for in vivo markers of axonal loss for use in patient monitoring or as end-points for trials of neuroprotective agents. Advanced diffusion MRI can provide markers of diffuse loss of axonal fibre density or atrophy within specific white matter pathways. These markers can be interrogated in specific white matter tracts that underpin important functional domains such as sensorimotor function. This study aimed to evaluate advanced diffusion MRI markers of axonal loss within the major sensorimotor tracts of the brain, and to correlate the degree of axonal loss in these tracts to precise kinematic measures of hand and foot motor control and gait in minimally disabled people with multiple sclerosis. Twenty-eight patients (Expanded Disability Status Scale < 4, and Kurtzke Functional System Scores for pyramidal and cerebellar function ≤ 2) and 18 healthy subjects underwent ultra-high field 7 Tesla diffusion MRI for calculation of fibre-specific measures of axonal loss (fibre density, reflecting diffuse axonal loss and fibre cross-section reflecting tract atrophy) within three tracts: cortico-spinal tract, interhemispheric sensorimotor tract and cerebello-thalamic tracts. A visually guided force-matching task involving either the hand or foot was used to assess visuomotor control, and three-dimensional marker-based video tracking was used to assess gait. Fibre-specific axonal markers for each tract were compared between groups and correlated with visuomotor task performance (force error and lag) and gait parameters (stance, stride length, step width, single and double support) in patients. Patients displayed significant regional loss of fibre cross-section with minimal loss of fibre density in all tracts of interest compared to healthy subjects (family-wise error corrected p-value < 0.05), despite relatively few focal lesions within these tracts. In patients, reduced axonal fibre density and cross-section within the corticospinal tracts and interhemispheric sensorimotor tracts were associated with larger force tracking error and gait impairments (shorter stance, smaller step width and longer double support) (family-wise error corrected p-value < 0.05). In conclusion, significant gait and motor control impairments can be detected in minimally disabled people with multiple sclerosis that correlated with axonal loss in major sensorimotor pathways of the brain. Given that axonal loss is irreversible, the combined use of advanced imaging and kinematic markers could be used to identify patients at risk of more severe motor impairments as they emerge for more aggressive therapeutic interventions.
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Affiliation(s)
- Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - L Eduardo Cofré Lizama
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- School of Allied Health, Human Services and Sports, La Trobe University, Victoria 3086, Australia
| | - Camille J Shanahan
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Anneke van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Frederique M C Boonstra
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Rebecca Glarin
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Trevor J Kilpatrick
- Florey Institute of Neuroscience and Mental Health, Parkville 3052, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville 3050, Australia
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Jon O Cleary
- Department of Radiology, Guy’s and St. Thomas’ NHS Foundation Trust, London SE1 7EH, UK
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Mary P Galea
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Scott C Kolbe
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
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6
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Strik M, Shanahan CJ, van der Walt A, Boonstra FMC, Glarin R, Galea MP, Kilpatrick TJ, Geurts JJG, Cleary JO, Schoonheim MM, Kolbe SC. Functional correlates of motor control impairments in multiple sclerosis: A 7 Tesla task functional MRI study. Hum Brain Mapp 2021; 42:2569-2582. [PMID: 33666314 PMCID: PMC8090767 DOI: 10.1002/hbm.25389] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/10/2021] [Accepted: 02/16/2021] [Indexed: 02/01/2023] Open
Abstract
Upper and lower limb impairments are common in people with multiple sclerosis (pwMS), yet difficult to clinically identify in early stages of disease progression. Tasks involving complex motor control can potentially reveal more subtle deficits in early stages, and can be performed during functional MRI (fMRI) acquisition, to investigate underlying neural mechanisms, providing markers for early motor progression. We investigated brain activation during visually guided force matching of hand or foot in 28 minimally disabled pwMS (Expanded Disability Status Scale (EDSS) < 4 and pyramidal and cerebellar Kurtzke Functional Systems Scores ≤ 2) and 17 healthy controls (HC) using ultra‐high field 7‐Tesla fMRI, allowing us to visualise sensorimotor network activity in high detail. Task activations and performance (tracking lag and error) were compared between groups, and correlations were performed. PwMS showed delayed (+124 s, p = .002) and more erroneous (+0.15 N, p = .001) lower limb tracking, together with lower cerebellar, occipital and superior parietal cortical activation compared to HC. Lower activity within these regions correlated with worse EDSS (p = .034), lower force error (p = .006) and higher lesion load (p < .05). Despite no differences in upper limb task performance, pwMS displayed lower inferior occipital cortical activation. These results demonstrate that ultra‐high field fMRI during complex hand and foot tracking can identify subtle impairments in lower limb movements and upper and lower limb brain activity, and differentiates upper and lower limb impairments in minimally disabled pwMS.
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Affiliation(s)
- Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia.,Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Camille J Shanahan
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Anneke van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
| | - Frederique M C Boonstra
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
| | - Rebecca Glarin
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Mary P Galea
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia
| | - Trevor J Kilpatrick
- Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia.,Department of Neurology, Royal Melbourne Hospital, Parkville, Australia
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jon O Cleary
- Department of Radiology, Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Scott C Kolbe
- Department of Medicine and Radiology, University of Melbourne, Parkville, Australia.,Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
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