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Rocca MA, Romanò F, Tedone N, Filippi M. Advanced neuroimaging techniques to explore the effects of motor and cognitive rehabilitation in multiple sclerosis. J Neurol 2024; 271:3806-3848. [PMID: 38691168 DOI: 10.1007/s00415-024-12395-0] [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: 01/31/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 05/03/2024]
Abstract
INTRODUCTION Progress in magnetic resonance imaging (MRI) technology and analyses is improving our comprehension of multiple sclerosis (MS) pathophysiology. These advancements, which enable the evaluation of atrophy, microstructural tissue abnormalities, and functional plasticity, are broadening our insights into the effectiveness and working mechanisms of motor and cognitive rehabilitative treatments. AREAS COVERED This narrative review with selected studies discusses findings derived from the application of advanced MRI techniques to evaluate structural and functional neuroplasticity modifications underlying the effects of motor and cognitive rehabilitative treatments in people with MS (PwMS). Current applications as outcome measure in longitudinal trials and observational studies, their interpretation and possible pitfalls and limitations in their use are covered. Finally, we examine how the use of these techniques could evolve in the future to improve monitoring of motor and cognitive rehabilitative treatments. EXPERT COMMENTARY Despite substantial variability in study design and participant characteristics in rehabilitative studies for PwMS, improvements in motor and cognitive functions accompanied by structural and functional brain modifications induced by rehabilitation can be observed. However, significant enhancements to refine rehabilitation strategies are needed. Future studies in this field should strive to implement standardized methodologies regarding MRI acquisition and processing, possibly integrating multimodal measures. This will help identifying relevant markers of treatment response in PwMS, thus improving the use of rehabilitative interventions at individual level. The combination of motor and cognitive strategies, longer periods of treatment, as well as adequate follow-up assessments will contribute to enhance the quality of evidence in support of their routine use.
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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.
| | - Francesco Romanò
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nicolò Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- 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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Rocca MA, Valsasina P, Romanò F, Tedone N, Amato MP, Brichetto G, Boccia VD, Chataway J, Chiaravalloti ND, Cutter G, Dalgas U, DeLuca J, Farrell RA, Feys P, Freeman J, Inglese M, Meza C, Motl RW, Salter A, Sandroff BM, Feinstein A, Filippi M. Cognitive rehabilitation effects on grey matter volume and Go-NoGo activity in progressive multiple sclerosis: results from the CogEx trial. J Neurol Neurosurg Psychiatry 2024:jnnp-2024-333460. [PMID: 38754979 DOI: 10.1136/jnnp-2024-333460] [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: 01/22/2024] [Accepted: 04/23/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Research on cognitive rehabilitation (CR) and aerobic exercise (EX) to improve cognition in progressive multiple sclerosis (PMS) remains limited. CogEx trial investigated the effectiveness of CR and EX in PMS: here, we present MRI substudy volumetric and task-related functional MRI (fMRI) findings. METHODS Participants were randomised to: 'CR plus EX', 'CR plus sham EX (EX-S)', 'EX plus sham CR (CR-S)' and 'CR-S plus EX-S' and attended 12-week intervention. All subjects performed physical/cognitive assessments at baseline, week 12 and 6 months post intervention (month 9). All MRI substudy participants underwent volumetric MRI and fMRI (Go-NoGo task). RESULTS 104 PMS enrolled at four sites participated in the CogEx MRI substudy; 84 (81%) had valid volumetric MRI and valid fMRI. Week 12/month 9 cognitive performances did not differ among interventions; however, 25-62% of the patients showed Symbol Digit Modalities Test improvements. Normalised cortical grey matter volume (NcGMV) changes at week 12 versus baseline were heterogeneous among interventions (p=0.05); this was mainly driven by increased NcGMV in 'CR plus EX-S' (p=0.02). Groups performing CR (ie, 'CR plus EX' and 'CR plus EX-S') exhibited increased NcGMV over time, especially in the frontal (p=0.01), parietal (p=0.04) and temporal (p=0.04) lobes, while those performing CR-S exhibited NcGMV decrease (p=0.008). In CR groups, increased NcGMV (r=0.36, p=0.01) at week 12 versus baseline correlated with increased California Verbal Learning Test (CVLT)-II scores. 'CR plus EX-S' patients exhibited Go-NoGo activity increase (p<0.05, corrected) at week 12 versus baseline in bilateral insula. CONCLUSIONS In PMS, CR modulated grey matter (GM) volume and insular activity. The association of GM and CVLT-II changes suggests GM plasticity contributes to cognitive improvements. TRIAL REGISTRATION NUMBER NCT03679468.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Francesco Romanò
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicolò Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Pia Amato
- Department NEUROFARBA, Section Neurosciences, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Giampaolo Brichetto
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
- AISM Rehabilitation Service, Italian Multiple Sclerosis Society, Genoa, Italy
| | - Vincenzo Daniele Boccia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, and Center of Excellence for Biomedical Research, University of Genoa, Genoa, Italy
| | - Jeremy Chataway
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, UK
| | - Nancy D Chiaravalloti
- Kessler Foundation, West Orange, NJ, USA
- Department of Physical Medicine & Rehabilitation, Rutgers New Jersey Medical School, Newark, New Jersey, USA
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ulrik Dalgas
- Exercise Biology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - John DeLuca
- Kessler Foundation, West Orange, NJ, USA
- Department of Physical Medicine & Rehabilitation, Rutgers New Jersey Medical School, Newark, New Jersey, USA
| | - Rachel A Farrell
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Peter Feys
- REVAL, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
- University MS Center, Hasselt University, Pelt, Belgium
| | - Jennifer Freeman
- Faculty of Health, School of Health Professions, University of Plymouth, Plymouth, Devon, UK
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, and Center of Excellence for Biomedical Research, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Cecilia Meza
- Department of Psychiatry, University of Toronto and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Robert W Motl
- Department of Kinesiology and Nutrition, University of Illinois Chicago, Chicago, Illinois, USA
| | - Amber Salter
- Department of Neurology, Section on Statistical Planning and Analysis, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Brian M Sandroff
- Kessler Foundation, West Orange, NJ, USA
- Department of Physical Medicine & Rehabilitation, Rutgers New Jersey Medical School, Newark, New Jersey, USA
| | - Anthony Feinstein
- Department of Psychiatry, University of Toronto and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurophysiology Service, IRCCS Ospedale San Raffaele, Milan, Italy
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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: 25] [Impact Index Per Article: 12.5] [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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