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Updated: Jan 30, 2026

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Imaging correlates of hand motor performance in multiple sclerosis: A multiparametric structural and functional MRI
Claudio Cordani1, Alessandro Meani1, Federica Esposito2
1Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Background:
Hand motor impairment has considerable effects on daily-life activities of patients with multiple sclerosis (pwMS). Understanding its anatomo-functional substrates is relevant to provide more specific therapeutic interventions.
Objectives:
To investigate the association between hand motor performance and anatomo-functional magnetic resonance imaging (MRI) abnormalities in pwMS.
Methods:
A total of 134 healthy controls (HC) and 366 pwMS underwent the Nine-Hole-Peg-Test (9HPT), structural and resting state (RS) functional MRI. Multivariate analyses identified the independent predictors of hand motor performance.
Results:
PwMS versus HC showed widespread gray matter atrophy, microstructural white matter abnormalities, and decreased RS functional connectivity in motor and cognitive networks. Predictors of worse right-9HPT (R2 = 0.52) were decreased right superior cerebellar peduncle and right lemniscus fractional anisotropy (FA) (p ⩽ 0.02), left angular gyrus atrophy (p < 0.003), decreased RS connectivity in left superior frontal gyrus, and left posterior cerebellum (p < 0.001). Worse left 9HPT (R2 = 0.56) was predicted by decreased right corticospinal FA (p = 0.003), atrophy of left anterior cingulum and left cerebellum (p ⩽ 0.02), decreased RS connectivity of left lingual gyrus and right posterior cerebellum in cerebellar and executive networks (p ⩽ 0.02).
Conclusion:
Structural and functional abnormalities of regions involved in motor functions contribute to explain motor disability in pwMS. The integration of clinical and advanced MRI measures contributes to improve our understanding of multiple sclerosis clinical manifestations.
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