ArticleJournal of neurology2025
Spinal cord structural changes in SPG4: insights from a large cohort using advanced neuroimaging.
Article in Journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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7 authors.
Funding
Abstract
backgroundSPG4 is the most common autosomal dominant hereditary spastic paraplegia (HSP), a neurodegenerative disorder characterized by progressive spasticity and weakness in the lower limbs due to corticospinal tract and fasciculus gracilis degeneration. While previous neuroimaging studies have focused on structural alterations in the spinal cord (SC), diffusion-related abnormalities remain insufficiently explored in a large SPG4 cohort.
objectivesTo assess structural and diffusion abnormalities in the cervical and upper thoracic SC in a large SPG4 cohort and evaluate correlations with demographic and clinical variables.
methodsWe analyzed cervical SC morphology and diffusion properties in 40 SPG4-HSP patients and 37 age- and sex-matched healthy controls using diffusion tensor imaging (DTI). We also explored MRI parameters in relation to genotype and disease onset subgroups, employing linear mixed-effects models to assess the impact of clinical data on structural and diffusion measures.
resultsSPG4-HSP patients exhibited significant reductions in cervical SC cross-sectional areas without anteroposterior flattening. DTI analyses revealed decreased fractional anisotropy (FA) and increased diffusivity in the fasciculus cuneatus, fasciculus gracilis, lateral corticospinal tract and rubrospinal tract (RST). A weak but significant correlation was observed between FA reduction in RST and disease onset. SC gray matter area was smaller in patients with late-onset vs those with early-onset.
conclusionsOur findings provide strong evidence of tract-specific axonal degeneration in the cervical SC in SPG4-HSP and highlight the potential of DTI as a biomarker for disease progression. Future studies with larger cohorts should explore subgroup analyses and longitudinal changes to enhance understanding of disease evolution.
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