Tract-based spatial statistics of diffusion tensor imaging in hereditary spastic paraplegia with thin corpus callosum reveals widespread white matter changes

PURPOSE We aimed to investigate white matter diffusivity abnormalities in hereditary spastic paraplegia with thin corpus callosum (HSP-TCC) patients in relation with electrophysiological findings. MATERIALS AND METHODS Brain magnetic resonance imaging (MRI) and diffusion tensor imaging were performed on four HSP-TCC patients and 15 age-matched healthy subjects. Voxel-wise statistical analysis of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity maps were carried out using tract-based spatial statistics, and significantly affected voxels were labeled using a human white matter atlas. Conventional nerve conduction studies, cortical and spinal-root motor evoked potentials, and somatosensory evoked potentials were examined in three patients. RESULTS On MRI, all patients had a thin corpus callosum with mild T2 hyperintensity in the periventricular white matter. Compared to control subjects, we detected widespread significant decreases in fractional anisotropy, and increases in axial diffusivity, radial diffusivity, and mean diffusivity in structures including in the corpus callosum, motor, and non-motor white matter tracts in HSP-TCC patients. Several different regions showed significant reduction in axial diffusivity. Electrophysiological studies revealed prolonged central motor conduction times and reduced cortical motor evoked potentials and somatosensory evoked potentials amplitudes in all patients. One patient had low sural sensory nerve action potential suggestive of axonal neuropathy. CONCLUSION Tract-based spatial statistics of diffusion tensor imaging revealed a more widespread involvement of white matter in HSP-TCC patients than has previously been detected by conventional MRI. This may explain the broad spectrum of electrophysiological and neurological abnormalities that complicate hereditary spastic paraplegia in these patients.