Progression of Microstructural Damage in Spinocerebellar Ataxia Type 2: A Longitudinal DTI Study

Abstract

BACKGROUND AND PURPOSE:The ability of DTI to track the progression of microstructural damage in patients with inherited ataxias has not been explored so far. We performed a longitudinal DTI study in patients with spinocerebellar ataxia type 2.

Regional Cerebral Disease Progression in Friedreich's Ataxia: A Longitudinal Diffusion Tensor Imaging Study

“…Diffusion‐sensitizing gradients were applied along 15 non‐collinear directions using b‐values of 0 (b0 image) and 1,000 s/mm 2 . Maps of fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, and mode of anisotropy were calculated from DWIs as previously described …”

“…Longitudinal analyses included tensor‐based morphometry (TBM) to assess progression of regional atrophy and tract‐based spatial statistics (TBSS) to assess progression of microstructural damage as reflected by DTI. Both techniques were detailed in previous studies by our group …”

“…Maps of fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, and mode of anisotropy were calculated from DWIs as previously described. 17 Longitudinal analyses included tensor-based morphometry (TBM) 18 to assess progression of regional atrophy and tractbased spatial statistics (TBSS) 19 to assess progression of microstructural damage as reflected by DTI. Both techniques were detailed in previous studies by our group.…”

“…Both techniques were detailed in previous studies by our group. 17,20,21 We employed TBM instead of conventional VBM because it does not rely on preventive gray matter and WM segmentation, 18 which can be cumbersome in the brainstem and cerebellum. Moreover, as compared to a previous study, 8 we performed an improved DTI data processing which includes the use of an updated version of the nonlinear coregistration algorithm implemented in FSL 5.0.2, 22 rotation of the b-matrix, 23 use of a constrained nonlinear least squares approach for estimating the diffusion tensor, as well as Pvalues calculation and correction for multiple comparisons through threshold-free cluster enhancement (TFCE), thereby avoiding the use of an arbitrary threshold for the initial cluster formation.…”

An assessment of the correlation between early postinfarction pyramidal tract Wallerian degeneration and nerve function recovery using diffusion tensor imaging

“…Since brain nerve fibers are uniformly oriented, the membrane structure of neurons (mainly axonal and myelin membrane) can effectively prevent water diffusion in a perpendicular direction, resulting in stronger water diffusion in the direction of nerve fibers compared with the vertical direction (Samartzis et al, 2014). However, structural changes in the nerve fibers cause alterations in water diffusion, leading to differences in DTI (Mascalchi et al, 2015). Using this technique, a previous study on the microstructure of white matter in patients with Cushing's syndrome was conducted and revealed a marked change in the integrity of white matter fibers with demyelinating lesions (Huang et al, 2014;Pires et al, 2015), suggesting DTI might be a reliable approach for the diagnosis of nerve-related diseases.…”