In vivo assessment of neurodegeneration in Spinocerebellar Ataxia type 7

• Main Authors: Jacob A. Parker, Shabbir H. Merchant, Sanaz Attaripour-Isfahani, Hyun Joo Cho, Patrick McGurrin, Brian P. Brooks, Albert R. La Spada, Mark Hallett, Laryssa A. Huryn, Silvina G. Horovitz
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: NeuroImage: Clinical
• Subjects: Spinocerebellar Ataxia type 7; Ataxia; Diffusion tensor imaging; Neurodegeneration; MRI
• Online Access: http://www.sciencedirect.com/science/article/pii/S221315822100005X

Spinocerebellar Ataxia type 7 (SCA7) is a neurodegenerative disease characterized by progressive cerebellar ataxia and retinal degeneration. Increasing loss of visual function complicates the use of clinical scales to track the progression of motor symptoms, hampering our ability to develop accurate biomarkers of disease progression, and thus test the efficacy of potential treatments. We aimed to identify imaging measures of neurodegeneration, which may more accurately reflect SCA7 severity and progression. While common structural MRI techniques have been previously used for this purpose, they can be biased by neurodegeneration-driven increases in extracellular CSF-like water. In a cross-sectional study, we analyzed diffusion tensor imaging (DTI) data collected from a cohort of 13 SCA7 patients and 14 healthy volunteers using: 1) a diffusion tensor-based image registration technique, and 2) a dual-compartment DTI model to control for the potential increase in extracellular CSF-like water. These methodologies allowed us to assess both volumetric and microstructural abnormalities in both white and gray matter brain-wide in SCA7 patients for the first time. To measure tissue volume, we performed diffusion tensor-based morphometry (DTBM) using the tensor-based registration. To assess tissue microstructure, we computed the parenchymal mean diffusivity (pMD) and parenchymal fractional anisotropy (pFA) using the dual compartment model. This model also enabled us to estimate the parenchymal volume fraction (pVF), a measure of parenchymal tissue volume within a given voxel. While DTBM and pVF revealed tissue loss primarily in the brainstem, cerebellum, thalamus, and major motor white matter tracts in patients (p < 0.05, FWE corrected; Hedge’s g > 1), pMD and pFA detected microstructural abnormalities in virtually all tissues brain-wide (p < 0.05, FWE corrected; Hedge’s g > 1). The Scale for the Assessment and Rating of Ataxia trended towards correlation with cerebellar pVF (r = −0.66, p = 0.104, FDR corrected) and global white matter pFA (r = −0.64, p = 0.104, FDR corrected). These results advance our understanding of neurodegeneration in living SCA7 patients by providing the first voxel-wise characterization of white matter volume loss and gray matter microstructural abnormalities. Moving forward, this comprehensive approach could be applied to characterize the full spatiotemporal pattern of neurodegeneration in SCA7, and potentially develop an accurate imaging biomarker of disease progression.