Prediction of the Clinical Severity of Progressive Supranuclear Palsy by Diffusion Tensor Imaging.

ABSTRACT: Progressive supranuclear palsy (PSP) is characterized by a rapid and progressive clinical course. A timely and objective image-based evaluation of disease severity before standard clinical assessments might increase the diagnostic confidence of the neurologist. We sought to investigate whether features from diffusion tensor imaging of the entire brain with a machine learning algorithm, rather than a few pathogenically involved regions, may predict the clinical severity of PSP. Fifty-three patients who met the diagnostic criteria for probable PSP were subjected to diffusion tensor imaging. Of them, 15 underwent follow-up imaging. Clinical severity was assessed by the neurological examinations. Mean diffusivity and fractional anisotropy maps were spatially co-registered, normalized, and parc

SUBMITTER: Chen YL 

PROVIDER: S-EPMC7020078 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature