Subcortical structures in progressive supranuclear palsy: vertex‐based analysis. Issue 3 (14th October 2012)

• Record Type: Journal Article
• Authors: Saini, J.; Bagepally, B. S.; Sandhya, M.; Pasha, S. A.; Yadav, R.; Thennarasu, K.; Pal, P. K.
• Is Part Of: European journal of neurology. Volume 20:Issue 3(2013:Mar.)
• Page Start: 493
• Page End: 501
• Publication Date: 2012-10-14
• Subjects: MRI -- progressive supranuclear palsy -- shape analysis -- thalamus -- volumetry; Neurology -- Periodicals; Nervous system -- Diseases -- Periodicals; 616.8
• DOI: 10.1111/j.1468-1331.2012.03884.x
• Languages: English
• ISSNs: 1351-5101

Abstract

Abstract : Background and purpose: To study the abnormalities of deep grey matter (GM) structures in patients with progressive supranuclear palsy (PSP) using MR volumetry and shape analysis techniques. Methods: Twenty‐eight patients with PSP and 25 matched controls (all were right handed) were evaluated using standard clinical scales. MRI was performed on a 3 tesla MRI scanner using standard protocol which included T1‐3D Turbo Field‐Echo images with 1‐mm slice thickness. The volumes of GM and white matter, total brain and the deep subcortical GM structures, including hippocampus, amygdala, caudate, putamen, globus pallidus and thalamus were extracted using a fully automated tool. Univariate analysis of covariance, adjusted for intracranial volume (ICV), sex and age, was used to explore group differences. Shape analysis was also performed using automated software with age, sex and total brain volume as covariates of no interest in the statistical design at P < 0.05 (FDR corrected). Results: The patients with PSP had significantly lower volumes of bilateral thalami, hippocampus, pallidum and brainstem. Shape analysis of GM structures showed significant surface reduction in bilateral thalami and head of right caudate nucleus. Conclusions: MR volumetry showed abnormalities of various deep GM structures. Shape analysis also revealed focal surface contractions in multiple subcortical structures. Our study highlights the usefulness of this novel technique in detecting abnormalities of deep GM structures.