Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/85275
Title: Huntington's disease : morphometric chances in prodromal and diagnosed patients
Authors: Leitão, Rui Pedro Rodrigues Pereira 
Orientador: Caetano, Gina
Castelo-Branco, Miguel
Keywords: Huntington’s disease; MRI; cerebral cortex; cortical thickness; cross sectional analysis
Issue Date: Apr-2013
Abstract: Neuroimaging studies have proven to be a valuable resource in Huntington’s disease (HD). As an autosomal dominant genetic disorder, it is possible to identify individuals before they manifest clinical symptoms (“prodromal HD”). This study was designed to assess if neuroimaging measures could be useful to successfully distinguish prodromal individuals from previously clinically diagnosed patients. Seven participants with previously clinically diagnosed disease and eight individuals in a presymptomatic state underwent brain magnetic resonance imaging (MRI) and were matched and compared to a group of thirteen healthy controls. Cortical reconstruction and volumetric segmentation was performed with FreeSurfer 5.1. We have found significant statistical differences on Caudate, Putamen and Globus Pallidus, from both hemispheres. Diagnosed group had smaller volumes when compared to Prodromal and Control group. Thickness maps derived from Diagnosed and Control groups’ comparison revealed a thinning pattern affecting mostly the posterior and superior cerebral regions. Our results suggest that structural MRI volumes and thickness maps can be useful to monitor Huntington’s disease progression, allowing researchers to identify individuals in different stages of the disease. Clinical trials might benefit the most, by synergizing the current clinical diagnostic method with MRI measures to track neurodegenerative patterns of HD
Description: Trabalho final de mestrado integrado em medicina área científica de Neurociências, apresentado á Faculdade de Medicina da Universidade de Coimbra
URI: https://hdl.handle.net/10316/85275
Rights: openAccess
Appears in Collections:UC - Dissertações de Mestrado
FMUC Medicina - Teses de Mestrado

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