Meeting Banner
Abstract #3495

3D Texture Analysis on fMRI to Detect Alterations in the Striatal Network of an Alcohol-Preferring Rat Model

Silvia Ruiz-España1, Rafael Ortiz-Ramón1, Úrsula Pérez-Ramírez1, Antonio Díaz-Parra1, Roberto Ciccocioppo2, Santiago Canals3, and David Moratal1

1Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain, 2School of Pharmacy, University of Camerino, Camerino, Italy, 3Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d' Alacant, Spain

We propose an approach that uses 3D texture features extracted from fMRI to detect changes in the striatal network induced by alcohol drinking. Scans of eighteen alcohol-preferring rats before and after 30 days of alcohol consumption were analyzed. Data were preprocessed and a group independent component analysis was performed to identify striatal network; in total 36 volumes of interest were studied. Texture analysis was performed using 43 texture features and six predictive models. An AUC of 0.927±0.089 (sensitivity=84.25%, specificity=81.75%) was obtained for the best model (random forests). The proposed method was able to accurately identify subjects with alcohol use disorders.

This abstract and the presentation materials are available to members only; a login is required.

Join Here