Journal
EUROPEAN NEUROPSYCHOPHARMACOLOGY
Volume 26, Issue 2, Pages 246-254Publisher
ELSEVIER
DOI: 10.1016/j.euroneuro.2015.12.014
Keywords
Obsessive-compulsive disorder; Structural magnetic resonance imaging; Multivariate pattern analysis; Support vector machine; Gaussian process classifier
Funding
- National Natural Science Foundation of China [81030027, 81171488, 81227002, 81220108013]
- National Key Technologies RD Program [2012BA101603]
- Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of China [IRT1272]
Ask authors/readers for more resources
Magnetic resonance imaging (MRI) studies have revealed brain structural abnormalities in obsessive-compulsive disorder (OCD) patients, involving both gray matter (GM) and white matter (WM). However, the results of previous publications were based on average differences between groups, which limited their usages in clinical practice. Therefore, the aim of this study was to examine whether the application of multivariate pattern analysis (MVPA) to high-dimensional structural images would allow accurate discrimination between OCD patients and healthy control subjects (HCS). High-resolution T1-weighted images were acquired from 33 OCD patients and 33 demographically matched HCS in a 3.0 T scanner. Differences in GM and WM volume between OCD and HCS were examined using two types of well-established MVPA techniques: support vector machine (SVM) and Gaussian process classifier (GPC). We also drew a receiver operating characteristic (ROC) curve to evaluate the performance of each classifier. The classification accuracies for both classifiers using GM and WM anatomy were all above 75%. The highest classification accuracy (81.82%, P<0.001) was achieved with the SVM classifier using WM information. Regional brain anomalies with high discriminative power were based on three distributed networks including the fronto-striatal circuit, the temporo-parieto-occipital junction and the cerebellum. Our study illustrated that both GM and WM anatomical features may be useful in differentiating OCD patients from HCS. WM volume using the SVM approach showed the highest accuracy in our population for revealing group differences, which suggested its potential diagnostic role in detecting highly enriched OCD patients at the level of the individual. (C) 2015 Elsevier B.V. and ECNP. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available