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Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach.
- Source :
-
Psychological medicine [Psychol Med] 2014 Feb; Vol. 44 (3), pp. 519-32. Date of Electronic Publication: 2013 Jun 05. - Publication Year :
- 2014
-
Abstract
- Background: Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD.<br />Method: GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls.<br />Results: The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD.<br />Conclusions: Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.
- Subjects :
- Adult
Algorithms
Bipolar Disorder drug therapy
Bipolar Disorder pathology
Case-Control Studies
Delayed Diagnosis adverse effects
Diagnosis, Differential
Diagnostic and Statistical Manual of Mental Disorders
Feasibility Studies
Female
Humans
Image Processing, Computer-Assisted methods
Magnetic Resonance Imaging classification
Male
Normal Distribution
Pattern Recognition, Automated classification
Bipolar Disorder diagnosis
Brain pathology
Magnetic Resonance Imaging methods
Pattern Recognition, Automated methods
Predictive Value of Tests
Subjects
Details
- Language :
- English
- ISSN :
- 1469-8978
- Volume :
- 44
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Psychological medicine
- Publication Type :
- Academic Journal
- Accession number :
- 23734914
- Full Text :
- https://doi.org/10.1017/S0033291713001013