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Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

Abstract：

BACKGROUND:To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. METHOD:One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. RESULTS:At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). CONCLUSIONS:We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.

journal_name

Psychol Med

journal_title

Psychological medicine

authors

Mourao-Miranda J,Reinders AA,Rocha-Rego V,Lappin J,Rondina J,Morgan C,Morgan KD,Fearon P,Jones PB,Doody GA,Murray RM,Kapur S,Dazzan P

doi

10.1017/S0033291711002005

subject

Has Abstract

pub_date

2012-05-01 00:00:00

pages

1037-47

issue

eissn

0033-2917

issn

1469-8978

pii

S0033291711002005

journal_volume

pub_type

杂志文章

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Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.