From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

卷:57

Review

Wolfers, Thomas^1,2  Buitelaar, Jan K.^3,4  Beckmann, Christian F.^2,3,5  Franke, Barbara^1,6  Marquan, Andre F.^2,7 

[1] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Dept Human Genet, NL-6500 HB Nijmegen, Netherlands

[2] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Donders Ctr Cognit Neuroimaging, NL-6500 HB Nijmegen, Netherlands

[3] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Dept Cognit Neurosci, NL-6500 HB Nijmegen, Netherlands

[4] Radboud Univ Nijmegen, Med Ctr, Karakter Child & Adolescent Psychiany Univ Ctr, NL-6500 HB Nijmegen, Netherlands

[5] Univ Oxford, Ctr Funct MRI Brain FMRIB, Oxford, England

[6] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Dept Psychiat, NL-6500 HB Nijmegen, Netherlands

[7] Kings Coll London, Inst Psychiat, Dept Neuroimaging, London WC2R 2LS, England

关键词: Pattern recognition;    Magnetic resonance imaging;    Psychiatric diagnostics;    Psychiatric disorders;    Mental disorders;    Schizophrenia;    Bipolar disorder;    Major depressive disorder;    Obsessive compulsive disorder;    Social anxiety disorder;    Post-traumatic stress disorder;    Specific phobia;    Attention-deficit/hyperactivity disorder;    Autism spectrum disorder;   

DOI  :  10.1016/j.neubiorev.2015.08.001

来源: Elsevier

【 摘 要 】

Psychiatric disorders are increasingly being recognised as having a biological basis, but their diagnosis is made exclusively behaviourally. A promising approach for 'biomarker' discovery has been based on pattern recognition methods applied to neuroimaging data, which could yield clinical utility in future. In this review we survey the literature on pattern recognition for making diagnostic predictions in psychiatric disorders, and evaluate progress made in translating such findings towards clinical application. We evaluate studies on many criteria, including data modalities used, the types of features extracted and algorithm applied. We identify problems common to many studies, such as a relatively small sample size and a primary focus on estimating generalisability within a single study. Furthermore, we highlight challenges that are not widely acknowledged in the field including the importance of accommodating disease prevalence, the necessity of more extensive validation using large carefully acquired samples, the need for methodological innovations to improve accuracy and to discriminate between multiple disorders simultaneously. Finally, we identify specific clinical contexts in which pattern recognition can add value in the short to medium term. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

【 授权许可】

Free