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Neurobiological support to the diagnosis of ADHD in stimulant‐naïve adults: pattern recognition analyses of MRI data
Author(s) -
ChaimAvancini T. M.,
Doshi J.,
Zanetti M. V.,
Erus G.,
Silva M. A.,
Duran F. L. S.,
Cavallet M.,
Serpa M. H.,
Caetano S. C.,
Louza M. R.,
Davatzikos C.,
Busatto G. F.
Publication year - 2017
Publication title -
acta psychiatrica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.849
H-Index - 146
eISSN - 1600-0447
pISSN - 0001-690X
DOI - 10.1111/acps.12824
Subject(s) - stimulant , attention deficit hyperactivity disorder , psychology , diffusion mri , audiology , magnetic resonance imaging , medicine , psychiatry , radiology
Objective In adulthood, the diagnosis of attention‐deficit/hyperactivity disorder ( ADHD ) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning‐based pattern classification methods to structural MRI and diffusion tensor imaging ( DTI ) data obtained from stimulant‐naïve adults with childhood‐onset ADHD and healthy controls ( HC ). Method Sixty‐seven ADHD patients and 66 HC underwent high‐resolution T1‐weighted and DTI acquisitions. A support vector machine ( SVM ) classifier with a non‐linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain. Results The discrimination between a mixed‐gender ADHD subgroup and individually matched HC ( n = 58 each) yielded area‐under‐the‐curve ( AUC ) and diagnostic accuracy ( DA ) values of up to 0.71% and 66% ( P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% ( P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC ). Conclusion Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.