Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Molecular Psychiatry
Abraham NunesENIGMA Bipolar Disorders Working Group

Abstract

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of ...Continue Reading

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Citations

Aug 11, 2019·Psychiatry and Clinical Neurosciences·Abhishek AppajiNaren P Rao
Feb 5, 2019·Journal of Neuroimaging : Official Journal of the American Society of Neuroimaging·Lauren E SalminenPaul M Thompson
Jul 30, 2020·Human Brain Mapping·Christopher R K ChingUNKNOWN ENIGMA Bipolar Disorder Working Group
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Apr 18, 2021·Molecular Psychiatry·Sean R McWhinneyUNKNOWN ENIGMA Bipolar Disorders Working Group
Feb 2, 2022·BJPsych Open·Mojtaba Oraki KohshourThomas G Schulze

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Software Mentioned

lme4
ENIGMA
FreeSurfer
R
BD
LOSO
HSROC
Tomek link
R Statistical Programming Language
imblearn

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