Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach.
Translational psychiatry May 12, 2026 Linda Bryant, Laith Alexander, Sergio Mena et al.
A machine-learning model using structural brain scans predicted which adults with treatment-resistant depression would respond to a single ketamine infusion. The model, trained on 99 participants, achieved 72% balanced accuracy in the discovery sample and 60% in two independent groups, with performance dropping to chance in a saline-treated control group. Greater gray matter volume in frontal regions predicted response, while greater cerebellar volume predicted non-response. The findings suggest that pre-treatment brain structure may help guide personalized treatment decisions for ketamine therapy.