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Current trial-and-error prescribing practices may expose patients to ineffective treatment and avoidable adverse effects, underscoring the need for reliable predictive tools to optimize treatment selection and support personalized, evidence-based care. We developed a machine-learning model (support vector classifier) to predict antidepressant response to ketamine using pre-treatment structural MRI data. The model was trained on 99 adults with TRD given a single intravenous ketamine infusion (0.5\u2009mg\/kg). Clinical response was defined as a\u2009\u226550% reduction in MADRS scores 24\u2009h post-infusion. Internal validation used repeated nested cross-validation, and generalizability was tested in two independent ketamine-treated cohorts (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200951) and a saline-treated control group (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200949). Among ketamine-treated participants, 52 (52.5%) responded to treatment. The model achieved a balanced accuracy of 72.2% (sensitivity\u2009=\u200972.3%, specificity\u2009=\u200973.1%, AUC\u2009=\u20090.72) in the discovery sample and 60.0% (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20090.01, AUC\u2009=\u20090.65) in external validation. Greater gray matter volume in frontal regions predicted response, whereas greater cerebellar volume predicted non-response. Performance dropped to chance in the saline cohort (BAC\u2009=\u200941.1%, AUC\u2009=\u20090.45), supporting pharmacologic specificity. These findings present the first machine-learning model for the prediction of ketamine response in TRD using structural neuroimaging and highlight its potential utility for stratified treatment planning and biomarker-informed interventions while providing mechanistic insight into neuroanatomical predictors of antidepressant response.\n                  <\/jats:p>","DOI":"10.1038\/s41398-026-04085-4","type":"journal-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T11:44:02Z","timestamp":1778586242000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach"],"prefix":"10.1038","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-1249-5975","authenticated-orcid":false,"given":"Linda","family":"Bryant","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1297-6548","authenticated-orcid":false,"given":"Laith","family":"Alexander","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sergio","family":"Mena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3278-9264","authenticated-orcid":false,"given":"Yael","family":"Jacob","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2338-9593","authenticated-orcid":false,"given":"Jenna","family":"Jubeir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9442-0043","authenticated-orcid":false,"given":"Philipp T.","family":"Neukam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5862-6650","authenticated-orcid":false,"given":"Laurel S.","family":"Morris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6286-1242","authenticated-orcid":false,"given":"James W.","family":"Murrough","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7590-4325","authenticated-orcid":false,"given":"Rebecca","family":"Price","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikolaos","family":"Koutsouleris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1152-5323","authenticated-orcid":false,"given":"Mitul A.","family":"Mehta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8558-3396","authenticated-orcid":false,"given":"Mario","family":"Juruena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fiona","family":"Coutts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9642-3080","authenticated-orcid":false,"given":"Paris Alexandros","family":"Lalousis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,12]]},"reference":[{"key":"4085_CR1","first-page":"23","volume":"58","author":"M Thase","year":"1997","unstructured":"Thase M, Rush J. 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The Icahn School of Medicine (employer of Dr. Murrough) is named on a patent and has entered into a licensing agreement and will receive payments related to the use of ketamine or esketamine for the treatment of depression. The Icahn School of Medicine is also named on a patent related to the use of ketamine for the treatment of PTSD. Dr. Murrough is not named on these patents and will not receive any payments. Prof. Mehta has provided consultation services for Neurocentrx, Curie.bio and Nxera. Prof. Price is the named inventor on a University of Pittsburgh-owned patent filing optioned to TaJa Health, Inc., and has received consulting fees from Lightstone Ventures. Dr. Lalousis has received honoraria for talks presented at educational meetings organized by Boehringer Ingelheim outside the submitted work. All other authors report no potential conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"330"}}