{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T22:26:36Z","timestamp":1790115996616,"version":"4.0.1"},"reference-count":39,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T00:00:00Z","timestamp":1648166400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["#APP1176426"],"award-info":[{"award-number":["#APP1176426"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["#APP1091593"],"award-info":[{"award-number":["#APP1091593"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Epilepsia"],"published-print":{"date-parts":[[2022,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Around 30% of patients undergoing surgical resection for drug\u2010resistant mesial temporal lobe epilepsy (MTLE) do not obtain seizure freedom. Success of anterior temporal lobe resection (ATLR) critically depends on the careful selection of surgical candidates, aiming at optimizing seizure freedom while minimizing postoperative morbidity. Structural MRI and FDG\u2010PET neuroimaging are routinely used in presurgical assessment and guide the decision to proceed to surgery. In this study, we evaluate the potential of machine learning techniques applied to standard presurgical MRI and PET imaging features to provide enhanced prognostic value relative to current practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Eighty two patients with drug resistant MTLE were scanned with FDG\u2010PET pre\u2010surgery and T1\u2010weighted MRI pre\u2010 and postsurgery. From these images the following features of interest were derived: volume of temporal lobe (TL) hypometabolism, % of extratemporal hypometabolism, presence of contralateral TL hypometabolism, presence of hippocampal sclerosis, laterality of seizure onset volume of tissue resected and % of temporal lobe hypometabolism resected. These measures were used as predictor variables in logistic regression, support vector machines, random forests and artificial neural networks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the study cohort, 24 of 82 (28.3%) who underwent an ATLR for drug\u2010resistant MTLE did not achieve Engel Class I (i.e., free of disabling seizures) outcome at a minimum of 2\u00a0years of postoperative follow\u2010up. We found that machine learning approaches were able to predict up to 73% of the 24 ATLR surgical patients who did not achieve a Class I outcome, at the expense of incorrect prediction for up to 31% of patients who did achieve a Class I outcome. Overall accuracies ranged from 70% to 80%, with an area under the receiver operating characteristic curve (AUC) of .75\u2013.81. We additionally found that information regarding overall extent of both total and significantly hypometabolic tissue resected was crucial to predictive performance, with AUC dropping to .59\u2013.62 using presurgical information alone. Incorporating the laterality of seizure onset and the choice of machine learning algorithm did not significantly change predictive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Significance<\/jats:title>\n                    <jats:p>Collectively, these results indicate that \"acceptable\" to \"good\" patient\u2010specific prognostication for drug\u2010resistant MTLE surgery is feasible with machine learning approaches utilizing commonly collected imaging modalities, but that information on the surgical resection region is critical for optimal prognostication.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/epi.17217","type":"journal-article","created":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T03:15:03Z","timestamp":1646882103000},"page":"1081-1092","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Machine learning approaches for imaging\u2010based prognostication of the outcome of surgery for mesial temporal lobe epilepsy"],"prefix":"10.1111","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0850-3644","authenticated-orcid":false,"given":"Benjamin","family":"Sinclair","sequence":"first","affiliation":[{"name":"Department of Neuroscience Central Clinical School Monash University Melbourne Victoria Australia"},{"name":"Department Neurology Alfred Health Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Varduhi","family":"Cahill","sequence":"additional","affiliation":[{"name":"Department of Medicine University of Melbourne Melbourne Victoria Australia"},{"name":"Academic Neurology Unit Royal Hallamshire Hospital University of Sheffield Sheffield UK"},{"name":"Division of Neuroscience and Experimental Psychology School of Biological Sciences University of Manchester Manchester UK"},{"name":"Department of Neurology Melbourne Brain Centre Royal Melbourne Hospital Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jarrel","family":"Seah","sequence":"additional","affiliation":[{"name":"Department of Radiology Alfred Health Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andy","family":"Kitchen","sequence":"additional","affiliation":[{"name":"Department of Neuroscience Central Clinical School Monash University Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1182-0907","authenticated-orcid":false,"given":"Lucy E.","family":"Vivash","sequence":"additional","affiliation":[{"name":"Department of Neuroscience Central Clinical School Monash University Melbourne Victoria Australia"},{"name":"Department Neurology Alfred Health Melbourne Victoria 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Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie F.","family":"O'Shea","sequence":"additional","affiliation":[{"name":"Melbourne School of Psychological Sciences University of Melbourne Melbourne Victoria Australia"},{"name":"Comprehensive Epilepsy Program Austin Health Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patricia M.","family":"Desmond","sequence":"additional","affiliation":[{"name":"Department of Radiology Royal Melbourne Hospital University of Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rodney J.","family":"Hicks","sequence":"additional","affiliation":[{"name":"Peter MacCallum Cancer Centre and Sir Peter MacCallum Department of Oncology University of Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew P.","family":"Morokoff","sequence":"additional","affiliation":[{"name":"Department of Surgery Royal Melbourne Hospital University of Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"King","sequence":"additional","affiliation":[{"name":"Department of Surgery Royal Melbourne Hospital University of Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gavin C.","family":"Fabinyi","sequence":"additional","affiliation":[{"name":"Department of Surgery Austin Hospital University of Melbourne Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew H.","family":"Kaye","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery Hadassah Hebrew University Hospital Jerusalem 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