{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:39:17Z","timestamp":1778884757160,"version":"3.51.4"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100012245","name":"Science and Technology Planning Project of Guangdong Province","doi-asserted-by":"publisher","award":["2022A0505050042"],"award-info":[{"award-number":["2022A0505050042"]}],"id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82102107"],"award-info":[{"award-number":["82102107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["882371988"],"award-info":[{"award-number":["882371988"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82371988"],"award-info":[{"award-number":["82371988"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004000","name":"Guangzhou Municipal Science and Technology Program key projects","doi-asserted-by":"publisher","award":["2023A03J0610"],"award-info":[{"award-number":["2023A03J0610"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004000","name":"Guangzhou Municipal Science and Technology Program key projects","doi-asserted-by":"publisher","award":["202206010106"],"award-info":[{"award-number":["202206010106"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","seizure-journal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Seizure: European Journal of Epilepsy"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1016\/j.seizure.2024.04.021","type":"journal-article","created":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T11:57:46Z","timestamp":1714046266000},"page":"17-27","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"special_numbering":"C","title":["A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery"],"prefix":"10.1016","volume":"119","author":[{"given":"Huanhua","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1004-2795","authenticated-orcid":false,"given":"Kai","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyuan","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biao","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjin","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weijian","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9930-2006","authenticated-orcid":false,"given":"Xueying","family":"Ling","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6199-3929","authenticated-orcid":false,"given":"Hao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.seizure.2024.04.021_bib0001","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/S1474-4422(18)30499-X","article-title":"Global, regional, and national burden of neurological disorders, 1990\u20132016: a systematic analysis for the Global Burden of Disease Study 2016","volume":"18","author":"Feigin","year":"2019","journal-title":"The Lancet Neurology"},{"key":"10.1016\/j.seizure.2024.04.021_bib0002","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1056\/NEJMra1004418","article-title":"Drug-resistant epilepsy","volume":"365","author":"Kwan","year":"2011","journal-title":"New England Journal of Medicine"},{"key":"10.1016\/j.seizure.2024.04.021_bib0003","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1177\/107385840100700410","article-title":"Mesial temporal lobe epilepsy: what have we learned?","volume":"7","author":"Engel","year":"2001","journal-title":"The Neuroscientist"},{"key":"10.1016\/j.seizure.2024.04.021_bib0004","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.1007\/s00259-020-05108-y","article-title":"A deep learning framework for 18F-FDG PET imaging diagnosis in pediatric patients with temporal lobe epilepsy","volume":"48","author":"Zhang","year":"2021","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"10.1016\/j.seizure.2024.04.021_bib0005","article-title":"Localizing epileptic foci before surgery in patients with MRI-negative refractory epilepsy using statistical parameter mapping and three-dimensional stereotactic surface projection based on (18)F-FDG PET","volume":"9","author":"Zhou","year":"2021","journal-title":"Front Bioeng Biotechnol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0006","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1111\/epi.17194","article-title":"Utility of 18F-fluorodeoxyglucose positron emission tomography in presurgical evaluation of patients with epilepsy: a multicenter study","volume":"63","author":"Steinbrenner","year":"2022","journal-title":"Epilepsia"},{"key":"10.1016\/j.seizure.2024.04.021_bib0007","article-title":"Electroclinical and multimodality neuroimaging characteristics and predictors of post-surgical outcome in focal cortical dysplasia type IIIa","volume":"9","author":"Zhang","year":"2021","journal-title":"Front Bioeng Biotechnol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0008","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1016\/j.nicl.2016.05.002","article-title":"Combined 18F-FDG-PET and diffusion tensor imaging in mesial temporal lobe epilepsy with hippocampal sclerosis","volume":"12","author":"Aparicio","year":"2015","journal-title":"NeuroImage: Clinical"},{"key":"10.1016\/j.seizure.2024.04.021_bib0009","article-title":"Combined [18F]FDG-PET with MRI structural patterns in predicting post-surgical seizure outcomes in temporal lobe epilepsy patients","author":"Wang","year":"2022","journal-title":"Eur Radiol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.yebeh.2020.107714","article-title":"Quantitative [18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy","volume":"116","author":"Kini","year":"2021","journal-title":"Epilepsy & Behavior"},{"key":"10.1016\/j.seizure.2024.04.021_bib0011","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1016\/S1474-4422(16)00112-5","article-title":"Advances in the development of biomarkers for epilepsy","volume":"15","author":"Pitk\u00e4nen","year":"2016","journal-title":"Lancet Neurol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0012","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","article-title":"Radiomics: extracting more information from medical images using advanced feature analysis","volume":"48","author":"Lambin","year":"2012","journal-title":"Eur J Cancer"},{"key":"10.1016\/j.seizure.2024.04.021_bib0013","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1007\/s00415-021-10638-y","article-title":"MRI radiomic features-based machine learning approach to classify ischemic stroke onset time","volume":"269","author":"Zhang","year":"2022","journal-title":"J Neurol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0014","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1111\/epi.15612","article-title":"Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: a consensus report from the International league against epilepsy neuroimaging task force","volume":"60","author":"Bernasconi","year":"2019","journal-title":"Epilepsia"},{"key":"10.1016\/j.seizure.2024.04.021_bib0015","doi-asserted-by":"crossref","first-page":"9068","DOI":"10.1038\/s41598-021-87564-6","article-title":"The ANTsX ecosystem for quantitative biological and medical imaging","volume":"11","author":"Tustison","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.seizure.2024.04.021_bib0016","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"van Griethuysen","year":"2017","journal-title":"Cancer Res"},{"key":"10.1016\/j.seizure.2024.04.021_bib0017","doi-asserted-by":"crossref","first-page":"e348","DOI":"10.1016\/S2589-7500(20)30107-2","article-title":"Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study","volume":"2","author":"Zhu","year":"2020","journal-title":"The Lancet Digital Health"},{"key":"10.1016\/j.seizure.2024.04.021_bib0018","series-title":"An introduction to statistical learning: with applications in r","author":"Gareth","year":"2013"},{"key":"10.1016\/j.seizure.2024.04.021_bib0019","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1148\/radiol.2020191145","article-title":"The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping","volume":"295","author":"Zwanenburg","year":"2020","journal-title":"Radiology"},{"key":"10.1016\/j.seizure.2024.04.021_bib0020","unstructured":"R Core Team. R: a language and environment for statistical computing. Vienna, Austria, 2022 https:\/\/www.R-project.org\/."},{"key":"10.1016\/j.seizure.2024.04.021_bib0021","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1177\/0962280214558972","article-title":"Events per variable (EPV) and the relative performance of different strategies for estimating the out-of-sample validity of logistic regression models","volume":"26","author":"Austin","year":"2017","journal-title":"Stat Methods Med Res"},{"key":"10.1016\/j.seizure.2024.04.021_bib0022","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1016\/S0140-6736(11)60890-8","article-title":"The long-term outcome of adult epilepsy surgery, patterns of seizure remission, and relapse: a cohort study","volume":"378","author":"De Tisi","year":"2011","journal-title":"The Lancet"},{"key":"10.1016\/j.seizure.2024.04.021_bib0023","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1007\/s10143-014-0527-9","article-title":"Rates and predictors of seizure freedom in resective epilepsy surgery: an update","volume":"37","author":"Englot","year":"2014","journal-title":"Neurosurg Rev"},{"key":"10.1016\/j.seizure.2024.04.021_bib0024","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/S1474-4422(14)70325-4","article-title":"Development and validation of nomograms to provide individualised predictions of seizure outcomes after epilepsy surgery: a retrospective analysis","volume":"14","author":"Jehi","year":"2015","journal-title":"Lancet Neurol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0025","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.seizure.2013.06.010","article-title":"Preoperative estimation of seizure control after resective surgery for the treatment of epilepsy","volume":"22","author":"Kumar","year":"2013","journal-title":"Seizure"},{"key":"10.1016\/j.seizure.2024.04.021_bib0026","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: the bridge between medical imaging and personalized medicine","volume":"14","author":"Lambin","year":"2017","journal-title":"Nat Rev Clin Oncol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0027","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.nicl.2018.04.024","article-title":"Radiomics analysis allows for precise prediction of epilepsy in patients with low-grade gliomas","volume":"19","author":"Liu","year":"2018","journal-title":"Neuroimage Clin"},{"key":"10.1016\/j.seizure.2024.04.021_bib0028","doi-asserted-by":"crossref","first-page":"E7","DOI":"10.3171\/2022.7.FOCUS2254","article-title":"Preoperative MRI for postoperative seizure prediction: a radiomics study of dysembryoplastic neuroepithelial tumor and a systematic review","volume":"53","author":"Wang","year":"2022","journal-title":"Neurosurg Focus"},{"key":"10.1016\/j.seizure.2024.04.021_bib0029","doi-asserted-by":"crossref","first-page":"19567","DOI":"10.1038\/s41598-020-76283-z","article-title":"Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls","volume":"10","author":"Park","year":"2020","journal-title":"Sci Rep"},{"key":"10.1016\/j.seizure.2024.04.021_bib0030","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.seizure.2021.10.012","article-title":"Radiomic features as a risk factor for early postoperative seizure in patients with meningioma","volume":"93","author":"Xu","year":"2021","journal-title":"Seizure"},{"key":"10.1016\/j.seizure.2024.04.021_bib0031","doi-asserted-by":"crossref","first-page":"235","DOI":"10.3389\/fonc.2020.00235","article-title":"Predicting the type of tumor-related epilepsy in patients with low-grade gliomas: a radiomics study","volume":"10","author":"Wang","year":"2020","journal-title":"Front Oncol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0032","unstructured":"Chang W., Cheng J., Allaire J., et al. shiny: web application framework for R. 2022 https:\/\/CRAN.R-project.org\/package=shiny."},{"key":"10.1016\/j.seizure.2024.04.021_bib0033","article-title":"FDG-PET profiles of extratemporal metabolism as a predictor of surgical failure in temporal lobe epilepsy","volume":"7","author":"Tang","year":"2020","journal-title":"Front Med (Lausanne)"},{"key":"10.1016\/j.seizure.2024.04.021_bib0034","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2021.725926","article-title":"Radiomics for the prediction of epilepsy in patients with frontal glioma","volume":"11","author":"Gao","year":"2021","journal-title":"Front Oncol"},{"key":"10.1016\/j.seizure.2024.04.021_bib0035","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1111\/epi.17217","article-title":"Machine learning approaches for imaging-based prognostication of the outcome of surgery for mesial temporal lobe epilepsy","volume":"63","author":"Sinclair","year":"2022","journal-title":"Epilepsia"},{"key":"10.1016\/j.seizure.2024.04.021_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.eplepsyres.2022.106861","article-title":"Artificial intelligence for medical image analysis in epilepsy","author":"Sollee","year":"2022","journal-title":"Epilepsy Res."},{"key":"10.1016\/j.seizure.2024.04.021_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.eclinm.2023.102269","article-title":"Development and validation of CT-based radiomics deep learning signatures to predict lymph node metastasis in non-functional pancreatic neuroendocrine tumors: a multicohort study","volume":"65","author":"Gu","year":"2023","journal-title":"eClinicalMedicine"}],"container-title":["Seizure: European Journal of Epilepsy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1059131124001262?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1059131124001262?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T17:10:58Z","timestamp":1762362658000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1059131124001262"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":37,"alternative-id":["S1059131124001262"],"URL":"https:\/\/doi.org\/10.1016\/j.seizure.2024.04.021","relation":{},"ISSN":["1059-1311"],"issn-type":[{"value":"1059-1311","type":"print"}],"subject":[],"published":{"date-parts":[[2024,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery","name":"articletitle","label":"Article Title"},{"value":"Seizure: European Journal of Epilepsy","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.seizure.2024.04.021","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Published by Elsevier Ltd on behalf of British Epilepsy Association.","name":"copyright","label":"Copyright"}]}}