{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T07:52:15Z","timestamp":1785311535648,"version":"3.55.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:00:00Z","timestamp":1642032000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:00:00Z","timestamp":1642032000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100009601","name":"Beijing Municipal Administration of Hospitals","doi-asserted-by":"publisher","award":["Grant No. DFL20180802"],"award-info":[{"award-number":["Grant No. DFL20180802"]}],"id":[{"id":"10.13039\/501100009601","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s00330-021-08490-9","type":"journal-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T09:02:56Z","timestamp":1642064576000},"page":"3880-3888","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Individual [18F]FDG PET and functional MRI based on simultaneous PET\/MRI may predict seizure recurrence after temporal lobe epilepsy surgery"],"prefix":"10.1007","volume":"32","author":[{"given":"Jingjuan","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bixiao","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaqin","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoguang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0425-3921","authenticated-orcid":false,"given":"Jie","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"8490_CR1","doi-asserted-by":"publisher","first-page":"116706","DOI":"10.1016\/j.neuroimage.2020.116706","volume":"213","author":"R Rodriguez-Cruces","year":"2020","unstructured":"Rodriguez-Cruces R, Bernhardt BC, Concha L (2020) Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy. Neuroimage 213:116706. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.116706","journal-title":"Neuroimage"},{"key":"8490_CR2","doi-asserted-by":"publisher","first-page":"102714","DOI":"10.1016\/j.nicl.2021.102714","volume":"31","author":"W Li","year":"2021","unstructured":"Li W, Jiang Y, Qin Y et al (2021) Structural and functional reorganization of contralateral hippocampus after temporal lobe epilepsy surgery. Neuroimage Clin 31:102714. https:\/\/doi.org\/10.1016\/j.nicl.2021.102714","journal-title":"Neuroimage Clin"},{"key":"8490_CR3","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/S0140-6736(18)32596-0","volume":"393","author":"RD Thijs","year":"2019","unstructured":"Thijs RD, Surges R, O\u2019Brien TJ, Sander JW (2019) Epilepsy in adults. Lancet 393:689\u2013701. https:\/\/doi.org\/10.1016\/S0140-6736(18)32596-0","journal-title":"Lancet"},{"key":"8490_CR4","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/S1474-4422(16)00112-5","volume":"15","author":"A Pitkanen","year":"2016","unstructured":"Pitkanen A, Loscher W, Vezzani A et al (2016) Advances in the development of biomarkers for epilepsy. Lancet Neurol 15:843\u2013856. https:\/\/doi.org\/10.1016\/S1474-4422(16)00112-5","journal-title":"Lancet Neurol"},{"key":"8490_CR5","doi-asserted-by":"publisher","first-page":"1804","DOI":"10.1016\/j.clinph.2018.02.135","volume":"129","author":"BT Grobelny","year":"2018","unstructured":"Grobelny BT, London D, Hill TC, North E, Dugan P, Doyle WK (2018) Betweenness centrality of intracranial electroencephalography networks and surgical epilepsy outcome. Clin Neurophysiol 129:1804\u20131812. https:\/\/doi.org\/10.1016\/j.clinph.2018.02.135","journal-title":"Clin Neurophysiol"},{"key":"8490_CR6","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1001\/jamaneurol.2018.4316","volume":"76","author":"JP Andrews","year":"2019","unstructured":"Andrews JP, Gummadavelli A, Farooque P et al (2019) Association of seizure spread with surgical failure in epilepsy. JAMA Neurol 76:462\u2013469. https:\/\/doi.org\/10.1001\/jamaneurol.2018.4316","journal-title":"JAMA Neurol"},{"key":"8490_CR7","doi-asserted-by":"publisher","first-page":"3635","DOI":"10.1093\/brain\/aws296","volume":"135","author":"J O\u2019Muircheartaigh","year":"2012","unstructured":"O\u2019Muircheartaigh J, Vollmar C, Barker GJ et al (2012) Abnormal thalamocortical structural and functional connectivity in juvenile myoclonic epilepsy. Brain 135:3635\u20133644. https:\/\/doi.org\/10.1093\/brain\/aws296","journal-title":"Brain"},{"key":"8490_CR8","doi-asserted-by":"publisher","first-page":"1851","DOI":"10.1002\/hbm.20982","volume":"31","author":"Z Zhang","year":"2010","unstructured":"Zhang Z, Lu G, Zhong Y et al (2010) fMRI study of mesial temporal lobe epilepsy using amplitude of low-frequency fluctuation analysis. Hum Brain Mapp 31:1851\u20131861. https:\/\/doi.org\/10.1002\/hbm.20982","journal-title":"Hum Brain Mapp"},{"key":"8490_CR9","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.jneumeth.2008.04.012","volume":"172","author":"QH Zou","year":"2008","unstructured":"Zou QH, Zhu CZ, Yang Y et al (2008) An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. J Neurosci Methods 172:137\u2013141. https:\/\/doi.org\/10.1016\/j.jneumeth.2008.04.012","journal-title":"J Neurosci Methods"},{"key":"8490_CR10","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1089\/brain.2018.0601","volume":"9","author":"G Hwang","year":"2019","unstructured":"Hwang G, Nair VA, Mathis J et al (2019) Using low-frequency oscillations to detect temporal lobe epilepsy with machine learning. Brain Connect 9:184\u2013193. https:\/\/doi.org\/10.1089\/brain.2018.0601","journal-title":"Brain Connect"},{"key":"8490_CR11","doi-asserted-by":"publisher","first-page":"1806","DOI":"10.1007\/s00259-019-04356-x","volume":"46","author":"J Tomas","year":"2019","unstructured":"Tomas J, Pittau F, Hammers A et al (2019) The predictive value of hypometabolism in focal epilepsy: a prospective study in surgical candidates. Eur J Nucl Med Mol Imaging 46:1806\u20131816. https:\/\/doi.org\/10.1007\/s00259-019-04356-x","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"8490_CR12","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1002\/ana.25405","volume":"85","author":"V Cahill","year":"2019","unstructured":"Cahill V, Sinclair B, Malpas CB et al (2019) Metabolic patterns and seizure outcomes following anterior temporal lobectomy. Ann Neurol 85:241\u2013250. https:\/\/doi.org\/10.1002\/ana.25405","journal-title":"Ann Neurol"},{"key":"8490_CR13","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.seizure.2016.07.019","volume":"41","author":"T Higo","year":"2016","unstructured":"Higo T, Sugano H, Nakajima M et al (2016) The predictive value of FDG-PET with 3D-SSP for surgical outcomes in patients with temporal lobe epilepsy. Seizure 41:127\u2013133. https:\/\/doi.org\/10.1016\/j.seizure.2016.07.019","journal-title":"Seizure"},{"key":"8490_CR14","doi-asserted-by":"publisher","first-page":"2037","DOI":"10.1111\/epi.16333","volume":"60","author":"B Abbasi","year":"2019","unstructured":"Abbasi B, Goldenholz DM (2019) Machine learning applications in epilepsy. Epilepsia 60:2037\u20132047. https:\/\/doi.org\/10.1111\/epi.16333","journal-title":"Epilepsia"},{"key":"8490_CR15","doi-asserted-by":"publisher","unstructured":"An Q, Yu L(2021) A heterogeneous network embedding framework for predicting similarity-based drug-target interactions. Brief Bioinform. bbab275. https:\/\/doi.org\/10.1093\/bib\/bbab275","DOI":"10.1093\/bib\/bbab275"},{"key":"8490_CR16","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1016\/j.nicl.2018.06.008","volume":"19","author":"YH Wang","year":"2018","unstructured":"Wang YH et al (2018) Comparison between simultaneously acquired arterial spin labeling and [18F]FDG PET in mesial temporal lobe epilepsy assisted by a PET\/MR system and SEEG. Neuroimage Clin 19:824\u2013830. https:\/\/doi.org\/10.1016\/j.nicl.2018.06.008","journal-title":"Neuroimage Clin"},{"key":"8490_CR17","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1111\/epi.13709","volume":"58","author":"IE Scheffer","year":"2017","unstructured":"Scheffer IE, Berkovic S, Capovilla G et al (2017) ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia 58:512\u2013521. https:\/\/doi.org\/10.1111\/epi.13709","journal-title":"Epilepsia"},{"key":"8490_CR18","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1148\/radiol.2020191008","volume":"294","author":"MN DeSalvo","year":"2020","unstructured":"DeSalvo MN, Tanaka N, Douw L, Cole AJ, Stufflebeam SM (2020) Contralateral preoperative resting-state functional MRI network integration is associated with surgical outcome in temporal lobe epilepsy. Radiology 294:622\u2013627. https:\/\/doi.org\/10.1148\/radiol.2020191008","journal-title":"Radiology"},{"key":"8490_CR19","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.3389\/fneur.2019.01263","volume":"10","author":"AS Job","year":"2019","unstructured":"Job AS, David O, Minotti L, Bartolomei F, Chabardes S, Kahane P (2019) Epileptogenicity maps of intracerebral fast activities (60\u2013100 Hz) at seizure onset in epilepsy surgery candidates. Front Neurol 10:1263. https:\/\/doi.org\/10.3389\/fneur.2019.01263","journal-title":"Front Neurol"},{"key":"8490_CR20","doi-asserted-by":"publisher","first-page":"3130","DOI":"10.1007\/s00259-020-04791-1","volume":"47","author":"S Lagarde","year":"2020","unstructured":"Lagarde S, Boucekine M, McGonigal A et al (2020) Relationship between PET metabolism and SEEG epileptogenicity in focal lesional epilepsy. Eur J Nucl Med Mol Imaging 47:3130\u20133142. https:\/\/doi.org\/10.1007\/s00259-020-04791-1","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"8490_CR21","doi-asserted-by":"publisher","first-page":"1583","DOI":"10.1111\/epi.14474","volume":"59","author":"Y Lin","year":"2018","unstructured":"Lin Y, Fang YD, Wu G et al (2018) Quantitative positron emission tomography-guided magnetic resonance imaging postprocessing in magnetic resonance imaging-negative epilepsies. Epilepsia 59:1583\u20131594. https:\/\/doi.org\/10.1111\/epi.14474","journal-title":"Epilepsia"},{"key":"8490_CR22","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1111\/epi.13762","volume":"58","author":"VL Morgan","year":"2017","unstructured":"Morgan VL, Englot DJ, Rogers BP et al (2017) Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy. Epilepsia 58:1251\u20131260. https:\/\/doi.org\/10.1111\/epi.13762","journal-title":"Epilepsia"},{"key":"8490_CR23","doi-asserted-by":"publisher","first-page":"2285","DOI":"10.1212\/WNL.0000000000004035","volume":"88","author":"X He","year":"2017","unstructured":"He X, Doucet GE, Pustina D, Sperling MR, Sharan AD, Tracy JI (2017) Presurgical thalamic \u201chubness\u201d predicts surgical outcome in temporal lobe epilepsy. Neurology 88:2285\u20132293. https:\/\/doi.org\/10.1212\/WNL.0000000000004035","journal-title":"Neurology"},{"key":"8490_CR24","doi-asserted-by":"publisher","first-page":"e758","DOI":"10.1212\/WNL.0000000000011315","volume":"96","author":"N Sinha","year":"2021","unstructured":"Sinha N, Wang Y, Moreira da Silva N et al (2021) Structural brain network abnormalities and the probability of seizure recurrence after epilepsy surgery. Neurology 96:e758\u2013e771. https:\/\/doi.org\/10.1212\/WNL.0000000000011315","journal-title":"Neurology"},{"key":"8490_CR25","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1002\/hbm.20625","volume":"30","author":"G Bettus","year":"2009","unstructured":"Bettus G, Guedj E, Joyeux F et al (2009) Decreased basal fMRI functional connectivity in epileptogenic networks and contralateral compensatory mechanisms. Hum Brain Mapp 30:1580\u20131591. https:\/\/doi.org\/10.1002\/hbm.20625","journal-title":"Hum Brain Mapp"},{"key":"8490_CR26","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1089\/brain.2014.0251","volume":"5","author":"VL Morgan","year":"2015","unstructured":"Morgan VL, Abou-Khalil B, Rogers BP (2015) Evolution of functional connectivity of brain networks and their dynamic interaction in temporal lobe epilepsy. Brain Connect 5:35\u201344. https:\/\/doi.org\/10.1089\/brain.2014.0251","journal-title":"Brain Connect"},{"key":"8490_CR27","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1111\/epi.13377","volume":"57","author":"F Chassoux","year":"2016","unstructured":"Chassoux F, Artiges E, Semah F et al (2016) Determinants of brain metabolism changes in mesial temporal lobe epilepsy. Epilepsia 57:907\u2013919. https:\/\/doi.org\/10.1111\/epi.13377","journal-title":"Epilepsia"},{"key":"8490_CR28","doi-asserted-by":"publisher","first-page":"103742","DOI":"10.1016\/j.compbiomed.2020.103742","volume":"120","author":"HJ Jo","year":"2020","unstructured":"Jo HJ, Reynolds RC, Gotts SJ et al (2020) Fast detection and reduction of local transient artifacts in resting-state fMRI. Comput Biol Med 120:103742. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.103742","journal-title":"Comput Biol Med"},{"key":"8490_CR29","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1111\/epi.13658","volume":"58","author":"L Gupta","year":"2017","unstructured":"Gupta L, Janssens R, Vlooswijk MC et al (2017) Towards prognostic biomarkers from BOLD fluctuations to differentiate a first epileptic seizure from new-onset epilepsy. Epilepsia 58:476\u2013483. https:\/\/doi.org\/10.1111\/epi.13658","journal-title":"Epilepsia"},{"key":"8490_CR30","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1002\/hbm.21076","volume":"32","author":"W Liao","year":"2011","unstructured":"Liao W, Zhang Z, Pan Z et al (2011) Default mode network abnormalities in mesial temporal lobe epilepsy: a study combining fMRI and DTI. Hum Brain Mapp 32:883\u2013895. https:\/\/doi.org\/10.1002\/hbm.21076","journal-title":"Hum Brain Mapp"},{"key":"8490_CR31","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.brainresbull.2020.05.016","volume":"162","author":"Q Xu","year":"2020","unstructured":"Xu Q, Hu Z, Yang F et al (2020) Resting state signal latency assesses the propagation of intrinsic activations and estimates anti-epileptic effect of levetiracetam in Rolandic epilepsy. Brain Res Bull 162:125\u2013131. https:\/\/doi.org\/10.1016\/j.brainresbull.2020.05.016","journal-title":"Brain Res Bull"},{"key":"8490_CR32","doi-asserted-by":"publisher","first-page":"1791","DOI":"10.3174\/ajnr.A5814","volume":"39","author":"K Shang","year":"2018","unstructured":"Shang K, Wang J, Fan X et al (2018) Clinical value of hybrid TOF-PET\/MR imaging-based multiparametric imaging in localizing seizure focus in patients with MRI-negative temporal lobe epilepsy. AJNR Am J Neuroradiol 39:1791\u20131798. https:\/\/doi.org\/10.3174\/ajnr.A5814","journal-title":"AJNR Am J Neuroradiol"},{"key":"8490_CR33","doi-asserted-by":"publisher","first-page":"1831","DOI":"10.1002\/acn3.51168","volume":"7","author":"J Wang","year":"2020","unstructured":"Wang J, Shan Y, Dai J et al (2020) Altered coupling between resting-state glucose metabolism and functional activity in epilepsy. Ann Clin Transl Neurol 7:1831\u20131842. https:\/\/doi.org\/10.1002\/acn3.51168","journal-title":"Ann Clin Transl Neurol"},{"key":"8490_CR34","doi-asserted-by":"publisher","first-page":"2904","DOI":"10.1007\/s00259-021-05220-7","volume":"48","author":"Y Zhou","year":"2021","unstructured":"Zhou Y, Ma X-L, Zhang T et al (2021) Use of radiomics based on 18F-FDG PET\/CT and machine learning methods to aid clinical decision-making in the classification of solitary pulmonary lesions: an innovative approach. Eur J Nucl Med Mol Imaging 48:2904\u20132913. https:\/\/doi.org\/10.1007\/s00259-021-05220-7","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"8490_CR35","doi-asserted-by":"publisher","first-page":"23772","DOI":"10.1073\/pnas.1913092116","volume":"116","author":"M Halgren","year":"2019","unstructured":"Halgren M, Ulbert I, Bastuji H et al (2019) The generation and propagation of the human alpha rhythm. Proc Natl Acad Sci U S A 116:23772\u201323782. https:\/\/doi.org\/10.1073\/pnas.1913092116","journal-title":"Proc Natl Acad Sci U S A"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-021-08490-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-021-08490-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-021-08490-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T10:12:18Z","timestamp":1653041538000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-021-08490-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,13]]},"references-count":35,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["8490"],"URL":"https:\/\/doi.org\/10.1007\/s00330-021-08490-9","relation":{},"ISSN":["1432-1084"],"issn-type":[{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,13]]},"assertion":[{"value":"3 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 November 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The scientific guarantor of this publication is Jie Lu.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all subjects (patients) in this study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"\u2022 retrospective\u2022 diagnostic or prognostic study\u2022 performed at one institution","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}