{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T13:14:20Z","timestamp":1780319660489,"version":"3.54.1"},"reference-count":27,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Clinical Neurology and Neurosurgery"],"published-print":{"date-parts":[[2020,11]]},"DOI":"10.1016\/j.clineuro.2020.106205","type":"journal-article","created":{"date-parts":[[2020,9,6]],"date-time":"2020-09-06T06:56:41Z","timestamp":1599375401000},"page":"106205","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":30,"special_numbering":"C","title":["Presurgical detection of brain invasion status in meningiomas based on first-order histogram based texture analysis of contrast enhanced imaging"],"prefix":"10.1016","volume":"198","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3976-4062","authenticated-orcid":false,"given":"Sedat Giray","family":"Kandemirli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saurav","family":"Chopra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarv","family":"Priya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caitlin","family":"Ward","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Locke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neetu","family":"Soni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanvesh","family":"Srivastava","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8819-8992","authenticated-orcid":false,"given":"Karra","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3170-242X","authenticated-orcid":false,"given":"Girish","family":"Bathla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.clineuro.2020.106205_bib0005","doi-asserted-by":"crossref","first-page":"v1","DOI":"10.1093\/neuonc\/nox158","article-title":"CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2010\u20132014","volume":"19","author":"Ostrom","year":"2017","journal-title":"Neuro Oncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0010","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1007\/s00401-016-1545-1","article-title":"The 2016 world health organization classification of tumors of the central nervous system: a summary","volume":"131","author":"Louis","year":"2016","journal-title":"Acta Neuropathol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0015","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.neuchi.2017.03.004","article-title":"Atypical meningioma. A study on recurrence and disease-specific survival","volume":"63","author":"Champeaux","year":"2017","journal-title":"Neurochirurgie"},{"key":"10.1016\/j.clineuro.2020.106205_bib0020","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3171\/2014.10.JNS14502","article-title":"Survival in patients treated for anaplastic meningioma","volume":"123","author":"Moliterno","year":"2015","journal-title":"J. Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0025","doi-asserted-by":"crossref","first-page":"e815","DOI":"10.1016\/j.crad.2019.07.020","article-title":"Can CT and MRI features differentiate benign from malignant meningiomas?","volume":"74","author":"Salah","year":"2019","journal-title":"Clin. Radiol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0030","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1016\/j.clinimag.2013.03.006","article-title":"Classification methods for the differentiation of atypical meningiomas using diffusion and perfusion techniques at 3-T MRI","volume":"37","author":"Svolos","year":"2013","journal-title":"Clin. Imaging"},{"key":"10.1016\/j.clineuro.2020.106205_bib0035","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s11060-012-0809-4","article-title":"Prediction of high-grade meningioma by preoperative MRI assessment","volume":"108","author":"Kawahara","year":"2012","journal-title":"J. Neurooncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0040","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.3171\/2014.7.JNS132359","article-title":"Correlation between magnetic resonance imaging grading and pathological grading in meningioma","volume":"121","author":"Lin","year":"2014","journal-title":"J. Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0045","doi-asserted-by":"crossref","first-page":"35974","DOI":"10.18632\/oncotarget.26313","article-title":"Prediction of brain invasion in patients with meningiomas using preoperative magnetic resonance imaging","volume":"9","author":"Adeli","year":"2018","journal-title":"Oncotarget"},{"key":"10.1016\/j.clineuro.2020.106205_bib0050","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.wneu.2019.05.017","article-title":"Prediction of high-grade histology and recurrence in meningiomas using routine preoperative magnetic resonance imaging: a systematic review","volume":"128","author":"Spille","year":"2019","journal-title":"World Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0055","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1016\/j.mri.2012.06.010","article-title":"Radiomics: the process and the challenges","volume":"30","author":"Kumar","year":"2012","journal-title":"Magn. Reson Imaging"},{"key":"10.1016\/j.clineuro.2020.106205_bib0060","doi-asserted-by":"crossref","first-page":"1338","DOI":"10.3389\/fonc.2019.01338","article-title":"The diagnostic value of radiomics-based machine learning in predicting the grade of meningiomas using conventional magnetic resonance imaging: a preliminary study","volume":"9","author":"Chen","year":"2019","journal-title":"Front. Oncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0065","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1007\/s00330-018-5632-7","article-title":"The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest","volume":"29","author":"Lu","year":"2019","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0070","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/j.tranon.2017.04.006","article-title":"The potential value of preoperative MRI texture and shape analysis in grading meningiomas: a preliminary investigation","volume":"10","author":"Yan","year":"2017","journal-title":"Transl. Oncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0075","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3171\/2018.7.GKS181327","article-title":"Pretreatment texture analysis of routine MR images and shape analysis of the diffusion tensor for prediction of volumetric response after radiosurgery for meningioma","volume":"129","author":"Speckter","year":"2018","journal-title":"J. Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0080","article-title":"Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival","volume":"1","author":"Morin","year":"2019","journal-title":"Neurooncol. Adv."},{"key":"10.1016\/j.clineuro.2020.106205_bib0085","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.neurad.2019.05.013","article-title":"Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis","volume":"46","author":"Li","year":"2019","journal-title":"J. Neuroradiol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0090","first-page":"1","article-title":"The effect of the revised WHO classification on the incidence of grade II meningioma","author":"Bulleid","year":"2019","journal-title":"Br. J. Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0095","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1007\/s00401-016-1598-1","article-title":"Brain invasion in otherwise benign meningiomas does not predict tumor recurrence","volume":"132","author":"Baumgarten","year":"2016","journal-title":"Acta Neuropathol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0100","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.1093\/neuonc\/nox071","article-title":"Brain invasion in meningiomas-clinical considerations and impact of neuropathological evaluation: a systematic review","volume":"19","author":"Brokinkel","year":"2017","journal-title":"Neuro Oncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0105","first-page":"453","article-title":"Atypical meningioma-is it time to standardize surgical sampling techniques?","volume":"19","author":"Jenkinson","year":"2017","journal-title":"Neuro Oncol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0110","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.wneu.2016.08.047","article-title":"Brain invasion in meningiomas: the rising importance of a uniform neuropathologic assessment after the release of the 2016 world health organization classification of central nervous system tumors","volume":"95","author":"Brokinkel","year":"2016","journal-title":"World neurosurgery"},{"key":"10.1016\/j.clineuro.2020.106205_bib0115","doi-asserted-by":"crossref","first-page":"e366","DOI":"10.1016\/j.wneu.2019.08.148","article-title":"Accuracy of radiomics-based feature analysis on multiparametric magnetic resonance images for noninvasive meningioma grading","volume":"132","author":"Laukamp","year":"2019","journal-title":"World Neurosurg."},{"key":"10.1016\/j.clineuro.2020.106205_bib0120","doi-asserted-by":"crossref","first-page":"4068","DOI":"10.1007\/s00330-018-5830-3","article-title":"Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging","volume":"29","author":"Park","year":"2019","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0125","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.ejrad.2019.04.022","article-title":"A deep learning radiomics model for preoperative grading in meningioma","volume":"116","author":"Zhu","year":"2019","journal-title":"Eur. J. Radiol."},{"key":"10.1016\/j.clineuro.2020.106205_bib0130","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.mri.2019.08.011","article-title":"Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: a multicenter radiomics study","volume":"63","author":"Hamerla","year":"2019","journal-title":"Magn Reson Imaging."},{"key":"10.1016\/j.clineuro.2020.106205_bib0135","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0187908","article-title":"Radiographic prediction of meningioma grade by semantic and radiomic features","volume":"12","author":"Coroller","year":"2017","journal-title":"PLoS One"}],"container-title":["Clinical Neurology and Neurosurgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0303846720305485?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0303846720305485?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T14:35:22Z","timestamp":1759588522000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0303846720305485"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11]]},"references-count":27,"alternative-id":["S0303846720305485"],"URL":"https:\/\/doi.org\/10.1016\/j.clineuro.2020.106205","relation":{},"ISSN":["0303-8467"],"issn-type":[{"value":"0303-8467","type":"print"}],"subject":[],"published":{"date-parts":[[2020,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Presurgical detection of brain invasion status in meningiomas based on first-order histogram based texture analysis of contrast enhanced imaging","name":"articletitle","label":"Article Title"},{"value":"Clinical Neurology and Neurosurgery","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.clineuro.2020.106205","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"106205"}}