{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T19:25:03Z","timestamp":1793733903152,"version":"4.6.1"},"reference-count":41,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2019,11,11]],"date-time":"2019-11-11T00:00:00Z","timestamp":1573430400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81672484"],"award-info":[{"award-number":["81672484"]}],"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":["81871349"],"award-info":[{"award-number":["81871349"]}],"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":["61728107"],"award-info":[{"award-number":["61728107"]}],"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":["616712"],"award-info":[{"award-number":["616712"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2020,6]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>It is difficult to prospectively differentiate between benign (World Health Organization [WHO] I) and nonbenign (WHO II and III) meningiomas.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To evaluate the feasibility of preoperative differentiation between benign and nonbenign meningiomas by using texture analysis from multiparametric MR data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Subjects<\/jats:title><jats:p>In all, 184 patients with meningioma (139 benign and 45 nonbenign) were included as the training cohort and 79 patients with meningioma (60 benign and 19 nonbenign) were included as the external validation cohort.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>T<jats:sub>1<\/jats:sub>\u2010weighted, T<jats:sub>2<\/jats:sub>\u2010weighted, and contrast\u2010enhanced T<jats:sub>1<\/jats:sub>\u2010weighted imaging were performed on 1.5 or 3.0T MR systems from two centers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Tumor segmentation and radiological characteristic (RC) evaluation were performed by experienced radiologists. The texture features were extracted from preprocessed images and combined with RCs, and then the combined features were reduced by using a two\u2010step feature selection. Three single\u2010sequence models and a multiparametric MRI (the combination of single sequences) model were constructed and then evaluated with the external validation cohort.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Area under receiver operating characteristic curve (AUC), accuracy (Acc), f1\u2010score (F1), sensitivity (Sen), and specificity (Spec), were calculated to quantify the performance of the models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among the four texture models, the multiparametric MRI model demonstrated the best performance for differentiating between benign and nonbenign meningiomas in both the training and external validation cohorts (AUC 0.91, Acc 89%, F1 0.88, Sen 0.93, and Spec 0.87 in the training cohort; AUC 0.83, Acc 80%, F1 0.77, Sen 0.84, and Spec 0.78 in the validation cohort).<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>Nonbenign meningiomas might be preoperatively differentiated from benign meningiomas by using texture analysis from multiparametric MR data.<\/jats:p><jats:p><jats:bold>Level of Evidence:<\/jats:bold> 3<\/jats:p><jats:p><jats:bold>Technical Efficacy Stage:<\/jats:bold> 2<\/jats:p><jats:p>J. Magn. Reson. Imaging 2020;51:1810\u20131820.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.26976","type":"journal-article","created":{"date-parts":[[2019,11,11]],"date-time":"2019-11-11T13:45:07Z","timestamp":1573479907000},"page":"1810-1820","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI"],"prefix":"10.1002","volume":"51","author":[{"given":"Chao","family":"Ke","sequence":"first","affiliation":[{"name":"Department of Neurosurgery and neuro\u2010oncology, Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou 510060 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1791-6560","authenticated-orcid":false,"given":"Haolin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Southern Medical University  Guangzhou China"},{"name":"Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University  Guangzhou China"},{"name":"Key Laboratory of Mental Health of the Ministry of Education Southern Medical University  Guangzhou China"},{"name":"Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Center for Brain Science and Brain\u2010Inspired Intelligence  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1712-630X","authenticated-orcid":false,"given":"Xiaofei","family":"Lv","sequence":"additional","affiliation":[{"name":"Department of Radiology Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojiang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery and neuro\u2010oncology, Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou 510060 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maodong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Southern Medical University  Guangzhou China"},{"name":"Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University  Guangzhou China"},{"name":"Key Laboratory of Mental Health of the Ministry of Education Southern Medical University  Guangzhou China"},{"name":"Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Center for Brain Science and Brain\u2010Inspired Intelligence  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daokun","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Southern Medical University  Guangzhou China"},{"name":"Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University  Guangzhou China"},{"name":"Key Laboratory of Mental Health of the Ministry of Education Southern Medical University  Guangzhou China"},{"name":"Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Center for Brain Science and Brain\u2010Inspired Intelligence  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangying","family":"Ruan","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery and neuro\u2010oncology, Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou 510060 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Pathology, Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youming","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology Xiangya Hospital, Central South University  Changsha China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lizhi","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery and neuro\u2010oncology, Sun Yat\u2010sen University Cancer Center, State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine  Guangzhou 510060 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanqiu","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Southern Medical University  Guangzhou China"},{"name":"Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University  Guangzhou China"},{"name":"Key Laboratory of Mental Health of the Ministry of Education Southern Medical University  Guangzhou China"},{"name":"Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Center for Brain Science and Brain\u2010Inspired Intelligence  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,11,11]]},"reference":[{"key":"e_1_2_5_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/noy162"},{"key":"e_1_2_5_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.wneu.2018.08.019"},{"key":"e_1_2_5_4_1","doi-asserted-by":"publisher","DOI":"10.3171\/2017.12.FOCUS17756"},{"key":"e_1_2_5_5_1","doi-asserted-by":"publisher","DOI":"10.3171\/2014.7.JNS131644"},{"key":"e_1_2_5_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(16)30321-7"},{"key":"e_1_2_5_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/noy143"},{"key":"e_1_2_5_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/nox101"},{"key":"e_1_2_5_9_1","doi-asserted-by":"publisher","DOI":"10.3171\/2014.7.JNS132359"},{"key":"e_1_2_5_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocn.2017.11.013"},{"key":"e_1_2_5_11_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A1170"},{"key":"e_1_2_5_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tranon.2015.11.012"},{"key":"e_1_2_5_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00234-008-0373-y"},{"key":"e_1_2_5_14_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20180088"},{"key":"e_1_2_5_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.wneu.2015.10.049"},{"key":"e_1_2_5_16_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21552"},{"key":"e_1_2_5_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25835"},{"key":"e_1_2_5_18_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A2061"},{"key":"e_1_2_5_19_1","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/now256"},{"key":"e_1_2_5_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26265"},{"key":"e_1_2_5_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-018-5830-3"},{"key":"e_1_2_5_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-018-5632-7"},{"key":"e_1_2_5_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tranon.2017.04.006"},{"key":"e_1_2_5_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00401-007-0243-4"},{"key":"e_1_2_5_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2010.2046908"},{"key":"e_1_2_5_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2594(199912)42:6<1072::AID-MRM11>3.0.CO;2-M"},{"key":"e_1_2_5_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1982.1056489"},{"key":"e_1_2_5_28_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/60\/14\/5471"},{"key":"e_1_2_5_29_1","article-title":"Scikit\u2010learn: Machine learning in Python","volume":"12","author":"Pedregosa F","year":"2012","journal-title":"J Mach Learn Res"},{"key":"e_1_2_5_30_1","unstructured":"JonesE OliphantT PetersonP. SciPy: Open Source Scientific Tools for Python.2001."},{"key":"e_1_2_5_31_1","unstructured":"ZwanenburgA LegerS Valli\u00e8resM L\u00f6ckS. Image biomarker standardisation initiative 2016."},{"key":"e_1_2_5_32_1","doi-asserted-by":"publisher","DOI":"10.1215\/S1152851704000158"},{"key":"e_1_2_5_33_1","first-page":"1272","article-title":"Anatomic location is a risk factor for atypical and malignant meningiomas","volume":"117","author":"Kane AJ","year":"2011","journal-title":"Cancer Am Cancer Soc"},{"key":"e_1_2_5_34_1","doi-asserted-by":"publisher","DOI":"10.3171\/2017.9.JNS171609"},{"key":"e_1_2_5_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2017.10.005"},{"key":"e_1_2_5_36_1","doi-asserted-by":"publisher","DOI":"10.1097\/RCT.0000000000000873"},{"key":"e_1_2_5_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2003.09.001"},{"key":"e_1_2_5_38_1","doi-asserted-by":"publisher","DOI":"10.1055\/s-0034-1373657"},{"key":"e_1_2_5_39_1","doi-asserted-by":"publisher","DOI":"10.1080\/02688697.2017.1297765"},{"key":"e_1_2_5_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nec.2015.11.012"},{"key":"e_1_2_5_41_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00701-014-2306-3"},{"key":"e_1_2_5_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocn.2016.03.014"}],"container-title":["Journal of Magnetic Resonance Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fjmri.26976","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jmri.26976","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jmri.26976","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jmri.26976","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T08:16:16Z","timestamp":1693988176000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jmri.26976"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,11]]},"references-count":41,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["10.1002\/jmri.26976"],"URL":"https:\/\/doi.org\/10.1002\/jmri.26976","archive":["Portico"],"relation":{},"ISSN":["1053-1807","1522-2586"],"issn-type":[{"value":"1053-1807","type":"print"},{"value":"1522-2586","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,11]]},"assertion":[{"value":"2019-07-10","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-10-07","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-11-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}