Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images | |
Sun, Kai4,5; Liu, Zhenyu5; Li, Yiming6; Wang, Lei6; Tang, Zhenchao2,5; Wang, Shuo2,5; Zhou, Xuezhi4,5; Shao, Lizhi3,5; Sun, Caixia1,5; Liu, Xing6 | |
刊名 | FRONTIERS IN ONCOLOGY |
2020-07-08 | |
卷号 | 10页码:8 |
关键词 | low-grade glioma epilepsy radiomics elastic net Cox regression |
ISSN号 | 2234-943X |
DOI | 10.3389/fonc.2020.01096 |
通讯作者 | Wang, Yinyan(tiantanyinyan@126.com) ; Tian, Jie(jie.tian@ia.ac.cn) |
英文摘要 | Purpose:The present study aimed to evaluate the performance of radiomics features in the preoperative prediction of epileptic seizure following surgery in patients with LGG. Methods:This retrospective study collected 130 patients with LGG. Radiomics features were extracted from the T2-weighted MR images obtained before surgery. Multivariable Cox-regression with two nested leave-one-out cross validation (LOOCV) loops was applied to predict the prognosis, and elastic net was used in each LOOCV loop to select the predictive features. Logistic models were then built with the selected features to predict epileptic seizures at two time points. Student'st-tests were then used to compare the logistic model predicted probabilities of developing epilepsy in the epilepsy and non-epilepsy groups. Thet-test was used to identify features that differentiated patients with early-onset epilepsy from their late-onset counterparts. Results:Seventeen features were selected with the two nested LOOCV loops. The index of concordance (C-index) of the Cox model was 0.683, and the logistic model predicted probabilities of seizure were significantly different between the epilepsy and non-epilepsy groups at each time point. Moreover, one feature was found to be significantly different between the patients with early- or late-onset epilepsy. Conclusion:A total of 17 radiomics features were correlated with postoperative epileptic seizures in patients with LGG and one feature was a significant predictor of the time of epilepsy onset. |
资助项目 | National Natural Science Foundation of China[81922040] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81772012] ; Beijing Natural Science Foundation[7182109] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFA0700401] ; National Key R&D Program of China[2016YFA0100902] ; Strategic Priority Research Programof Chinese Academy of Sciences[XDB32030200] ; Strategic Priority Research Programof Chinese Academy of Sciences[XDB01030200] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[SFH 2018-2-1072] ; Youth Innovation Promotion Association CAS[2019136] |
WOS关键词 | MULTIVARIATE PATTERN-ANALYSIS ; BRAIN-TUMORS ; SURVIVAL ; PROPHYLAXIS ; PREDICTION ; REGRESSION ; RISK |
WOS研究方向 | Oncology |
语种 | 英语 |
出版者 | FRONTIERS MEDIA SA |
WOS记录号 | WOS:000553869300001 |
资助机构 | National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key R&D Program of China ; Strategic Priority Research Programof Chinese Academy of Sciences ; Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/40295] |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
通讯作者 | Wang, Yinyan; Tian, Jie |
作者单位 | 1.Guizhou Univ, Sch Comp Sci & Technol, Key Lab Intelligent Med Image Anal & Precise Diag, Guiyang, Peoples R China 2.Beihang Univ, Sch Med, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China 3.Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China 4.Xidian Univ, Sch Life Sci & Technol, Minist Educ, Engn Res Ctr Mol & Neuro Imaging, Xian, Peoples R China 5.Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 6.Capital Med Univ, Beijing Tiantan Hosp, Beijing, Peoples R China 7.Univ Chinese Acad Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Sun, Kai,Liu, Zhenyu,Li, Yiming,et al. Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images[J]. FRONTIERS IN ONCOLOGY,2020,10:8. |
APA | Sun, Kai.,Liu, Zhenyu.,Li, Yiming.,Wang, Lei.,Tang, Zhenchao.,...&Tian, Jie.(2020).Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images.FRONTIERS IN ONCOLOGY,10,8. |
MLA | Sun, Kai,et al."Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images".FRONTIERS IN ONCOLOGY 10(2020):8. |
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