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Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

文献类型：期刊论文

作者Tian, Xin2; Sun, Caixia1,5; Liu, Zhenyu4,5; Li, Weili2; Duan, Hui2; Wang, Lu2; Fan, Huijian2; Li, Mingwei2; Li, Pengfei2; Wang, Lihui1
刊名FRONTIERS IN ONCOLOGY
出版日期2020-02-04
卷号10页码:10
ISSN号2234-943X
关键词locally advanced cervical cancer (LACC) radiomics neoadjuvant chemotherapy response prediction CT
DOI10.3389/fonc.2020.00077
通讯作者Wang, Lihui(wlh1984@gmail.com) ; Liu, Ping(lpivy@126.com) ; Tian, Jie(jie.tian@ia.ac.cn) ; Chen, Chunlin(ccl1@smu.edu.cn)
英文摘要Objective: To investigate whether pre-treatment CT-derived radiomic features could be applied for prediction of clinical response to neoadjuvant chemotherapy (NACT) in locally advanced cervical cancer (LACC). Patients and Methods: Two hundred and seventy-seven LACC patients treated with NACT followed by surgery/radiotherapy were included in this multi-institution retrospective study. One thousand and ninety-four radiomic features were extracted from venous contrast enhanced and non-enhanced CT imaging for each patient. Five combined methods of feature selection were used to reduce dimension of features. Radiomics signature was constructed by Random Forest (RF) method in a primary cohort of 221 patients. A combined model incorporating radiomics signature with clinical factors was developed using multivariable logistic regression. Prediction performance was then tested in a validation cohort of 56 patients. Results: Radiomics signature containing pre- and post-contrast imaging features can adequately distinguish chemotherapeutic responders from non-responders in both primary and validation cohorts [AUCs: 0.773 (95% CI, 0.701-0.845) and 0.816 (95% CI, 0.690-0.942), respectively] and remain relatively stable across centers. The combined model has a better predictive performance with an AUC of 0.803 (95% CI, 0.734-0.872) in the primary set and an AUC of 0.821 (95% CI, 0.697-0.946) in the validation set, compared to radiomics signature alone. Both models showed good discrimination, calibration. Conclusion: Newly developed radiomic model provided an easy-to-use predictor of chemotherapeutic response with improved predictive ability, which might facilitate optimal treatment strategies tailored for individual LACC patients.
WOS关键词MAGNETIC-RESONANCE ; PATHOLOGICAL RESPONSE ; RADICAL HYSTERECTOMY ; CARCINOMA ; SURGERY
资助项目National Natural Science Foundation of China[81772012] ; Beijing Natural Science Foundation[7182109] ; National Key Research and Development Plan of China[2017YFA0205200] ; National Key Research and Development Plan of China[2016YFA0100900] ; National Key Research and Development Plan of China[2016YFA0100902] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC00] ; National Science and Technology Pillar Program during the Twelfth Five-year Plan Period[2014BAI05B03] ; Major Program of Natural Science Foundation of Guangdong Province[2015A030311024] ; Medical Scientific Research Foundation of Guangdong Province[A2015063]
WOS研究方向Oncology
语种英语
出版者FRONTIERS MEDIA SA
WOS记录号WOS:000515550400001
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Research and Development Plan of China ; Chinese Academy of Sciences ; National Science and Technology Pillar Program during the Twelfth Five-year Plan Period ; Major Program of Natural Science Foundation of Guangdong Province ; Medical Scientific Research Foundation of Guangdong Province
源URL[http://ir.ia.ac.cn/handle/173211/38512]  
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, Lihui; Liu, Ping; Tian, Jie; Chen, Chunlin
作者单位1.Guizhou Univ, Sch Comp Sci & Technol, Key Lab Intelligent Med Image Anal & Precise Diag, Guiyang, Peoples R China
2.Southern Med Univ, Nanfang Hosp, Dept Gynaecol & Obstet, Guangzhou, Peoples R China
3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
5.Chinese Acad Sci, CAS Key Lab Mol Imaging, Inst Automat, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Tian, Xin,Sun, Caixia,Liu, Zhenyu,et al. Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis[J]. FRONTIERS IN ONCOLOGY,2020,10:10.
APA Tian, Xin.,Sun, Caixia.,Liu, Zhenyu.,Li, Weili.,Duan, Hui.,...&Chen, Chunlin.(2020).Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis.FRONTIERS IN ONCOLOGY,10,10.
MLA Tian, Xin,et al."Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis".FRONTIERS IN ONCOLOGY 10(2020):10.

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