Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer

doi:10.3389/fonc.2020.00604

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer
	Zhou, Xuezhi 2,9; Yi, Yongju 1,8; Liu, Zhenyu 6,9; Zhou, Zhiyang 7; Lai, Bingjia 3; Sun, Kai 2; Li, Longfei 4; Huang, Liyu 2; Feng, Yanqiu 8; Cao, Wuteng 7
刊名	FRONTIERS IN ONCOLOGY
	2020-05-11
卷号	10 页码:13
关键词	lymph node metastasis prediction neoadjuvant therapy locally advanced rectal cancer radiomics
ISSN号	2234-943X
DOI	10.3389/fonc.2020.00604
通讯作者	Feng, Yanqiu(foree@163.com) ; Cao, Wuteng(caowteng@163.com) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要	Background and Purpose: Lymph node status is a key factor for the recommendation of organ preservation for patients with locally advanced rectal cancer (LARC) following neoadjuvant therapy but generally confirmed post-operation. This study aimed to preoperatively predict the lymph node status following neoadjuvant therapy using multiparametric magnetic resonance imaging (MRI)-based radiomic signature. Materials and Methods: A total of 391 patients with LARC who underwent neoadjuvant therapy and TME were included, of which 261 and 130 patients were allocated to the primary cohort and the validation cohort, respectively. The tumor area, as determined by preoperative MRI, underwent radiomics analysis to build a radiomic signature related to lymph node status. Two radiologists reassessed the lymph node status on MRI. The radiomic signature and restaging results were included in a multivariate analysis to build a combined model for predicting the lymph node status. Stratified analyses were performed to test the predictive ability of the combined model in patients with post-therapeutic MRI T1-2 or T3-4 tumors, respectively. Results: The combined model was built in the primary cohort, and predicted lymph node metastasis (LNM+) with an area under the curve of 0.818 and a negative predictive value (NPV) of 93.7% were considered in the validation cohort. Stratified analyses indicated that the combined model could predict LNM+ with a NPV of 100 and 87.8% in the post-therapeutic MRI T1-2 and T3-4 subgroups, respectively. Conclusion: This study reveals the potential of radiomics as a predictor of lymph node status for patients with LARC following neoadjuvant therapy, especially for those with post-therapeutic MRI T1-2 tumors.
资助项目	National Natural Science Foundation of China[81922040] ; National Natural Science Foundation of China[81772012] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[7182109] ; National Key Research and Development Plan of China[2016YFA0100900] ; National Key Research and Development Plan of China[2016YFA0100902] ; National Key Research and Development Plan of China[2017YFA0205200] ; Youth Innovation Promotion Association CAS[2019136] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[YJKYYQ20180048] ; CAS[XDBS01030200] ; Key Research Projects in Frontier Science of CAS[QYZDJ-SSW-JSC005]
WOS关键词	TOTAL MESORECTAL EXCISION ; RADIATION-THERAPY ; COMPLETE RESPONSE ; CHEMORADIOTHERAPY ; CHEMORADIATION ; CHEMOTHERAPY ; RADIOTHERAPY ; MULTICENTER ; FLUOROURACIL ; RESECTION
WOS研究方向	Oncology
语种	英语
出版者	FRONTIERS MEDIA SA
WOS记录号	WOS:000537209300001
资助机构	National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Research and Development Plan of China ; Youth Innovation Promotion Association CAS ; Chinese Academy of Sciences ; CAS ; Key Research Projects in Frontier Science of CAS
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/39514]
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	Feng, Yanqiu; Cao, Wuteng; Tian, Jie
作者单位	1.Sun Yat Sen Univ, Affiliated Hosp 6, Network Informat Ctr, Guangzhou, Peoples R China 2.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Peoples R China 3.Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Radiol, Guangzhou, Peoples R China 4.Zhengzhou Univ, Collaborat Innovat Ctr Internet Healthcare, Zhengzhou, Peoples R China 5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Beijing, Peoples R China 7.Sun Yat Sen Univ, Affiliated Hosp 6, Dept Radiol, Guangzhou, Peoples R China 8.Southern Med Univ, Sch Biomed Engn, Guangdong Prov Key Lab Med Image Proc, Guangzhou, Peoples R China 9.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Xuezhi,Yi, Yongju,Liu, Zhenyu,et al. Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer[J]. FRONTIERS IN ONCOLOGY,2020,10:13.
APA	Zhou, Xuezhi.,Yi, Yongju.,Liu, Zhenyu.,Zhou, Zhiyang.,Lai, Bingjia.,...&Tian, Jie.(2020).Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer.FRONTIERS IN ONCOLOGY,10,13.
MLA	Zhou, Xuezhi,et al."Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer".FRONTIERS IN ONCOLOGY 10(2020):13.