Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study

doi:10.1245/s10434-020-08659-4

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

	Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study
	Shao, Lizhi 1,2; Liu, Zhenyu 2,3; Feng, Lili 4; Lou, Xiaoying 5; Li, Zhenhui 6; Zhang, Xiao-Yan 7; Wan, Xiangbo 4; Zhou, Xuezhi 2,8; Sun, Kai 2,8; Zhang, Da-Fu 6
刊名	ANNALS OF SURGICAL ONCOLOGY
	2020-07-29
页码	11
ISSN号	1068-9265
DOI	10.1245/s10434-020-08659-4
通讯作者	Xu, Ruihua(xurh@sysucc.org.cn)
英文摘要	Background The aim of this work is to combine radiological and pathological information of tumor to develop a signature for pretreatment prediction of discrepancies of pathological response at several centers and restage patients with locally advanced rectal cancer (LARC) for individualized treatment planning. Patients and Methods A total of 981 consecutive patients with evaluation of response according to tumor regression grade (TRG) who received nCRT were retrospectively recruited from four hospitals (primary cohort and external validation cohort 1-3); both pretreatment multiparametric MRI (mp-MRI) and whole slide image (WSI) of biopsy specimens were available for each patient. Quantitative image features were extracted from mp-MRI and WSI and used to construct a radiopathomics signature (RPS) powered by an artificial-intelligence model. Models based on mp-MRI or WSI alone were also constructed for comparison. Results The RPS showed overall accuracy of 79.66-87.66% in validation cohorts. The areas under the curve of RPS at specific response grades were 0.98 (TRG0), 0.93 (<= TRG1), and 0.84 (<= TRG2). RPS at each grade of pathological response revealed significant improvement compared with both signatures constructed without combining multiscale tumor information (P < 0.01). Moreover, RPS showed relevance to distinct probabilities of overall survival and disease-free survival in patients with LARC who underwent nCRT (P < 0.05). Conclusions The results of this study suggest that radiopathomics, combining both radiological information of the whole tumor and pathological information of local lesions from biopsy, could potentially predict discrepancies of pathological response prior to nCRT for better treatment planning.
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 Program of Chinese Academy of Sciences[XDB32030200] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB01030200] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Youth Innovation Promotion Association CAS[2019136]
WOS关键词	RADIOMICS
WOS研究方向	Oncology ; Surgery
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000553745500002
资助机构	National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key R&D Program of China ; Strategic Priority Research Program of 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/173211/40280]
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	Xu, Ruihua
作者单位	1.Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China 2.Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Sun Yat Sen Univ, Dept Radiat Oncol, Affiliated Hosp 6, Guangzhou, Peoples R China 5.Sun Yat Sen Univ, Dept Pathol, Affiliated Hosp 6, Guangzhou, Guangdong, Peoples R China 6.Kunming Med Univ, Yunnan Canc Hosp, Yunnan Canc Ctr, Dept Radiol,Affiliated Hosp 3, Kunming, Yunnan, Peoples R China 7.Peking Univ, Dept Radiol, Key Lab Carcinogenesis & Translat Res, Minist Educ Beijing,Canc Hosp & Inst, Beijing, Peoples R China 8.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Shaanxi, Peoples R China 9.Kunming Med Univ, Yunnan Canc Hosp, Yunnan Canc Ctr, Dept Pathol,Affiliated Hosp 3, Kunming, Yunnan, Peoples R China 10.Southeast Univ, Key Lab Comp Network & Informat Integrat, Minist Educ, LIST, Nanjing, Peoples R China
推荐引用方式 GB/T 7714	Shao, Lizhi,Liu, Zhenyu,Feng, Lili,et al. Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study[J]. ANNALS OF SURGICAL ONCOLOGY,2020:11.
APA	Shao, Lizhi.,Liu, Zhenyu.,Feng, Lili.,Lou, Xiaoying.,Li, Zhenhui.,...&Tian, Jie.(2020).Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study.ANNALS OF SURGICAL ONCOLOGY,11.
MLA	Shao, Lizhi,et al."Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study".ANNALS OF SURGICAL ONCOLOGY (2020):11.