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	Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer
	Wang, Xiao-Xiao7; Ding, Yi7; Wang, Si-Wen5,6; Dong, Di4,5,6; Li, Hai-Lin1,6; Chen, Jian2; Hu, Hui7; Lu, Chao7; Tian, Jie1,3,4,6; Shan, Xiu-Hong7
刊名	CANCER IMAGING
	2020-12-23
卷号	20期号:1页码:10
关键词	Lauren classification Radiomics Peritumoral analysis Gastric cancer Computed tomography
ISSN号	1740-5025
DOI	10.1186/s40644-020-00358-3
通讯作者	Tian, Jie(jie.tian@ia.ac.cn) ; Shan, Xiu-Hong(13913433095@163.com)
英文摘要	Background Preoperative prediction of the Lauren classification in gastric cancer (GC) is very important to the choice of therapy, the evaluation of prognosis, and the improvement of quality of life. However, there is not yet radiomics analysis concerning the prediction of Lauren classification straightly. In this study, a radiomic nomogram was developed to preoperatively differentiate Lauren diffuse type from intestinal type in GC. Methods A total of 539 GC patients were enrolled in this study and later randomly allocated to two cohorts at a 7:3 ratio for training and validation. Two sets of radiomic features were derived from tumor regions and peritumor regions on venous phase computed tomography (CT) images, respectively. With the least absolute shrinkage and selection operator logistic regression, a combined radiomic signature was constructed. Also, a tumor-based model and a peripheral ring-based model were built for comparison. Afterwards, a radiomic nomogram integrating the combined radiomic signature and clinical characteristics was developed. All the models were evaluated regarding classification ability and clinical usefulness. Results The combined radiomic signature achieved an area under receiver operating characteristic curve (AUC) of 0.715 (95% confidence interval [CI], 0.663-0.767) in the training cohort and 0.714 (95% CI, 0.636-0.792) in the validation cohort. The radiomic nomogram incorporating the combined radiomic signature, age, CT T stage, and CT N stage outperformed the other models with a training AUC of 0.745 (95% CI, 0.696-0.795) and a validation AUC of 0.758 (95% CI, 0.685-0.831). The significantly improved sensitivity of radiomic nomogram (0.765 and 0.793) indicated better identification of diffuse type GC patients. Further, calibration curves and decision curves demonstrated its great model fitness and clinical usefulness. Conclusions The radiomic nomogram involving the combined radiomic signature and clinical characteristics holds potential in differentiating Lauren diffuse type from intestinal type for reasonable clinical treatment strategy.
资助项目	National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFA0205200] ; National Natural Science Foundation of China[82022036] ; National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[6202790004] ; National Natural Science Foundation of China[81930053] ; Beijing Natural Science Foundation[L182061] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB 38040200] ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai)[HLHPTP201703] ; Youth Innovation Promotion Association CAS[2017175] ; Key Research Program of the Chinese Academy of Sciences[KGZD-EW-T03] ; Zhenjiang Innovation Capacity Building Program (technological infrastructure) -R&D project of China[SS2015023] ; Zhenjiang first people's Hospital Fund[Y2019016-S] ; Jiangsu Provincial Key Research and Development Special Fund[BE2015666] ; Jiangsu Innovative team leading talent fund[CXTDC2016006] ; Jiangsu six high peak talent fund[WSW-205] ; Jiangsu 333 talent fund[BRA2020016]
WOS关键词	CT ; CARCINOMA ; NOMOGRAM
WOS研究方向	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	BMC
WOS记录号	WOS:000595717300001
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Sciences ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai) ; Youth Innovation Promotion Association CAS ; Key Research Program of the Chinese Academy of Sciences ; Zhenjiang Innovation Capacity Building Program (technological infrastructure) -R&D project of China ; Zhenjiang first people's Hospital Fund ; Jiangsu Provincial Key Research and Development Special Fund ; Jiangsu Innovative team leading talent fund ; Jiangsu six high peak talent fund ; Jiangsu 333 talent fund
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/41681]
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	Tian, Jie; Shan, Xiu-Hong
作者单位	1.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing, Peoples R China 2.Jiangsu Univ, Dept Med Imaging, Med Coll, Zhenjiang, Jiangsu, Peoples R China 3.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Peoples R China 4.Jinan Univ, Zhuhai Peoples Hosp, Zhuhai Precis Med Ctr, Zhuhai, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging,State Key Lab Managem, Beijing, Peoples R China 7.Jiangsu Univ, Affiliated Peoples Hosp, Dept Radiol, Zhenjiang, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Wang, Xiao-Xiao,Ding, Yi,Wang, Si-Wen,et al. Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer[J]. CANCER IMAGING,2020,20(1):10.
APA	Wang, Xiao-Xiao.,Ding, Yi.,Wang, Si-Wen.,Dong, Di.,Li, Hai-Lin.,...&Shan, Xiu-Hong.(2020).Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer.CANCER IMAGING,20(1),10.
MLA	Wang, Xiao-Xiao,et al."Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer".CANCER IMAGING 20.1(2020):10.

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