Radiomics signature based on computed tomography images for the preoperative prediction of lymph node metastasis at individual stations in gastric cancer: A multicenter study

被引：19

作者：

Sun, Zepang ^{[1
,2
]}

Jiang, Yuming ^{[1
,2
]}

Chen, Chuanli ^{[3
]}

Zheng, Huan ^{[3
]}

Huang, Weicai ^{[1
,2
]}

Xu, Benjamin ^{[4
]}

Tang, Weijing ^{[5
]}

Yuan, Qingyu ^{[3
]}

Zhou, Kangneng ^{[6
]}

Liang, Xiaokun ^{[7
,8
]}

Chen, Hao ^{[1
,2
]}

Han, Zhen ^{[1
,2
]}

Feng, Hao ^{[1
,2
]}

Yu, Shitong ^{[1
,2
]}

Hu, Yanfeng ^{[1
,2
]}

Yu, Jiang ^{[1
,2
]}

Zhou, Zhiwei ^{[9
,10
]}

Wang, Wei ^{[9
,10
]}

Xu, Yikai ^{[3
]}

Li, Guoxin ^{[1
,2
]}

机构：

[1] Southern Med Univ, Nanfang Hosp, Sch Clin Med 1, Dept Gen Surg, Guangzhou 510515, Guangdong, Peoples R China

[2] Southern Med Univ, Nanfang Hosp, Sch Clin Med 1, Guangdong Prov Key Lab Precis Med Gastrointestina, Guangzhou 510515, Guangdong, Peoples R China

[3] Southern Med Univ, Nanfang Hosp, Dept Med Imaging Ctr, 1838 North Guangzhou Ave, Guangzhou 510515, Peoples R China

[4] Lynbrook High Sch, San Jose, CA USA

[5] Stanford Univ, Dept Pathol, Sch Med, Stanford, CA 94305 USA

[6] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing, Peoples R China

[7] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China

[8] Univ Chinese Acad Sci, Shenzhen Coll Adv Technol, Shenzhen, Peoples R China

[9] Sun Yat Sen Univ, Dept Gastr Surg, Canc Ctr, 651 Dongfeng Rd East, Guangzhou 510060, Peoples R China

[10] Collaborat Innovat Ctr Canc Med, State Key Lab Oncol South China, Guangzhou, Peoples R China

来源：

RADIOTHERAPY AND ONCOLOGY | 2021年 / 165卷

基金：

中国国家自然科学基金;

关键词：

Radiomics; Gastric cancer; Lymph node metastasis; Individual stations prediction; Computed tomography; MULTIDETECTOR-ROW CT; METAANALYSIS; DISSECTION; SELECTION;

D O I：

10.1016/j.radonc.2021.11.003

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Background: Specific diagnosis and treatment of gastric cancer (GC) require accurate preoperative predictions of lymph node metastasis (LNM) at individual stations, such as estimating the extent of lymph node dissection. This study aimed to develop a radiomics signature based on preoperative computed tomography (CT) images, for predicting the LNM status at each individual station. Methods: We enrolled 1506 GC patients retrospectively from two centers as training (531) and external (975) validation cohorts, and recruited 112 patients prospectively from a single center as prospective validation cohort. Radiomics features were extracted from preoperative CT images and integrated with clinical characteristics to construct nomograms for LNM prediction at individual lymph node stations. Performance of the nomograms was assessed through calibration, discrimination and clinical usefulness. Results: In training, external and prospective validation cohorts, radiomics signature was significantly associated with LNM status. Moreover, radiomics signature was an independent predictor of LNM status in the multivariable logistic regression analysis. The radiomics nomograms revealed good prediction performances, with AUCs of 0.716-0.871 in the training cohort, 0.678-0.768 in the external validation cohort and 0.700-0.841 in the prospective validation cohort for 12 nodal stations. The nomograms demonstrated a significant agreement between the actual probability and predictive probability in calibration curves. Decision curve analysis showed that nomograms had better net benefit than clinicopathologic characteristics. Conclusion: Radiomics nomograms for individual lymph node stations presented good prediction accuracy, which could provide important information for individual diagnosis and treatment of gastric cancer. (C) 2021 Elsevier B.V. All rights reserved.

引用

页码：179 / 190

页数：12

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