CASIA OpenIR  > 中国科学院分子影像重点实验室
Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study
Wang, Siwen1,2; Feng, Caizhen3; Dong, Di1,2; Li, Hailin1,2; Zhou, Jing4; Ye, Yingjiang4; Liu, Zaiyi5; Tian, Jie1,6; Wang, Yi3
Source PublicationMEDICAL PHYSICS
ISSN0094-2405
2020-06-26
Volume47Issue:10Pages:4862-4871
Abstract

Purpose: Preoperative and noninvasive prognosis evaluation remains challenging for gastric cancer. Novel preoperative prognostic biomarkers should be investigated. This study aimed to develop multidetector-row computed tomography (MDCT)-guided prognostic models to direct follow-up strategy and improve prognosis.

Methods: A retrospective dataset of 353 gastric cancer patients were enrolled from two centers and allocated to three cohorts: training cohort (n = 166), internal validation cohort (n = 83), and external validation cohort (n = 104). Quantitative radiomic features were extracted from MDCT images. The least absolute shrinkage and selection operator penalized Cox regression was adopted to construct a radiomic signature. A radiomic nomogram was established by integrating the radiomic signature and significant clinical risk factors. We also built a preoperative tumor-node-metastasis staging model for comparison. All models were evaluated considering the abilities of risk stratification, discrimination, calibration, and clinical use.

Results: In the two validation cohorts, the established four-feature radiomic signature showed robust risk stratification power (P = 0.0260 and 0.0003, log-rank test). The radiomic nomogram incorporated radiomic signature, extramural vessel invasion, clinical T stage, and clinical N stage, outperforming all the other models (concordance index = 0.720 and 0.727) with good calibration and decision benefits. Also, the 2-yr disease-free survival (DFS) prediction was most effective (time-dependent area under curve = 0.771 and 0.765). Moreover, subgroup analysis indicated that the radiomic signature was more sensitive in risk stratifying patients with advanced clinical T/N stage.

Conclusions: The proposed MDCT-guided radiomic signature was verified as a prognostic factor for gastric cancer. The radiomic nomogram was a noninvasive auxiliary model for preoperative individualized DFS prediction, holding potential in promoting treatment strategy and clinical prognosis.

Keyworddisease-free survival gastric cancer multidetector-row computed tomography risk stratification radiomics
DOI10.1002/mp.14350
WOS KeywordEXTRAMURAL VENOUS INVASION ; PROGNOSTIC VALUE ; CURATIVE RESECTION ; VASCULAR INVASION ; NOMOGRAM ; METASTASIS ; SIGNATURE ; MRI ; CARCINOMA ; DIAGNOSIS
Indexed BySCI
Language英语
WOS Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000555757600001
PublisherWILEY
Sub direction classification医学影像处理与分析
Citation statistics
Cited Times:23[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/40365
Collection中国科学院分子影像重点实验室
Corresponding AuthorLiu, Zaiyi; Tian, Jie; Wang, Yi
Affiliation1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Peking Univ, Dept Radiol, Peoples Hosp, Beijing 100044, Peoples R China
4.Peking Univ, Dept Gastrointestinal Surg, Peoples Hosp, Beijing 100044, Peoples R China
5.Guangdong Acad Med Sci, Guangdong Prov Peoples Hosp, Dept Radiol, Guangzhou 510080, Peoples R China
6.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Siwen,Feng, Caizhen,Dong, Di,et al. Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study[J]. MEDICAL PHYSICS,2020,47(10):4862-4871.
APA Wang, Siwen.,Feng, Caizhen.,Dong, Di.,Li, Hailin.,Zhou, Jing.,...&Wang, Yi.(2020).Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study.MEDICAL PHYSICS,47(10),4862-4871.
MLA Wang, Siwen,et al."Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study".MEDICAL PHYSICS 47.10(2020):4862-4871.
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