Xing Y, Jiao Y, Gao YN. Radiomics for preoperative assessment of peritoneal metastasis in gastric cancer. World J Gastrointest Oncol 2026; 18(10): 118414 [DOI: 10.4251/wjgo.118414]
Corresponding Author of This Article
Yan Jiao, PhD, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, Xinmin Street, Changchun 130021, Jilin Province, China. jiaoyan@jlu.edu.cn
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
editorial
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Xing Y, Jiao Y, Gao YN. Radiomics for preoperative assessment of peritoneal metastasis in gastric cancer. World J Gastrointest Oncol 2026; 18(10): 118414 [DOI: 10.4251/wjgo.118414]
World J Gastrointest Oncol. Oct 15, 2026; 18(10): 118414 Published online Oct 15, 2026. doi: 10.4251/wjgo.118414
Radiomics for preoperative assessment of peritoneal metastasis in gastric cancer
Yue Xing, Yan Jiao, Yu-Ning Gao
Yue Xing, Anesthesia Recovery Room, The First Hospital of Jilin University, Changchun 130021, Jilin Province, China
Yan Jiao, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun 130021, Jilin Province, China
Yu-Ning Gao, Department of Gastrointestinal Surgery, Changchun Central Hospital, Changchun 130012, Jilin Province, China
Co-corresponding authors: Yan Jiao and Yu-Ning Gao.
Author contributions: Xing Y contributed to the literature search, data extraction, and initial drafting of the manuscript; Jiao Y and Gao YN conceived and designed the study, provided critical clinical and methodological input, and supervised the overall preparation of the manuscript, contributed to the interpretation of the radiomics and clinical evidence and critically revised the manuscript for important intellectual content as co-corresponding authors; all authors participated in the manuscript revision process, approved the final version, and agree to be accountable for all aspects of the work.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Corresponding author: Yan Jiao, PhD, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, Xinmin Street, Changchun 130021, Jilin Province, China. jiaoyan@jlu.edu.cn
Received: January 2, 2026 Revised: January 15, 2026 Accepted: February 12, 2026 Published online: October 15, 2026 Processing time: 258 Days and 15.6 Hours
Abstract
Peritoneal metastasis is a major determinant of prognosis and treatment strategy in gastric cancer, yet its accurate preoperative detection remains challenging with conventional imaging. Computed tomography often underestimates occult peritoneal disease, leading to delayed diagnosis or unnecessary exploratory procedures. Radiomics, enabling high-dimensional quantitative analysis of medical images, has emerged as a promising non-invasive approach for capturing tumor heterogeneity and improving metastatic risk assessment. Recent evidence, including the study by Mu et al, published in the World Journal of Gastrointestinal Oncology, highlights the value of multiphase contrast-enhanced computed tomography radiomics, where integration of arterial, venous, and delayed-phase features improves predictive performance, with reported area under the curves often exceeding 0.80. Despite these advances, significant challenges remain, including heterogeneity in imaging protocols, region-of-interest delineation, feature extraction pipelines, and the lack of prospective multicenter validation. Furthermore, the incremental value of radiomics over optimized clinical models and its impact on clinical decision-making require further clarification. This editorial critically appraises current advances and limitations of radiomics for peritoneal metastasis prediction, emphasizing methodological standardization and future directions toward clinically applicable, reproducible imaging biomarkers for gastric cancer staging.
Core Tip: Radiomics based on multiphase contrast-enhanced computed tomography offers a promising non-invasive approach for the preoperative assessment of peritoneal metastasis in gastric cancer. By quantitatively capturing tumor heterogeneity beyond visual interpretation, multiphase radiomics models – particularly when integrated with clinical variables – demonstrate improved predictive performance compared with conventional imaging alone. However, heterogeneity in imaging protocols, feature extraction strategies, and model validation remains a major barrier to clinical translation. Standardization and prospective validation are essential before routine clinical implementation.
