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Prediction of Peritoneal Metastasis for Gastric Cancer Based on Radiomics: a Multi-center Prospective Study
Peritoneal metastasis of gastric cancer is difficult to be detected in time, thus delaying treatment. Based on the conventional CT images of gastric cancer, this study plans to develop, improve and validate an intelligent analysis system based on radiomics. By extracting and combining the radiomics features related to peritoneal metastasis of gastric cancer, the intelligent analysis system could predict the risk of peritoneal metastasis, and provide personalized decision suggestions for the treatment of gastric cancer.
Peritoneal metastasis of gastric cancer is difficult to be detected in time, thus delaying treatment. Based on the conventional CT images of gastric cancer, this study plans to develop, improve and validate an intelligent analysis system based on radiomics. By extracting and combining the radiomics features related to peritoneal metastasis of gastric cancer, the intelligent analysis system could predict the risk of peritoneal metastasis, and provide personalized decision suggestions for the treatment of gastric cancer.
Age
18 - No limit years
Sex
ALL
Healthy Volunteers
No
Peking University Cancer Hospital & Institute
Beijing, China
Fujian Medical University Union Hospital
Fuzhou, China
Affiliated Cancer Hospital and Institute of Guangzhou Medical University
Guangzhou, China
Guangdong Provincial People's Hospital
Guangzhou, China
Nanfang Hospital of Southern Medical University
Guangzhou, China
Sun Yat-Sen University Cancer Hospital
Guangzhou, China
Guizhou Provincial People's Hospital
Guiyang, China
Yunnan Cancer Hospital
Kunming, China
Shanxi Province Cancer Hospital
Taiyuan, China
Henan Cancer Hospital
Zhengzhou, China
Start Date
January 1, 2023
Primary Completion Date
December 31, 2023
Completion Date
December 31, 2028
Last Updated
February 14, 2023
400
ESTIMATED participants
Peritoneal metastasis status ascertainment
DIAGNOSTIC_TEST
Lead Sponsor
Chinese Academy of Sciences
Collaborators
NCT04550494
NCT04704661
Data Source & Attribution
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