Academic radiology · 2025
CT Radiomics for Predicting Outcomes in HER2-Positive Surgically Resectable Advanced Gastric Cancer: A Preliminary Study.
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Zhao Huiping, Gao Jianbo, Li Jing, Qu Jinrong, Wang Rui, Li Liming, Cheng Ming, Liang Pan
Аннотация
RATIONALE AND OBJECTIVES: Accurate risk stratification in human epidermal growth factor receptor 2-positive surgically resectable advanced gastric cancer (HER2-p SRAGC) can strengthen monitoring for high-risk patients, allowing timely HER2-specific treatment and potentially improving prognosis. Therefore, we aimed to develop a CT radiomics model for predicting outcomes in HER2-p SRAGC and compare it with the 8th edition TNM staging system.
MATERIALS AND METHODS: 621 HER2-p SRAGC patients who received either radical gastrectomy or radical gastrectomy after neoadjuvant therapy or chemotherapy were retrospectively enrolled in two hospitals and assigned to a training (n=330), an internal validation (n=143) and an external validation (n=148) cohorts. A radiomics model incorporating Radscore and clinical scores was constructed. Model performance was assessed by Kaplan-Meier estimator, Log-rank test, and Harrell's C-index.
RESULTS: The radiomics model was correlated with the overall survival (OS) across all cohorts, with C-indexes of 0.711[95% confidence interval (CI): 0.666-0.756; p<0.001; training], 0.669 (95%CI: 0.585-0.753; p=0.009; internal validation) and 0.693 (95%CI: 0.597-0.789; p=0.015; external validation). In all study cohorts, the radiomics model successfully stratified patients into high-risk and low-risk groups, and outweighed individual scores, pathological staging (pTNM), and clinical staging (cTNM) but was inferior to post-neoadjuvant therapy staging (ypTNM). Additionally, the radiomics model had added value to the prognostic efficacy of pTNM and was unaffected by patient age and gender.
CONCLUSION: The radiomics model delivers individualized prognosis prediction of HER2-p SRAGC, surpassing clinical scores, and both pTNM and cTNM in forecasting OS. It confers incremental benefit to pTNM and exhibits certain universality across patient types.
TRIAL REGISTRATION: Retrospectively registered.
MATERIALS AND METHODS: 621 HER2-p SRAGC patients who received either radical gastrectomy or radical gastrectomy after neoadjuvant therapy or chemotherapy were retrospectively enrolled in two hospitals and assigned to a training (n=330), an internal validation (n=143) and an external validation (n=148) cohorts. A radiomics model incorporating Radscore and clinical scores was constructed. Model performance was assessed by Kaplan-Meier estimator, Log-rank test, and Harrell's C-index.
RESULTS: The radiomics model was correlated with the overall survival (OS) across all cohorts, with C-indexes of 0.711[95% confidence interval (CI): 0.666-0.756; p<0.001; training], 0.669 (95%CI: 0.585-0.753; p=0.009; internal validation) and 0.693 (95%CI: 0.597-0.789; p=0.015; external validation). In all study cohorts, the radiomics model successfully stratified patients into high-risk and low-risk groups, and outweighed individual scores, pathological staging (pTNM), and clinical staging (cTNM) but was inferior to post-neoadjuvant therapy staging (ypTNM). Additionally, the radiomics model had added value to the prognostic efficacy of pTNM and was unaffected by patient age and gender.
CONCLUSION: The radiomics model delivers individualized prognosis prediction of HER2-p SRAGC, surpassing clinical scores, and both pTNM and cTNM in forecasting OS. It confers incremental benefit to pTNM and exhibits certain universality across patient types.
TRIAL REGISTRATION: Retrospectively registered.