Abstract

BackgroundWe evaluated the ability of radiomics based on intratumoral and peritumoral regions on preoperative gastric cancer (GC) contrast-enhanced CT imaging to predict disease-free survival (DFS) and chemotherapy response in stage II/III GC.MethodsThis study enrolled of 739 consecutive stage II/III GC patients. Within the intratumoral and peritumoral regions of CT images, 584 total radiomic features were computed at the portal venous-phase. A radiomics signature (RS) was generated by using support vector machine (SVM) based methods. Univariate and multivariate Cox proportional hazards models and Kaplan-Meier analysis were used to determine the association of the RS and clinicopathological variables with DFS. A radiomics nomogram combining the radiomics signature and clinicopathological findings was constructed for individualized DFS estimation.ResultsThe radiomics signature consisted of 26 features and was significantly associated with DFS in both the training and validation sets (both P<0.0001). Multivariate analysis showed that the RS was an independent predictor of DFS. The signature had a higher predictive accuracy than TNM stage and single radiomics features and clinicopathological factors. Further analysis showed that stage II/III patients with high scores were more likely to benefit from adjuvant chemotherapy.ConclusionThe newly developed radiomics signature was a powerful predictor of DFS in GC, and it may predict which patients with stage II and III GC benefit from chemotherapy.

Highlights

  • We evaluated the ability of radiomics based on intratumoral and peritumoral regions on preoperative gastric cancer (GC) contrast-enhanced Computed tomography (CT) imaging to predict disease-free survival (DFS) and chemotherapy response in stage II/III Gastric cancer (GC)

  • There was a significant difference in DFS between patients with low and highRS scores (hazard ratio (HR) 0.190 (95% confidence interval (CI) 0.112–0.324); P

  • To confirm the association between the radiomics signature (RS) and prognosis, we tested it in the validation cohort and found similar results for DFS [HR 0.252; P

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Summary

Introduction

We evaluated the ability of radiomics based on intratumoral and peritumoral regions on preoperative gastric cancer (GC) contrast-enhanced CT imaging to predict disease-free survival (DFS) and chemotherapy response in stage II/III GC. Most patients in China are diagnosed at an advanced stage, and surgical resection is the main curative method for GC [2, 3]. For patients with advanced GC, prognosis remains dismal even after radical resection, with approximately 20% experiencing relapse within 1 year of the initial surgery [4, 5]. The survival rates for many stage II and III patients were still low though initial high response rates [4, 5]. It is highly necessary to develop a precise classification of GC that could be applied to better predict survivals and chemotherapy responses for GC patients

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