Published online Jun 27, 2025. doi: 10.4240/wjgs.v17.i6.104545
Revised: February 23, 2025
Accepted: May 12, 2025
Published online: June 27, 2025
Processing time: 142 Days and 3.4 Hours
Gastric cancer (GC) remains a significant global health challenge, with high incidence and mortality rates. Neoadjuvant chemotherapy is increasingly used to improve surgical outcomes and long-term survival in advanced cases. However, individual responses to treatment vary widely, and current imaging methods often fall short in accurately predicting efficacy. Advanced imaging techniques, such as computed tomography (CT) 3D reconstruction and texture analysis, offer potential for more precise assessment of therapeutic response.
To explore the application value of CT 3D reconstruction volume change rate, texture feature analysis, and visual features in assessing the efficacy of neoad
A retrospective analysis was conducted on the clinical and imaging data of 97 patients with advanced GC who received S-1 plus Oxaliplatin combined chemo
The minimum misclassification rate of texture features in venous phase CT images (7.85%) was lower than in the arterial phase (13.92%). The volume change rate in the effective chemotherapy group (75.20%) was significantly higher than in the ineffective group (41.75%). There was a strong correlation between volume change rate and TRG grade (r = -0.886, P < 0.001). Multivariate analysis showed that gastric wall peristalsis (OR = 0.286) and thickness change rate ≥ 40% (OR = 0.265) were independent predictive factors. Receiver operating characteristic curve analysis indicated that the volume change rate [area under the curve (AUC) = 0.885] was superior to the CT visual feature model (AUC = 0.795). When the cutoff value was 82.56%, the sensitivity and specificity were 85.62% and 96.45%, respectively.
The CT 3D reconstruction volume change rate can serve as a preferred quantitative indicator for evaluating the efficacy of neoadjuvant chemotherapy in GC. Combining it with a CT visual feature predictive model can further improve the accuracy of efficacy evaluation.
Core Tip: This study highlights the value of computed tomography (CT) 3D reconstruction, texture analysis, and visual features in assessing neoadjuvant chemotherapy efficacy for gastric cancer (GC). The tumor volume change rate, derived from CT 3D reconstruction, showed a strong correlation with pathological tumor regression grade, outperforming CT visual features in predictive accuracy. Texture analysis, especially in the venous phase, demonstrated superior diagnostic capability. Combining these quantitative and qualitative imaging indicators provides a robust evaluation framework, aiding personalized treatment decisions. These findings emphasize the clinical utility of advanced imaging techniques for optimizing chemotherapy strategies and improving patient outcomes in GC management.