Application of image post-processing and data analysis of dual-energy CT in distinguishing gastric cancer from gastric stromal tumors

objective: The image processing and data analysis of dual-energy CT are widely used in the diagnosis of masses. This study explores the value of DECT in distinguishing gastric cancer from gastric stromal tumors. methods: 104 patients were categorized into two groups: gastric cancer (n=72) and gastric stromal tumor (n=32). The dual-energy CT parameters during dual phases were quantified using a post-processing workstation. Additionally, diagnostic performance was evaluated and contrasted. results: CT40keV_AP, CT70keV_AP, λHu_AP, Zeff_AP, CT40keV_VP, CT70 keV_VP, λHu_VP, NIC_VP, and Zeff_VP in the gastric cancer cohort were larger than those in the gastric stromal tumor cohort. The discrepancies were statistically significant (P<0.001). Diagnostic efficacy ranged from 0.776 to 0.869 for all statistically significant parameters. NIC_VP exhibited the best diagnostic efficacy (AUC= 0.869). The combined model revealed the highest efficacy through multiple logistic regression, with an AUC of 0.925. conclusion: Certain parameters of dual-energy CT are valuable in differentiating gastric cancer from gastric stromal tumors.