Application of image post-processing and data analysis of dual-energy CT in distinguishing the differentiation degree of gastric cancer
Year: 2025
Type: conference-paper
Study design: Observational Study
Abstract: objective: Dual-energy CT is a device that diagnoses diseases by scanning and post-processing images to obtain corresponding parameters and images. The objective of this study is to investigate the use of dual-energy CT characteristics in evaluating gastric cancer differentiation degrees. methods: Sixty-five patients diagnosed with gastric cancer were included and categorized into a poorly differentiated group (n=43) and a moderately or highly differentiated group (n=22) based on pathological findings. Parameters for dual-energy CT were assessed for dual phases, encompassing CT values of 40KeV and 70KeV, iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), and the slope of the curve (λHu). In addition, ROC curves were employed to evaluate the diagnostic capability of DECT parameters. results: In both arterial and venous phases, the group with poor differentiation had greater levels of IC, NIC, and Zeff (all P<0.05). For all DECT parameters showing notable variations, Zeff_AP and Zeff_VP possessed the greatest diagnostic effectiveness (AUC=0.770). The integration of characteristics with notable differences revealed that the combined model presented the best diagnostic efficacy (AUC=0.853). conclusion: DECT quantitative parameters are valuable in identifying the degree of differentiation of gastric cancer and may afford more imaging information for patients with gastric cancer.
Authors: Siwen Liu, Jianhua Liu, Meng Wu, Jiale Tian, Longhai Jin, Tingting Gong
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410920319