LAUSR

PURPOSE To evaluate the image quality of ultra-high-resolution CT (U-HRCT) in the comparison among four different reconstruction methods, focusing on the gastric wall structure, and to compare the conspicuity of a three-layered structure of the gastric wall between conventional HRCT (C-HRCT) and U-HRCT. METHOD Our retrospective study included 48 patients who underwent contrast-enhanced U-HRCT. Quantitative analyses were performed to compare image noise of U-HRCT between deep-learning reconstruction (DLR) and other three methods (filtered back projection: FBP, hybrid iterative reconstruction: Hybrid-IR, and Model-based iterative reconstruction: MBIR). The mean overall image quality scores were also compared between the DLR and other three methods. In addition, the mean conspicuity scores for the three-layered structure of the gastric wall at five regions were compared between C-HRCT and U-HRCT. RESULTS The mean noise of U-HRCT with DLR was significantly lower than that with the other three methods (P < 0.001). The mean overall image quality scores with DLR images were significantly higher than those with the other three methods (P < 0.001). Regarding the comparison between C-HRCT and U-HRCT, the mean conspicuity scores for the three-layered structure of the gastric wall on U-HRCT were significantly better than those on C-HRCT in the fornix (5 [5-5] vs. 3.5 [3-4], P < 0.001), body (4 [3.25-5] vs. 4 [3-4], P = 0.039), angle (5 [4-5] vs. 3 [2-4], P < 0.001), and antral posterior (4 [3.25-5] vs. 2 [2-4], P < 0.001), except for antral anterior (4 [3-5] vs. 3 [3-4], P = 0.230) CONCLUSION: U-HRCT using DLR improved the image noise and overall image quality of the gastric wall as well as the conspicuity of the three-layered structure, suggesting its utility for the evaluation of the anatomical details of the gastric wall structure.