Evaluation of image quality between hybrid iterative reconstruction and deep learning reconstruction in low dose abdominopelvic CT in low body mass index individuals

significantly increased across the non-contrast [idose4: 0.09(- 0.4,0.6) vs PI: 0.4(- 0.3, 1), p < 0.001] and portal venous [idose4: 6 (4,7.17) vs PI: 6.47 (4.49, 7.62) p < 0.001] phases. Image noise was significantly lower with PI compared to iDose4 in the non- contrast (iDose4: 7.87 ± 0.97 vs PI: 7.59 ± 0.93, p value = 0.001), arterial (iDose4: 10.4 ± 1.42 vs PI: 9.83 ± 1.29, p < 0.001) and portal venous (idose4: 10.1 (9.6, 11.1) vs PI: 9.4 (8.9, 10.2), p < 0.001) phases. In qualitative analysis, Interobserver agreement between the two radiologists demonstrated good to excellent agreement (ICC range: 0.70-0.96). All the images were graded 3, 4 or 5, indicating good to excellent image quality with no artifacts. DLIR (Precise image-standard) offers a promising approach for improving image quality in low-dose abdominal and pelvic CT scans, particularly in individuals with a low BMI.