Image quality, diagnostic performance of reduced-dose abdominal CT with artificial intelligence model-based iterative reconstruction for colorectal liver metastasis: a prospective cohort study

作者：Qiansai Qiu, Xiaoshan Chen, Wentao Wang, Jiahui Wang, Cheng Yan, Min Ji, San-Yuan Dong, Mengsu Zeng, Shengxiang Rao · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2025 · DOI：10.21037/qims-24-1570 · 被引用次数：8 · 研究领域：Radiation Dose and Imaging、Advanced X-ray and CT Imaging、Medical Imaging Techniques and Applications

Background: The optimization of regularization strategies in computed tomography (CT) iterative reconstruction may allow for a reduced dose (RD) without compromising image quality, thus the diagnostic ability of RD imaging must be considered, especially for low-contrast lesions. In this study, we evaluated the image quality and diagnostic performance of 50% RD CT for low-contrast colorectal liver metastasis (CRLM) with artificial intelligence model-based iterative reconstruction (AIIR) and standard-dose (SD) CT with hybrid iterative reconstruction (HIR). Methods: In this prospective study, consecutive participants with pathologically proven colorectal cancer and suspected liver metastases who underwent portal venous phase CT scans both at SD and RD between June and November 2022 were included. All images were reconstructed by HIR and AIIR. Two radiologists detected and characterized liver lesions with RD HIR, SD HIR, and RD AIIR and scored the image quality. The contrast-to-noise ratio (CNR) for metastases were recorded. The diagnostic performance for CRLM of each reconstruction algorithm was analyzed and compared using the receiver operating characteristic curve and the area under the curves (AUC). Results: A total of 56 participants with 422 liver lesions were recruited. The mean volume CT dose indices of the SD and RD scans were 9.5 and 4.8 mGy. RD AIIR exhibited superior subjective image quality and higher CNR for liver metastases than did RD/SD HIR. In all liver lesions ...