Evaluation of an AI-powered tool in improving lesion visualization on standard-dose contrast-enhanced brain MRI: a retrospective, multicenter study.

Published in AJNR. American journal of neuroradiology. Abstract: Artificial intelligence (AI) algorithms have been used to synthesize standard-dose images from low-dose images in brain MRI, but have less been evaluated to boost standard-dose contrast to approximate higher-dose effect. This study aims to evaluate the performance of a deep learning-based post-processing tool (AiMIFY) in enhancing contrast and improving lesion visualization on standard-dose contrast-enhanced brain MRI. In this retrospective, multicenter, multireader study, 86 adult patients who underwent standard-dose contrast-enhanced brain MRI were included. Pre-contrast and post-contrast three-dimensional T1-weighted images were processed using AiMIFY to generate contrast-boosting images. Three independent neuroradiologists performed blinded assessments. Quantitative metrics, including contrast-to-noise ratio (CNR), lesion-to-brain ratio (LBR), and contrast enhancement percentage (CEP), were measured. Subjective image quality (border delineation, internal morphology, and contrast enhancement) were evaluated using a Likert scale. The overall diagnostic preference was recorded. Comparisons between standard post-contrast and AiMIFY-processed images were performed using the Wilcoxon signed-rank test. AiMIFY-processed images demonstrated significantly higher CNR, LBR, and CEP compared with standard-dose post-contrast images across all readers (all P < 0.001), with mean increases of 495.16%, 58.94%, and 160.55%, respectively. Subjective assessments showed significant improvement...