Exploring the impact of artificial intelligence on radiation dose reduction in urological imaging: a systematic review from EAU endourology

Background

Patients with urological conditions often undergo recurrent computed tomography (CT) imaging, which results in cumulative radiation exposure which can be deleterious. Artificial intelligence (AI)- based technologies, including Deep Learning Image Reconstruction (DLIR), have emerged as a potential strategy to reduce radiation dose in CT imaging while maintaining image quality. This systematic review aimed to quantify the benefits of AI-based techniques in urological CT imaging.