Fast T2‐Weighted Imaging With Deep Learning‐Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy

Background Deep learning‐based reconstruction (DLR) can potentially improve image quality by reduction of noise, thereby enabling fast acquisition of magnetic resonance imaging (MRI). However, a systematic evaluation of image quality and diagnostic performance of MRI using short acquisition time with DLR has rarely been investigated in men with prostate cancer. Purpose To assess the image quality and diagnostic performance of MRI using short acquisition time with DLR for the evaluation of extraprostatic extension (EPE). Study Type Retrospective. Population One hundred and nine men. Field Strength/Sequence 3 T; turbo spin echo T2‐weighted images (T2WI), echo‐planar diffusion‐weighted, and spoiled gradient echo dynamic contrast‐enhanced images. Assessment To compare image quality, signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio (CNR) and subjective analysis using Likert scales on three T2WIs (MRI using conventional acquisition time, MRI using short acquisition time [fast MRI], and fast MRI with DLR) were performed. The diagnostic performance for EPE was evaluated by three independent readers. Statistical Tests SNR, CNR, and image quality scores across the three imaging protocols were compared using Friedman tests. The diagnostic performance for EPE was assessed using the area under receiver operating characteristic curves (AUCs). P