Update on PI-RADS Version 2.1 Diagnostic Performance Benchmarks for Prostate MRI: Systematic Review and Meta-Analysis.

Background Prostate MRI for the detection of clinically significant prostate cancer (csPCa) is standardized by the Prostate Imaging Reporting and Data System (PI-RADS), currently in version 2.1. A systematic review and meta-analysis infrastructure with a 12-month update cycle was established to evaluate the diagnostic performance of PI-RADS over time.

Comparison of data fusion strategies for automated prostate lesion detection using mpMRI correlated with whole mount histology.

Background: In this work, we compare input level, feature level and decision level data fusion techniques for automatic detection of clinically significant prostate lesions (csPCa).

Methods: Multiple deep learning CNN architectures were developed using the Unet as the baseline. The CNNs use both multiparametric MRI images (T2W, ADC, and High b-value) and quantitative clinical data (prostate specific antigen (PSA), PSA density (PSAD), prostate gland volume & gross tumor volume (GTV)), and only mp-MRI images (n = 118), as input.

Deep learning reconstructed T2-weighted Dixon imaging of the spine: Impact on acquisition time and image quality.

Purpose: To assess the image quality and impact on acquisition time of a novel deep learning based T2 Dixon sequence (T2) of the spine.

Methods: This prospective, single center study included n = 44 consecutive patients with a clinical indication for lumbar MRI at our university radiology department between September 2022 and March 2023. MRI examinations were performed on 1.