Antonio C. Westphalen

Purpose To determine the interobserver reproducibility of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 lexicon. Materials and Methods This retrospective HIPAA-compliant study was institutional review board-approved. Six radiologists from six separate institutions, all experienced in prostate magnetic resonance (MR) imaging, assessed prostate MR imaging examinations performed at a single center by using the PI-RADS lexicon. Readers were provided screen captures that denoted the location of one specific lesion per case. Analysis entailed two sessions (40 and 80 examinations per session) and an intersession training period for individualized feedback and group discussion. Percent agreement (fraction of pairwise reader combinations with concordant readings) was compared between sessions. κ coefficients were computed. Results No substantial difference in interobserver agreement was observed between sessions, and the sessions were subsequently pooled. Agreement for PI-RADS score of 4 or greater was 0.593 in peripheral zone (PZ) and 0.509 in transition zone (TZ). In PZ, reproducibility was moderate to substantial for features related to diffusion-weighted imaging (κ = 0.535-0.619); fair to moderate for features related to dynamic contrast material-enhanced (DCE) imaging (κ = 0.266-0.439); and fair for definite extraprostatic extension on T2-weighted images (κ = 0.289). In TZ, reproducibility for features related to lesion texture and margins on T2-weighted images ranged from 0.136 (moderately hypointense) to 0.529 (encapsulation). Among 63 lesions that underwent targeted biopsy, classification as PI-RADS score of 4 or greater by a majority of readers yielded tumor with a Gleason score of 3+4 or greater in 45.9% (17 of 37), without missing any tumor with a Gleason score of 3+4 or greater. Conclusion Experienced radiologists achieved moderate reproducibility for PI-RADS version 2, and neither required nor benefitted from a training session. Agreement tended to be better in PZ than TZ, although was weak for DCE in PZ. The findings may help guide future PI-RADS lexicon updates. (©) RSNA, 2016 Online supplemental material is available for this article.

Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2–5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%–44% and 27%–48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

PURPOSE: To retrospectively determine the effect of liver iron deposition on the evaluation of liver fat by using opposed-phase magnetic resonance (MR) imaging. MATERIALS AND METHODS: Committee on Human Research approval was obtained, and compliance with HIPAA regulations was observed. Patient consent was waived by the committee. Thirty-eight patients with cirrhosis (30 men, eight women; mean age, 58 years; range, 34-76 years) who underwent abdominal MR imaging and had contemporaneous liver biopsy were retrospectively identified. Two radiologists independently quantified liver fat according to the relative loss of signal intensity and compared this loss on opposed-phase and in-phase T1-weighted gradient-echo images. Liver fat percentage and presence of iron deposition were independently recorded by a pathologist. Generalized linear models, which included a mixed-random effects model, were used to determine the effect of iron deposition on the Spearman correlation coefficient for relative signal intensity loss versus histopathologically determined fat percentage. RESULTS: Liver iron deposition was found in 25 of 38 patients. Liver fat percentage (mean, 3%; range, 0%-25%) was identified histopathologically in 14 of 38 patients and in nine of 25 patients with iron deposition. For both readers, relative signal intensity loss at opposed-phase imaging was closely and significantly correlated (P < .05) with histopathologically determined liver fat percentage in patients without iron deposition (r = 0.7 for reader 1, r = 0.6 for reader 2), but no such correlation was found in patients with iron deposition (r = 0.1 for reader 1, r = -0.31 for reader 2; P > .05). CONCLUSION: Signal intensity loss on in-phase images caused by the presence of liver iron is a potential pitfall in the determination of liver fat percentage at opposed-phase MR imaging in chronic liver disease.