Bi-Parametric Prostate MR Helps Detect Clinically Significant Prostate Cancer
PSA-density does not appear to significantly improve its diagnostic performance.
Bi-parametric prostate MR (bp-MR) aids in detection of clinically significant prostate cancer (PCa), according to a study published in the European Journal of Radiology. Contrary to findings in the recent literature, PSA-D does not appear to significantly improve its diagnostic performance.
Researchers from Italy retrospectively analyzed 334 patients to evaluate the diagnostic performance of bp-MR, PSA-density (PSA-D) and their combination in biopsy-naïve patients.
All patients had undergone prostate MR on a 3T scanner. A total of 114 patients who underwent TRUS-biopsy within 30â¯days following MR with no previous prostate biopsies were included in the results. The researchers assessed three scenarios:
• Detection of lesions independently of ISUP score (ISUPâ¯≥â¯1)
• Detection of both intermediate and clinically significant lesions (ISUPâ¯≥â¯2)
• Detection of clinically significant lesions alone (ISUPâ¯≥â¯3).
The results showed that in all evaluated scenarios, bp-MR showed a significantly higher predictive power (AUCâ¯=â¯0.87 to 0.95) compared to the performance of PSA-D (AUCâ¯=â¯0.73 to 0.79), while their combination (AUCâ¯=â¯0.91 to 0.95) showed no statistically significant improvement compared to bp-MR alone.
The researchers concluded their results confirmed that bp-MR is a powerful tool in detection of clinically significant PCa. They also noted that contrary to findings in the recent literature, PSA-D does not appear to significantly improve its diagnostic performance.
Can CT-Based Deep Learning Bolster Prognostic Assessments of Ground-Glass Nodules?
June 19th 2025Emerging research shows that a multiple time-series deep learning model assessment of CT images provides 20 percent higher sensitivity than a delta radiomic model and 56 percent higher sensitivity than a clinical model for prognostic evaluation of ground-glass nodules.
Burnout in Radiology: Key Risk Factors and Promising Solutions
June 9th 2025Recognizing the daunting combination of increasing imaging volume and workforce shortages, these authors discuss key risk factors contributing to burnout and moral injury in radiology, and potential solutions to help preserve well-being among radiologists.
