Related Experiment Video
Updated: Jan 2, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Prostate MRI and quality: lessons learned from breast imaging rad-path correlation
Prasad R Shankar1,2, Matthew S Davenport3,4,5, Mark A Helvie3
1Department of Radiology, University of Michigan, 1500 E Medical Center Dr, B2 A209P, Ann Arbor, MI, 48109-5030, USA. pshankar@med.umich.edu.
Abstract:
Radiologic-pathologic correlation of Prostate Imaging Reporting & Data System (PI-RADS) scores ensures local quality and offers opportunities to improve future iterations of the reporting system. Tracking positive predictive values of lesion-targeted biopsies helps provide generalizable population-level risks associated with each PI-RADS category and can highlight the sources of variation. While this process of formalized pathologic correlation is somewhat new to abdominal radiology, we are fortunate to have a model to follow which was developed by our colleagues in breast imaging. If the success and multi-national adoption of BI-RADS is an indicator, building a scoring system anchored on a histologic reference is an important step to ensuring diagnostic quality and reliability.
Insights
Radiologic-pathologic correlation of Prostate Imaging Reporting & Data System (PI-RADS) scores improves prostate cancer diagnosis quality. Tracking biopsy outcomes linked to PI-RADS categories refines risk assessment and reporting system accuracy.
Area of Science:
- Radiology
- Pathology
- Oncology
Background:
- Prostate Imaging Reporting & Data System (PI-RADS) is crucial for standardizing prostate cancer imaging.
- Radiologic-pathologic correlation is essential for quality assurance and system refinement.
- Established models like Breast Imaging Reporting & Data System (BI-RADS) demonstrate the value of histologic correlation.
Purpose of the Study:
- To establish radiologic-pathologic correlation for PI-RADS scoring.
- To enhance the accuracy and reliability of prostate cancer diagnosis.
- To identify opportunities for improving future PI-RADS iterations.
Main Methods:
- Correlating PI-RADS scores with histopathologic findings from targeted biopsies.
- Tracking positive predictive values for each PI-RADS category.
- Analyzing sources of variation in diagnostic accuracy.
Main Results:
- Radiologic-pathologic correlation confirms local quality and identifies areas for PI-RADS improvement.
- Positive predictive values provide population-level risk stratification for PI-RADS categories.
- This process highlights variability and informs system refinement.
Conclusions:
- Formalized pathologic correlation is vital for ensuring diagnostic quality and reliability in prostate imaging.
- Adoption of PI-RADS with histologic anchoring, similar to BI-RADS, is key to multi-national standardization.
- Continuous quality improvement through correlation enhances patient care and diagnostic outcomes.
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