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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
Published on: April 9, 2019
Multivariable stratification of PI-RADS version 2.1 categories for the risk of false-positive target biopsy: Impact
Rossano Girometti1, Gianluca Giannarini2, Maria De Martino3
1Institute of Radiology, Department of Medicine (DAME), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria ella Misericordia, 15, 33100 Udine, Italy.
Purpose:
To identify clinical and multiparametric magnetic resonance imaging (mpMRI) factors predicting false positive target biopsy (FP-TB) of prostate imaging reporting and data system version 2.1 (PI-RADSv2.1) ≥ 3 findings.
Method:
We retrospectively included 221 men with and without previous negative prostate biopsy who underwent 3.0 T/1.5 T mpMRI for suspicious clinically significant prostate cancer (csPCa) between April 2019-July 2021. A study coordinator revised mpMRI reports provided by one of two radiologists (experience of > 1500/>500 mpMRI examinations, respectively) and matched them with the results of transperineal systematic biopsy plus fusion target biopsy (TB) of PI-RADSv2.1 ≥ 3 lesions or PI-RADSv2.1 ≤ 2 men with higher clinical risk. A multivariable model was built to identify features predicting FP-TB of index lesions, defined as the absence of csPCa (International Society of Urogenital Pathology [ISUP] ≥ 2). The model was internally validated with the bootstrap technique, receiving operating characteristics (ROC) analysis, and decision analysis.
Results:
Features significantly associated with FP-TB were age < 65 years (odds ratio [OR] 2.77), prostate-specific antigen density (PSAD) < 0.15 ng/mL/mL (OR 2.45), PI-RADS 4/5 category vs. category 3 (OR 0.15/0.07), and multifocality (OR 0.46), with a 0.815 area under the curve (AUC) in assessing FP-TB. When adjusting PI-RADSv2.1 categorization for the model, mpMRI showed 87.5% sensitivity and 79.9% specificity for csPCa, with a greater net benefit in triggering biopsy compared to unadjusted categorization or adjustment for PSAD only at decision analysis, from threshold probability ≥ 15%.
Conclusion:
Adjusting PI-RADSv2.1 categories for a multivariable risk of FP-TB is potentially more effective in triggering TB of index lesions than unadjusted PI-RADS categorization or adjustment for PSAD alone.
Insights
Identifying factors for false positive prostate cancer biopsies is crucial. A multivariable model using age, PSA density, and MRI findings improves biopsy targeting accuracy.
Area of Science:
- Radiology
- Urology
- Oncology
Background:
- Multiparametric magnetic resonance imaging (mpMRI) is vital for detecting clinically significant prostate cancer (csPCa).
- Prostate Imaging Reporting and Data System version 2.1 (PI-RADSv2.1) categorizes lesions, guiding biopsy decisions.
- False positive target biopsies (FP-TB) can lead to unnecessary procedures and patient anxiety.
Purpose of the Study:
- To identify clinical and mpMRI factors that predict FP-TB in PI-RADSv2.1 ≥ 3 findings.
- To develop a model for improving the accuracy of prostate cancer diagnosis and reducing unnecessary biopsies.
Main Methods:
- Retrospective analysis of 221 men undergoing mpMRI and transperineal biopsy (systematic and targeted).
- Development and internal validation of a multivariable model to predict FP-TB, defined as absence of csPCa (ISUP ≥ 2).
- Analysis included age, prostate-specific antigen density (PSAD), PI-RADSv2.1 category, and lesion multifocality.
Main Results:
- Younger age (<65 years), lower PSAD (<0.15 ng/mL/mL), and PI-RADS 4/5 categories were associated with higher FP-TB risk.
- Multifocality was associated with a lower risk of FP-TB.
- The multivariable model achieved an area under the curve (AUC) of 0.815 for predicting FP-TB.
Conclusions:
- Adjusting PI-RADSv2.1 categories with a multivariable risk model is more effective for triggering target biopsies than unadjusted PI-RADS or PSAD adjustment alone.
- This approach can potentially improve the accuracy of csPCa detection and reduce false positive biopsies.
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