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Updated: Sep 2, 2025
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Performance of multi-parametric magnetic resonance imaging through PIRADS scoring system in biopsy naïve patients
Amr Nowier1, Hesham Mazhar1, Rasha Salah2
1Department of Urology, Faculty of Medicine Ain-Shams University, Cairo, Egypt.
Background:
Use of multi-parametric magnetic resonance imaging (mp-MRI) and Prostate Imaging Reporting and Data System (PI-RADS) scoring system allowed more precise detection of prostate cancer (PCa). Our study aimed at evaluating the diagnostic performance of mp-MRI in detection of PCa.
Methods:
Eighty-six patients suspected to have prostate cancer were enrolled. All patients underwent mp-MRI followed by systematic and targeted trans-rectal ultrasound (TRUS) guided prostate biopsies. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of mp-MRI were evaluated.
Results:
Forty-six patients (53.5%) had prostate cancer on targeted and systematic TRUS biopsies. On mp-MRI, 96.6% of lesions with PI-RADS < 3 revealed to be benign by TRUS biopsy, 73.3% of lesions with PI-RADS 4 showed ISUP grades ≥1, whereas all PI-RADS 5 lesions showed high ISUP grades ≥ 3. For PI-RADS 3 lesions, 62.5% of them revealed to be benign and 37.5% showed ISUP grades ≥1 by TRUS biopsy. PI-RADS scores ˃3 had 69.57% sensitivity and 85% specificity for detection of PCa. On adding the equivocal PI-RADS 3 lesions, PI-RADS scores ≥3 had higher sensitivity (97.83%), but at the cost of lower specificity (32.5%).
Conclusion:
Mp-MRI using PI-RADS V2 scoring system categories ≤3 and >3 could help in detection of PCa. PI-RADS 3 lesions are equivocal. Including PI-RADS lesions ≥3 demonstrated higher sensitivity, but at the cost of lower specificity for mp-MRI in diagnosis for Pca.
Abbreviations:
CDR: cancer detection rates; DRE: digital rectal examination; ISUP: international society of urological pathology; mp-MRI: multi-parametric magnetic resonance imaging; NPV: negative predictive value; PCa: prosatate cancer; PI-RADS: Prostate Imaging Reporting and Data System; PPV: Positive predictive value; PSA: prostate specific antigen; TRUS: transrectal ultrasound.
Insights
Multi-parametric MRI (mp-MRI) with PI-RADS scoring aids prostate cancer detection. While PI-RADS scores ≥3 increase sensitivity, they decrease specificity, indicating PI-RADS 3 lesions are equivocal.
Area of Science:
- Radiology
- Oncology
- Urology
Background:
- Multi-parametric magnetic resonance imaging (mp-MRI) and the Prostate Imaging Reporting and Data System (PI-RADS) scoring system enhance prostate cancer (PCa) detection.
- Evaluating the diagnostic performance of mp-MRI is crucial for accurate PCa diagnosis.
Purpose of the Study:
- To assess the diagnostic performance of mp-MRI in detecting prostate cancer (PCa).
- To evaluate the utility of PI-RADS V2 scoring in PCa detection.
Main Methods:
- Eighty-six patients with suspected PCa underwent mp-MRI followed by systematic and targeted trans-rectal ultrasound (TRUS) guided biopsies.
- Key performance metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for mp-MRI.
Main Results:
- Prostate cancer was confirmed in 53.5% of patients via TRUS biopsy.
- mp-MRI demonstrated high accuracy: PI-RADS < 3 lesions were mostly benign (96.6%), PI-RADS 4 lesions showed significant cancer (73.3%), and PI-RADS 5 lesions indicated high-grade cancer (≥ ISUP grade 3).
- PI-RADS scores >3 showed 69.57% sensitivity and 85% specificity; including PI-RADS 3 lesions (equivocal) increased sensitivity to 97.83% but reduced specificity to 32.5%.
Conclusions:
- mp-MRI with PI-RADS V2 scoring aids PCa detection, with categories ≤3 and >3 being informative.
- PI-RADS 3 lesions are equivocal and require careful interpretation.
- Including PI-RADS 3 lesions in the positive category (≥3) significantly boosts sensitivity but compromises specificity in PCa diagnosis.
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