Diagnostic performance of multiparametric MRI in prostate cancer: per core analysis of two prospective ultrasound/MRI fusion biopsy datasets
==inizio abstract==
Introduction & Objectives: The fusion of multiparametric (Mp) magnetic resonance imaging (MRI) with real time ultrasound during prostate biopsy is gaining popularity among urologists. We evaluated the diagnostic performance of Mp-MRI using a per-core analysis of patients who underwent prostate “fusion” biopsy.
Material & Methods: Baseline, clinical and pathological data of 76 consecutive patients who underwent “fusion” prostate biopsy were prospectively collected in two centres between October 2013 and September 2014.
Diagnostic accuracy of Mp-MRI was evaluated in the whole cohort and in those patients with Gleason score >6, separately. Sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and accuracy (Ac) of Mp-MRI were assessed on the base of a per core analysis of histologic findings.
Results: The 2 series were not homogeneous for number of suspicious foci at Mp-MRI (p<0.001), number of cores taken (p<0.001) and number of targeted cores taken (p<0.001) (Table 1).
Out of 76 patients, 47 had a PCa diagnosis (61.8%); 28 of them (59.5%) were Gleason score 6. Overall, 1691 cores were taken: Se, Sp, PPV, NPV and Ac of Mp-MRI in the whole cohort were 41.7%, 86.5%, 33.1%, 85.4% and 72.9%, respectively.
When restricting the analysis to Gleason scores >6, Se, Sp, PPV, NPV and Ac were 33.5%, 82.2%, 16.2%, 92.3% and 77.7%, respectively.
The PPV of PI-RADS scores 3,4 and 5 were 28.5%, 65.8% and 90%, respectively, while the PPV of PI-RADS scores for Gleason score PCa >6 were 7.1%, 18.4% and 60%, respectively.
Conclusions: This study confirmed high PCa detection rates with Mp-MRI-ultrasound fusion biopsy. Nevertheless, a meticulous analysis of 1691 biopsy cores taken has highlighted a poor sensitivity and PPV of Mp-MRI, especially for Gleason score>6 PCa foci. PIRADS scores 5 correctly identified PCa lesions with Gleason scores>6.
==fine abstract==