When to biopsy Prostate Imaging and Data Reporting System version 2 (PI-RADSv2) assessment category 3 lesions? Use of clinical and imaging variables to predict cancer diagnosis at targeted biopsy.

INTRODUCTION

We aimed to determine if clinical and imaging features can stratify men at higher risk for clinically significant (CS, International Society of Urological Pathology [ISUP] grade group ≥2) prostate cancer (PCa) in equivocal Prostate Imaging and Data Reporting System (PI-RADS) category 3 lesions on magnetic resonance imaging (MRI).

METHODS

Approved by the institutional review board, this retrospective study involved 184 men with 198 lesions who underwent 3T-MRI and MRI-directed transrectal ultrasound biopsy for PI-RADS 3 lesions. Men were evaluated including clinical stage, prostate-specific antigen density (PSAD), indication, and MRI lesion size. Diagnoses for all men and by indication (no cancer, any PCa, CSPCa) were compared using multivariate logistic regression, including stage, PSAD, and lesion size.

RESULTS

We found an overall PCa rate of 31.8% (63/198) and 10.1% (20/198) CSPCa (13 grade group 2, five group 3, and two group 4). Higher stage (p=0.001), PSAD (p=0.007), and lesion size (p=0.015) were associated with CSPCa, with no association between CSPCa and age, PSA, or prostate volume (p>0.05). PSAD modestly predicted CSPCa area under the curve (AUC) 0.66 (95% confidence interval [CI] 0.518-0.794) in all men and 0.64 (0.487-0.799) for those on active surveillance (AS). Model combining clinical stage, PSAD, and lesion size improved accuracy for all men and AS (AUC 0.82 [0.736-0.910], p<0.001 and 0.785 [0.666-0.904], p<0.001). In men with prior negative biopsy and persistent suspicion, PSAD (0.90 [0.767-1.000]) was not different from the model (p>0.05), with optimal cutpoint of ≥0.215 ng/mL/cc achieving sensitivity/specificity of 85.7/84.4%.

CONCLUSIONS

PI-RADSv2 category 3 lesions are often not CSPCa. PSAD predicted CSPCa in men with a prior negative biopsy; however, PSAD alone had limited value, and accuracy improved when using a model incorporating PSAD with clinical stage and MRI lesion size.