Reducing Unnecessary Prostate Multiparametric Magnetic Resonance Imaging by Using Clinical Parameters to Predict Negative and Indeterminate Findings

Abstract

Purpose: We sought to develop a triage strategy to reduce negative and indeterminate multiparametric magnetic resonance imaging scans in patients at risk for prostate cancer. Materials and Methods: In this retrospective study we evaluated 865 patients with no prior prostate cancer diagnosis who underwent prostate multiparametric magnetic resonance imaging between 2009 and 2017. Age, prostate volume, prostate specific antigen and prostate specific antigen density were assessed as predictors of positive multiparametric magnetic resonance imaging, defined as PI-RADSÔ (Prostate Imaging Reporting and Data System) version 2/Likert score 4 or greater. The cohort was split into a training cohort of 605 patients and a validation cohort of 260. The optimal threshold to rule out positive multiparametric magnetic resonance imaging was chosen to achieve a negative predictive value greater than 90%. Results: All clinical variables were significant predictors of positive multiparametric magnetic resonance imaging (p <0.05). Prostate specific antigen density outperformed other parameters in diagnostic accuracy and did not significantly differ compared to a multivariate model (AUC[0.74 vs 0.75). At prostate specific antigen density greater than 0.078 ng/ml 2 sensitivity, specificity, positive and negative predictive values were 94%, 29%, 22% and 95%, respectively, resulting in 25% fewer scans (64 of 260). In the multivariate model sensitivity, specificity, positive and negative predictive values were 85%, 32%, 22% and 91%, respectively, resulting in 29% fewer scans (75 of 260). Biopsies in men who would not have undergone multiparametric magnetic resonance imaging according to our proposed strategies revealed 2 clinically significant prostate cancers using prostate specific antigen density and 1 using the multivariate model. Conclusions: In patients at risk for prostate cancer applying a multivariate prediction model or a prostate specific antigen density cutoff of 0.078 ng/ml 2

Developing Strategy to Predict the Results of Prostate Multiparametric Magnetic Resonance Imaging and Reduce Unnecessary Multiparametric Magnetic Resonance Imaging Scan

“…In this study, our developed multivariate model including tPSA, fPSA, and PV has a similar diagnostic accuracy with the PSAD in the prediction of suspicious MRI-PCa ( P = 0.108). This was consistent with the study by Dominik Deniffel ( 13 ). Although cross-study comparisons are challenging, our multivariate model (AUC = 0.80) performed similarly with the model developed by Dominik Deniffel (AUC = 0.75) in the prediction of mpMRI results ( 13 ).…”

“…Studies demonstrated that a risk-based triage strategy could reduce more unnecessary biopsy and the overdiagnosis in comparison with single parameters (8,11,25). However, the study about developing a multivariate model to predict the results of prostate mpMRI and selecting patients who could benefit from mpMRI is limited (13,14). The study by Alberts et al introduced the concept of a patient triage strategy to avoid prostate mpMRI, and assessed the rate of potentially avoidable mpMRI by applying the risk calculators for detecting PCa (Rotterdam Prostate Cancer Risk Calculator, RPCRC) in a small cohort with one or more previously negative random TRUSguided biopsies (14).…”

“…Studies demonstrated that a risk-based triage strategy could reduce more unnecessary biopsy and the overdiagnosis in comparison with single parameters ( 8 , 11 , 25 ). However, the study about developing a multivariate model to predict the results of prostate mpMRI and selecting patients who could benefit from mpMRI is limited ( 13 , 14 ). The study by Alberts et al.…”

“…A dozen of risk calculators incorporating clinical variables and/or novel biomarkers have been developed to predict the results of prostate biopsy and to reduce unnecessary biopsy by 36%-66% (8)(9)(10)(11)(12). However, the knowledge about developing a strategy to predict the results of mpMRI and select patients who could benefit from mpMRI is limited (13,14).…”

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot‐assisted radical prostatectomy

“…We have seen a considerable recent effort to reduce the number of unnecessary prostate biopsies and more accurately diagnose clinically significant prostate cancers (csPCa). 1,2 Multiparametric magnetic resonance imaging (mpMRI) is a promising tool for detecting prostate cancer (PCa), 3 and clinicians are currently using mpMRI as a biopsy decision-making strategy. 4 Whether men with a negative mpMRI, defined as Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) scores of ≤ 2, should undergo prostate biopsy remains a matter of debate.…”