• Durgesh Kumar Dwivedi, Rajeev Kumar, Alok Kumar Dwivedi, Girdhar S Bora, Sanjay Thulkar, Sanjay Sharma, Siddhartha Datta Gupta, and Naranamangalam R Jagannathan.
• Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi, India.
• J Magn Reson Imaging. 2018 May 1; 47 (5): 1227-1236.

BackgroundRisk calculators have traditionally utilized serum prostate-specific antigen (PSA) values in addition to clinical variables to predict the likelihood of prostate cancer (PCa).PurposeTo develop a prebiopsy multiparametric MRI (mpMRI)-based risk score (RS) and a statistical equation for predicting the risk of PCa in biopsy-naive men with serum PSA between 4-10 ng/mL that may help reduce unnecessary biopsies.Study TypeProspective cross-sectional study.SubjectsIn all, 137 consecutive men with PSA between 4-10 ng/mL underwent prebiopsy mpMRI (diffusion-weighted [DW]-MRI and MR spectroscopic imaging [MRSI]) during 2009-2015 were recruited for this study.Field Strength/Sequence1.5T (Avanto, Siemens Health Care, Erlangen, Germany); T1 -weighted, T2 -weighted, DW-MRI, and MRSI sequences were used.AssessmentAll eligible patients underwent mpMRI-directed, cognitive-fusion transrectal ultrasound (TRUS)-guided biopsies.Statistical TestsAn equation model and an RS were developed using receiver operating characteristic (ROC) curve analysis and a multivariable logistic regression approach. A 10-fold crossvalidation and simulation analyses were performed to assess diagnostic performance of various combinations of mpMRI parameters.ResultsOf 137 patients, 32 were diagnosed with PCa on biopsy. Multivariable analysis, adjusted with positive pathology, showed apparent diffusion coefficient (ADC), metabolite ratio, and PSA as significant predictors of PCa (P < 0.05). A statistical equation was derived using these predictors. A simple 6-point mpMRI-based RS was derived for calculating the risk of PCa and it showed that it is highly predictive for PCa (odds ratio = 3.74, 95% confidence interval [CI]: 2.24-6.27, area under the curve [AUC] = 0.87). Both models (equation and RS) yielded high predictive performance (AUC ≥0.85) on validation analysis.Data ConclusionA statistical equation and a simple 6-point mpMRI-based RS can be used as a point-of-care tool to potentially help limit the number of negative biopsies in men with PSA between 4 and 10 ng/mL.Level Of Evidence1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1227-1236.© 2017 International Society for Magnetic Resonance in Medicine.

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