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A predictive model based on biparametric magnetic resonance imaging and clinical parameters for improved risk assessment and selection of biopsy-naïve men for prostate biopsies

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BackgroundProstate cancer risk prediction models and multiparametric magnetic resonance imaging (mpMRI) are used for individualised pre-biopsy risk assessment. However, biparametric MRI (bpMRI) has emerged as a simpler, more rapid MRI… Click to show full abstract

BackgroundProstate cancer risk prediction models and multiparametric magnetic resonance imaging (mpMRI) are used for individualised pre-biopsy risk assessment. However, biparametric MRI (bpMRI) has emerged as a simpler, more rapid MRI approach (fewer scan sequences, no intravenous contrast-media) to reduce costs and facilitate a more widespread clinical implementation. It is unknown how bpMRI and risk models perform conjointly. Therefore, the objective was to develop a predictive model for significant prostate cancer (sPCa) in biopsy-naive men based on bpMRI findings and clinical parameters.MethodsEight hundred and seventy-six biopsy-naive men with clinical suspicion of prostate cancer (prostate-specific antigen, <50 ng/mL; tumour stage,

Keywords: prostate; risk; biopsy; predictive model; clinical parameters

Journal Title: Prostate Cancer and Prostatic Diseases
Year Published: 2019

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