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

Dominik Deniffel, Yucheng Zhang, Emmanuel Salinas, Raj Satkunasivam, Farzad Khalvati, Masoom A. Haider

Research output: Contribution to journalArticle

2 Scopus citations

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-RADS™ (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/ml2 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/ml2 resulted in 25% to 29% fewer multiparametric magnetic resonance imaging scans performed while missing only a minimal number of clinically significant prostate cancers. Further prospective validation is required.

Original languageEnglish (US)
Pages (from-to)292-298
Number of pages7
JournalThe Journal of urology
Volume203
Issue number2
DOIs
StatePublished - Feb 1 2020

Keywords

  • diagnostic imaging
  • magnetic resonance imaging
  • prostate-specific antigen
  • prostatic neoplasms
  • risk

ASJC Scopus subject areas

  • Urology

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