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Prebiopsy multiparametric MRI‐based risk score for predicting prostate cancer in biopsy‐naive men with prostate‐specific antigen between 4–10 ng/mL
Author(s) -
Dwivedi Durgesh Kumar,
Kumar Rajeev,
Dwivedi Alok Kumar,
Bora Girdhar S.,
Thulkar Sanjay,
Sharma Sanjay,
Gupta Siddhartha Datta,
Jagannathan Naranamangalam R.
Publication year - 2018
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25850
Subject(s) - medicine , receiver operating characteristic , prostate cancer , confidence interval , logistic regression , prostate biopsy , prostate specific antigen , odds ratio , biopsy , prostate , area under the curve , effective diffusion coefficient , magnetic resonance imaging , urology , radiology , cancer
Background Risk calculators have traditionally utilized serum prostate‐specific antigen (PSA) values in addition to clinical variables to predict the likelihood of prostate cancer (PCa). Purpose To 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 Type Prospective cross‐sectional study. Subjects In 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/Sequence 1.5T (Avanto, Siemens Health Care, Erlangen, Germany); T 1 ‐weighted, T 2 ‐weighted, DW‐MRI, and MRSI sequences were used. Assessment All eligible patients underwent mpMRI‐directed, cognitive‐fusion transrectal ultrasound (TRUS)‐guided biopsies. Statistical Tests An 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. Results Of 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 Conclusion A 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 Evidence : 1 Technical Efficacy : Stage 2 J. Magn. Reson. Imaging 2018;47:1227–1236.