ArticleJournal of magnetic resonance imaging : JMRI2017
Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study.
Article in Journal of magnetic resonance imaging : JMRI, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
93 citing papers in PubMed, 2 syntheses or guidelines pooled it, 210 citations in OpenAlex.
- Pooled it
- Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions.European urology · 2019Guideline
- Trial
- Quantitative assessment of prostate cancer using an individualized apparent diffusion coefficient intensity scale: a proposal.Quantitative imaging in medicine and surgery · 2026Article
- Radiomics: Current Applications and Future Directions.MedComm · 2026Review
- Multi-regional Multiparametric Deep Learning Radiomics for Diagnosis of Clinically Significant Prostate Cancer.Journal of imaging informatics in medicine · 2026Article
- Diagnostic performance of magnetic resonance imaging-targeted biopsy for PI-RADS ≥3 peripheral zone lesions in multiparametric prostate magnetic resonance imaging: correlation with clinically significant prostate cancer.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Article
- Evaluating the impact of reader experience on PI-RADS 3 of version 2.1 scoring concordance in multiparametric prostate MRI: a single-center analysis.Abdominal radiology (New York) · 2026Article
- Diagnostic accuracy of abbreviated biparametric MRI for prostate cancer screening: a prospective feasibility study (ReIMAGINE study).European radiology · 2026Article
- Reproducibility of MRI Radiomics Measurements in Men with Prostate Cancer Undergoing Active Surveillance.Cancers · 2026Article
- Construction and validation of a multimodal MRI-based deep learning model for early differential diagnosis of prostate cancer in the PSA gray zone: a retrospective cohort study.Frontiers in oncology · 2026Article
- Automated MRI system for clinically significant prostate cancer detection development validation and real-world implementation.Nature communications · 2025Article
- An online national quality assessment survey of prostate MRI reading: interreader variability in prostate volume measurement and PI-RADS classification.European journal of radiology open · 2025Article
- PI-RADS in Predicting csPCa: A Comparison Between Academic and Nonacademic Centers.The Prostate · 2025Article
- Added value of amide proton transfer-weighted magnetic resonance imaging to Prostate Imaging Reporting and Data System version 2.1 in differentiating clinically significant prostate cancer.Quantitative imaging in medicine and surgery · 2024Article
- External Validation of a Previously Developed Deep Learning-based Prostate Lesion Detection Algorithm on Paired External and In-House Biparametric MRI Scans.Radiology. Imaging cancer · 2024Article
- Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.Ultrasound in medicine & biology · 2024Article
- A novel model incorporating quantitative contrast-enhanced ultrasound into PI-RADSv2-based nomogram detecting clinically significant prostate cancer.Scientific reports · 2024Article
- Evaluating Diagnostic Accuracy and Inter-reader Agreement of the Prostate Imaging After Focal Ablation Scoring System.European urology open science · 2024Article
- Using an artificial intelligence model to detect and localize visible clinically significant prostate cancer in prostate magnetic resonance imaging: a multicenter external validation study.Quantitative imaging in medicine and surgery · 2024Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 6 institutions in 2 countries.
Funding
Abstract
purposeMultiparametric MRI (mpMRI) improves the detection of clinically significant prostate cancer, but is limited by interobserver variation. The second version of theProstate Imaging Reporting and Data System (PIRADSv2) was recently proposed as a standard for interpreting mpMRI. To assess the performance and interobserver agreement of PIRADSv2 we performed a multi-reader study with five radiologists of varying experience. MATERIALS AND
methodsFive radiologists (n = 2 prostate dedicated, n = 3 general body) blinded to clinicopathologic results detected and scored lesions on prostate mpMRI using PIRADSv2. The endorectal coil 3 Tesla MRI included T2W, diffusion-weighted imaging (apparent diffusion coefficient, b2000), and dynamic contrast enhancement. Thirty-four consecutive patients were included. Results were correlated with radical prostatectomy whole-mount histopathology produced with patient-specific three-dimensional molds. An index lesion was defined on pathology as the lesion with highest Gleason score or largest volume if equivalent grades. Average sensitivity and positive predictive values (PPVs) for all lesions and index lesions were determined using generalized estimating equations. Interobserver agreement was evaluated using index of specific agreement.
resultsAverage sensitivity was 91% for detecting index lesions and 63% for all lesions across all readers. PPV was 85% for PIRADS ≥ 3 and 90% for PIRADS ≥ 4. Specialists performed better only for PIRADS ≥ 4 with sensitivity 90% versus 79% (P = 0.01) for index lesions. Index of specific agreement among readers was 93% for the detection of index lesions, 74% for the detection of all lesions, and 85% for scoring index lesions, and 58% for scoring all lesions.
conclusionBy using PIRADSv2, general body radiologists and prostate specialists can detect high-grade index prostate cancer lesions with high sensitivity and agreement. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:579-585.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.