ArticleJournal of magnetic resonance imaging : JMRI2019
Intra- and interreader reproducibility of PI-RADSv2: A multireader study.
Article in Journal of magnetic resonance imaging : JMRI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
77 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Factors Influencing Variability in the Performance of Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer: A Systematic Literature Review.European urology oncology · 2020Pooled it
- AI-Assisted Prostate Cancer Diagnosis Using Biparametric MRI and PI-RADS v2.1: Performance Comparison Between Novice-Level and Experienced Readers.Journal of magnetic resonance imaging : JMRI · 2026Article
- Editorial for "AI-Assisted Prostate Cancer Diagnosis Using Biparametric MRI and PI-RADS v2.1: Performance Comparison Between Novice-Level and Experienced Readers".Journal of magnetic resonance imaging : JMRI · 2026Article
- Multicentre evaluation of artificial intelligence risk classification for detection of clinically significant prostate cancer on biparametric MRI.European radiology · 2026Article
- Detecting clinically significant prostate cancer with a distributed parameter model based on quantitative dynamic contrast-enhanced magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2026Article
- Deep learning classification of significant prostate cancer on MRI: a systematic review and meta-analysis.Abdominal radiology (New York) · 2026Review
- Artificial intelligence may enhance the role of magnetic resonance imaging in prostate cancer focal therapy.Prostate cancer and prostatic diseases · 2026Review
- 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
- Combined radiomics, PI-RADS, and clinical model improve significant prostate cancer prediction and guide biopsy decision.Insights into imaging · 2026Article
- Artificial Intelligence in Prostate MRI: Comparison of an AI-Based Software and an Experienced Radiologist for Detecting Clinically Significant Prostate Cancer.Current oncology (Toronto, Ont.) · 2026Article
- Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies.Journal of magnetic resonance imaging : JMRI · 2026Review
- External evaluation of an open-source deep learning model for prostate cancer detection on bi-parametric MRI.European radiology · 2026Article
- Prospective validation of an AI software for detecting clinically significant prostate cancer on biparametric MRI.Insights into imaging · 2026Article
- Adaptive ensemble learning for prostate cancer classification on multi-modal MRI: reducing unnecessary biopsies.BMC medical imaging · 2026Article
- Dual-region deep learning model integrating prostate and peri-prostatic adipose tissue MRI features for bone metastasis prediction in prostate cancer.Frontiers in oncology · 2026Article
- [Differentiation of osteoarthritis phenotypes on MRI using artificial intelligence].Orthopadie (Heidelberg, Germany) · 2026Review
- Clinical-imaging fusion model for risk assessment of clinically significant prostate cancer.Frontiers in oncology · 2026Article
- Automated MRI system for clinically significant prostate cancer detection development validation and real-world implementation.Nature communications · 2025Article
- Restriction Spectrum Imaging as a Quantitative Biomarker for Prostate Cancer With Reliable Positive Predictive Value.The Journal of urology · 2025Article
- Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men.JU open plus · 2025Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
backgroundThe Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) has been in use since 2015; while interreader reproducibility has been studied, there has been a paucity of studies investigating the intrareader reproducibility of PI-RADSv2. PURPOSE: To evaluate both intra- and interreader reproducibility of PI-RADSv2 in the assessment of intraprostatic lesions using multiparametric magnetic resonance imaging (mpMRI). STUDY TYPE: Retrospective. POPULATION/SUBJECTS: In all, 102 consecutive biopsy-naïve patients who underwent prostate MRI and subsequent MR/transrectal ultrasonography (MR/TRUS)-guided biopsy. FIELD STRENGTH/SEQUENCES: Prostate mpMRI at 3T using endorectal with phased array surface coils (TW MRI, DW MRI with ADC maps and b2000 DW MRI, DCE MRI). ASSESSMENT: Previously detected and biopsied lesions were scored by four readers from four different institutions using PI-RADSv2. Readers scored lesions during two readout rounds with a 4-week washout period. STATISTICAL TESTS: Kappa (κ) statistics and specific agreement (P
resultsOverall intrareader reproducibility was moderate to substantial (κ = 0.43-0.67, P DATA
conclusionPI-RADSv2 provides moderate intrareader reproducibility, poor interreader reproducibility, and moderate interreader lesion measurement reproducibility. These findings suggest a need for more standardized reader training in prostate MRI. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2.
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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.