ArticleRadiology2022
Comparing Radiologist Performance in Diagnosing Clinically Significant Prostate Cancer with Multiparametric versus Hybrid Multidimensional MRI.
Article in Radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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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
16 citing papers in PubMed, 27 citations in OpenAlex.
- Prospective Validation of an Automated Hybrid Multidimensional MRI Tool for Prostate Cancer Detection Using Targeted Biopsy: Comparison with PI-RADS-based Assessment.Radiology. Imaging cancer · 2025Trial
- PI-RADS v2.1 for prostate MRI: current applications, ongoing debates, and synergies with advanced technologies-a narrative review.Translational andrology and urology · 2026Review
- Current state of the art of new prostate MRI technologies and potential future developments.BJR open · 2026Review
- Toward a Refined PI-RADS: The Feasibility and Limitations of More Informative Metrics in Reviewing MRI Scans.Journal of magnetic resonance imaging : JMRI · 2025Review
- Quantitative Prostate MRI, From theAJR. American journal of roentgenology · 2025Review
- Significance of multi-task deep learning neural networks for diagnosing clinically significant prostate cancer in plain abdominal CT.Frontiers in oncology · 2025Article
- Utility of quantitative measurement of TScientific reports · 2024Article
- Quantitative MRI biomarker for classification of clinically significant prostate cancer: Calibration for reproducibility across echo times.Journal of applied clinical medical physics · 2024Article
- Emerging and anticipated innovations in prostate cancer MRI and their impact on patient care.Abdominal radiology (New York) · 2024Review
- Interactive Cascaded Network for Prostate Cancer Segmentation from Multimodality MRI with Automated Quality Assessment.Bioengineering (Basel, Switzerland) · 2024Article
- MRI-based virtual pathology of the prostate.Magma (New York, N.Y.) · 2024Review
- Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Multiparametric MRI: From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics.Investigative radiology · 2023Review
- Genitourinary Imaging in 2040.Radiology · 2023Article
- Automated Patient-level Prostate Cancer Detection with Quantitative Diffusion Magnetic Resonance Imaging.European urology open science · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Background Variability of acquisition and interpretation of prostate multiparametric MRI (mpMRI) persists despite implementation of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 due to the range of reader experience and subjectivity of lesion characterization. A quantitative method, hybrid multidimensional MRI (HM-MRI), may introduce objectivity. Purpose To compare performance, interobserver agreement, and interpretation time of radiologists using mpMRI versus HM-MRI to diagnose clinically significant prostate cancer. Materials and Methods In this retrospective analysis, men with prostatectomy or MRI-fused transrectal US biopsy-confirmed prostate cancer underwent mpMRI (triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging) and HM-MRI (with multiple echo times and
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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.