ReviewJournal of magnetic resonance imaging : JMRI2025
Toward a Refined PI-RADS: The Feasibility and Limitations of More Informative Metrics in Reviewing MRI Scans.
Review in Journal of magnetic resonance imaging : JMRI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Combined ADC and TMagnetic resonance in medicine · 2026Article
- 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Prostate Imaging-Reporting and Data System (PI-RADS) is a widely-adopted framework for assessing prostate cancer risk using multiparametric MRI. However, as advancements in imaging and data analytics emerge, PI-RADS faces pressure to integrate novel quantitative techniques, enhanced imaging protocols, and artificial intelligence (AI) solutions to improve diagnostic accuracy. This review examines the recent innovations in advanced imaging, clinical, and AI methods that can provide more informative MRI scans and discuss their potential incorporation into PI-RADS. Techniques like multi-shot echo-planar imaging and reduced field-of-view DWI show promise in improving scan quality, but may present challenges with respect to technical complexity, cost, and standardization. Others, like restriction spectrum imaging and luminal water imaging, offer new possibilities for lesion characterization, yet remain difficult to implement consistently across clinical settings. In addition, integrating clinical parameters and AI-driven tools within PI-RADS could enhance risk stratification, but may introduce greater complexity, potentially impacting ease-of-use. We discuss the implications of these advancements for PI-RADS, balancing the potential diagnostic benefits with the challenges of maintaining accessibility and reproducibility in clinical practice. This review provides a comprehensive overview of how emerging MRI techniques and AI may redefine prostate cancer imaging standards. Evidence Level: 5. Technical Efficacy: Stage 5.
Indexed as
Identifiers
What OpenQuestion holds
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.