Evidence map›Paper›PMID 42293821›Full record

ReviewTranslational andrology and urology2026

PI-RADS v2.1 for prostate MRI: current applications, ongoing debates, and synergies with advanced technologies-a narrative review.

Siying Zhang, Xiaoli Wang, Mingyang Guo, Feng Chen

Abstract readReview
In one paragraph

Review in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Siying ZhangDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID https://orcid.org/0000-0003-4538-5904
Xiaoli WangDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Mingyang GuoDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Feng ChenDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID https://orcid.org/0000-0003-4402-4955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 is the current standard for prostate multiparametric magnetic resonance imaging (mpMRI) reporting, aimed at improving diagnostic consistency for clinically significant prostate cancer (csPCa). This review aims to summarize the current applications of PI-RADS v2.1, analyze its diagnostic performance and limitations, and explore emerging synergies with biomarkers, biparametric MRI (bpMRI), artificial intelligence (AI), and advanced quantitative MRI techniques. Methods: A comprehensive literature search was conducted in PubMed and Web of Science databases up to December 2025, covering English-language articles on PI-RADS v2.1, prostate MRI, and related diagnostic innovations. Both original research and systematic reviews were considered to provide a balanced overview. Key Content and Findings: Compared with version 2.0, PI-RADS v2.1 refines technical specifications and interpretive criteria, but persistent challenges remain, including inter-reader variability and ambiguous guidance on patient preparation. Integration with prostate-specific antigen (PSA) density helps optimize risk stratification for PI-RADS 3 lesions. The bpMRI pathway offers a contrast-free, time-efficient alternative with comparable diagnostic accuracy. AI, particularly deep learning and radiomics, augments lesion detection, classification, and workflow efficiency, narrowing the experience gap among radiologists. Emerging techniques such as amide proton transfer-weighted imaging, restriction spectrum imaging, and magnetic resonance elastography provide complementary quantitative data that may further improve csPCa detection when combined with PI-RADS v2.1. Conclusions: PI-RADS v2.1 has advanced standardization of prostate MRI, but its limitations-especially in patient preparation and transition zone assessment-require attention. Combining PI-RADS with clinical biomarkers and emerging technologies moves toward more precise and personalized diagnosis. Future prospective studies are needed to validate these integrated approaches across diverse clinical settings.

Indexed as

artificial intelligence (AI)biparametric magnetic resonance imaging (bpMRI)multiparametric magnetic resonance imaging (mpMRI)Prostate cancer (PCa)Prostate Imaging Reporting and Data System v2.1 (PI-RADS v2.1)

Identifiers

PMID42293821
PMCPMC13263862

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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.