ReviewEuropean radiology2026
Ongoing and completed clinical trials on prostate cancer screening using MRI.
Review in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Deep learning-based segmentation and detection of focal liver lesions on multi-sequence non-contrast MRI.Abdominal radiology (New York) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Before the introduction of prostate MRI, prostate cancer screening relied on prostate-specific antigen (PSA) testing followed by a systematic biopsy. Although this approach reduced prostate cancer mortality in large, randomized screening trials, its net benefit was questionable because of substantial overdiagnosis. In response, more precise screening tools have been developed. Diagnostic studies demonstrate that MRI has a high sensitivity for clinically significant prostate cancer and a low sensitivity for low-grade cancer, making it well-suited as a triage before biopsy. Using MRI as the primary screening test increases detection of potentially clinically significant cancer, while sequential strategies-such as those used in the STHLM3-MRI trial-reduce the number of MRI scans, unnecessary biopsies and low-grade cancer diagnoses with maintained detection of clinically significant cancer. Several ongoing randomized trials now incorporate PSA-triggered MRI in repeated screening rounds. The Gothenburg 2 trial has reported that its MRI-targeted biopsy pathway halves low-grade cancer detection but misses a few clinically significant cancers. Proscreen evaluates a screening pathway with an ancillary kallikrein test to select men for MRI, PROBASE start age 45 years, and large-scale initiatives-such as organized prostate cancer testing (OPT) programs-evaluate real-world feasibility. Key challenges include optimizing MRI protocols, improving consistency in image interpretation, and reducing false-positive findings, particularly in younger men. Centralized reading, AI support, and refined risk stratification may enhance scalability. Accumulating evidence from ongoing trials and population-based programs suggests that MRI-based screening strategies improve the benefit-to-harm ratio in prostate cancer screening. KEY POINTS: Question This special report summarizes the evidence from ongoing and completed clinical trials on prostate cancer screening using MRI. Findings Across diagnostic and randomized screening trials, MRI-based pathways reduce low-grade cancer detection and biopsy rates while maintaining detection of clinically significant prostate cancer. Clinical relevance MRI-based screening improves the benefit-harm balance by avoiding unnecessary biopsies and overdiagnosis while maintaining early detection of aggressive prostate cancer, enabling safer, more precise population-level screening for men.
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.