Evidence map›Paper›PMID 40192805›Full record

ArticleEuropean radiology2025

Diffusion levels for quantitative assessment of the apparent diffusion coefficient value in prostate MRI: a proof-of-concept bicentric study.

Rossano Girometti, Valeria Peruzzi, Paola Clauser, Nina Pötsch, Maria De Martino, Miriam Isola, Gianluca Giannarini, Alessandro Crestani, Chiara Zuiani, Lorenzo Cereser and 1 more

Abstract readMulticenter Study
In one paragraph

Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. The evolving PI-RADS paradigm.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Review
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

11 authors.

Rossano GiromettiInstitute of Radiology, Department of Medicine (DMED), University of Udine, Udine, Italy. rossano.girometti@uniud.it.ORCID http://orcid.org/0000-0002-0904-5147
Valeria PeruzziInstitute of Radiology, Department of Medicine (DMED), University of Udine, Udine, Italy.
Paola ClauserDepartment of Biomedical Imaging and Image-guided Treatment, Medical University of Vienna, Vienna, Austria.
Nina PötschDepartment of Biomedical Imaging and Image-guided Treatment, Medical University of Vienna, Vienna, Austria.
Maria De MartinoDivision of Medical Statistics, Department of Medicine (DMED), University of Udine, Udine, Italy.
Miriam IsolaDivision of Medical Statistics, Department of Medicine (DMED), University of Udine, Udine, Italy.
Gianluca GiannariniUrology Unit, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), University Hopital "S. Maria della Misericordia", Udine, Italy.
Alessandro CrestaniUrology Unit, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), University Hopital "S. Maria della Misericordia", Udine, Italy.
Chiara ZuianiInstitute of Radiology, Department of Medicine (DMED), University of Udine, Udine, Italy.
Lorenzo CereserInstitute of Radiology, Department of Medicine (DMED), University of Udine, Udine, Italy.
Pascal At BaltzerDepartment of Biomedical Imaging and Image-guided Treatment, Medical University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the performance of Diffusion levels (DLs) in diagnosing clinically significant prostate cancer (csPCa) when combined with the PI-RADS version 2.1. MATERIALS AND

methodsThis retrospective, bicentric study included 261 men who underwent 3.0-T prostate MRI between March 2020 and April 2023, receiving systematic and target prostate biopsy on PI-RADS ≥ 3 lesions. Two readers measured the Apparent diffusion coefficient (ADC) of PI-RADS 1-5 findings in the peripheral zone. By plotting the cumulative frequency of csPCa versus ADCs and using ROC analysis, we derived four DLs expressing levels of restricted diffusion, i.e., very low DL (VL-DL), low DL (L-DL), intermediate DL (I-DL), and high DL (H-DL). We compared the per-lesion diagnostic performance in assessing csPCa (grading group ≥ 2 cancer) assuming to biopsy PI-RADS ≥ 3 lesions (strategy 1), PI-RADS ≥ 3 lesions adjusted with ADC values (strategy 2-4), and PI-RADS ≥ 3 lesions adjusted with DLs (strategy 5-7). Net benefit was assessed with decision curve analysis.

resultscsPCa was found in 79/261 men (30.3%) and 152/528 lesions (28.8%). There was a negative correlation (p < 0.0001) between ADC versus malignancy rate (tau -0.970) and DLs versus csPCa grading group (tau -0.614). csPCa prevalence was highest in VL-DL (72.2%) and L-DL (54.4%). Most DLs-based strategies increased specificity, positive predictive value (PPV), and net benefit compared to ADC-based strategies or PI-RADS alone. The best strategy showed 94.7% sensitivity, 82.9% specificity, 69.2% PPV, and 97.5% negative predictive value.

conclusionWhile larger-scale validation is needed, DLs have the potential to improve PI-RADS-based biopsy decisions for detecting csPCa in the peripheral zone. KEY POINTS: Question It is still unclear how to incorporate quantitative information from diffusion-weighted imaging (DWI) into prostate MRI. Findings Combining DWI-derived diffusion levels (DLs) with the PI-RADS version 2.1 categorization reduced false positives while preserving high sensitivity for clinically significant prostate cancer. Clinical relevance DLs permit to easily account for ADC values of prostate lesions and, in turn, refine biopsy decisions.

Indexed as

Diffusion Magnetic Resonance ImagingProstatic NeoplasmsAgedHumansImage-Guided BiopsyMaleMiddle AgedNeoplasm GradingProof of Concept StudyProstateRetrospective StudiesSensitivity and SpecificityBiopsyDiffusion magnetic resonance imagingMagnetic resonance imagingProstatic neoplasms

Identifiers

PMID40192805
PMCPMC12417251

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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.