Evidence map›Paper›PMID 39076245›Full record

ArticleEuropean urology open science2024

Inter-reader Agreement for Prostate Cancer Detection Using Micro-ultrasound: A Multi-institutional Study.

Steve R Zhou, Moon Hyung Choi, Sulaiman Vesal, Adam Kinnaird, Wayne G Brisbane, Giovanni Lughezzani, Davide Maffei, Vittorio Fasulo, Patrick Albers, Lichun Zhang and 5 more

Registry-linked trialAbstract read
In one paragraph

Article in European urology open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04981223 (Predicting Location and Extent of Prostate Cancer Using Micro-Ultrasound Imaging), which is not on this map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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.

NCT04981223 nacompletednot on this map

Predicting Location and Extent of Prostate Cancer Using Micro-Ultrasound Imaging

TypeinterventionalSponsorStanford UniversityRan2022 to 2024Enrolled95ConditionsProstate CancerArmsExactVu
3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. BJUI compass · 2026
    Article
  6. Micro-ultrasound for prostate cancer.Nature reviews. Urology · 2026
    Review
  7. Article
  8. Article
  9. Review
  10. Article
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

15 authors.

Steve R ZhouDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Moon Hyung ChoiDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Sulaiman VesalDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Adam KinnairdDepartment of Urology, University of Alberta, Edmonton, Canada.
Wayne G BrisbaneDepartment of Urology, University of California-Los Angeles, Los Angeles, CA, USA.
Giovanni LughezzaniDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Davide MaffeiDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Vittorio FasuloDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Patrick AlbersDepartment of Urology, University of Alberta, Edmonton, Canada.
Lichun ZhangDepartment of Radiology, Stanford School of Medicine, Palo Alto, CA, USA.
Zachary KornbergDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Richard E FanDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Wei ShaoDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Mirabela RusuDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Geoffrey A SonnDepartment of Urology, Stanford School of Medicine, Palo Alto, CA, USA.

Funding

Rad-pathomic deep learning models to assist radiologists in differentiating aggressive from indolent prostate cancer on MRIR37CA260346 · NCI · STANFORD UNIVERSITY · PI Mirabela Rusu · 2022 to 2026
$2.8M
NCI NIH HHS R37 CA260346
6 · The paper itself

Abstract

Background and objective: Micro-ultrasound (MUS) uses a high-frequency transducer with superior resolution to conventional ultrasound, which may differentiate prostate cancer from normal tissue and thereby allow targeted biopsy. Preliminary evidence has shown comparable sensitivity to magnetic resonance imaging (MRI), but consistency between users has yet to be described. Our objective was to assess agreement of MUS interpretation across multiple readers. Methods: After institutional review board approval, we prospectively collected MUS images for 57 patients referred for prostate biopsy after multiparametric MRI from 2022 to 2023. MUS images were interpreted by six urologists at four institutions with varying experience (range 2-6 yr). Readers were blinded to MRI results and clinical data. The primary outcome was reader agreement on the locations of suspicious lesions, measured in terms of Light's κ and positive percent agreement (PPA). Reader sensitivity for identification of grade group (GG) ≥2 prostate cancer was a secondary outcome. Key findings and limitations: Analysis revealed a κ value of 0.30 (95% confidence interval [CI] 0.21-0.39). PPA was 33% (95% CI 25-42%). The mean patient-level sensitivity for GG ≥2 cancer was 0.66 ± 0.05 overall and 0.87 ± 0.09 when cases with anterior lesions were excluded. Readers were 12 times more likely to detect higher-grade cancers (GG ≥3), with higher levels of agreement for this subgroup (κ 0.41, PPA 45%). Key limitations include the inability to prospectively biopsy reader-delineated targets and the inability of readers to perform live transducer maneuvers. Conclusions and clinical implications: Inter-reader agreement on the location of suspicious lesions on MUS is lower than rates previously reported for MRI. MUS sensitivity for cancer in the anterior gland is lacking. Patient summary: The ability to find cancer on imaging scans can vary between doctors. We found that there was frequent disagreement on the location of prostate cancer when doctors were using a new high-resolution scan method called micro-ultrasound. This suggests that the performance of micro-ultrasound is not yet consistent enough to replace MRI (magnetic resonance imaging) for diagnosis of prostate cancer.

Indexed as

Inter-reader agreementMicro-ultrasoundProstate cancerTargeted biopsy

Identifiers

PMID39076245
PMCPMC11284543

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.