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Record W3043132908 · doi:10.5489/cuaj.6712

Comparison of micro-ultrasound and multiparametric magnetic resonance imaging for prostate cancer: A multicenter, prospective analysis

2020· article· en· W3043132908 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Urological Association Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsSunnybrook HospitalUniversity of Toronto
FundersTerry Fox Foundation
KeywordsMedicineProstate cancerProstateUltrasoundMagnetic resonance imagingRadiologyProspective cohort studyProstate biopsyBiopsyNuclear medicineCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: High-resolution micro-ultrasound has the capability of imaging prostate cancer based on detecting alterations in ductal anatomy, analogous to multiparametric magnetic resonance imaging (mpMRI). This technology has the potential advantages of relatively low cost, simplicity, and accessibility compared to mpMRI. This multicenter, prospective registry aims to compare the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of mpMRI with high-resolution micro-ultrasound imaging for the detection of clinically significant prostate cancer. METHODS: We included 1040 subjects at 11 sites in seven countries who had prior mpMRI and underwent ExactVu micro-ultrasound-guided biopsy. Biopsies were taken from both mpMRI targets (Prostate Imaging-Reporting and Data System [PI-RADS] >3 and micro-ultrasound targets (Prostate Risk Identification using Micro-ultrasound [PRIMUS] >3). Systematic biopsies (up to 14 cores) were also performed. Various strategies were used for mpMRI target sampling, including cognitive fusion with micro-ultrasound, separate software-fusion systems, and software-fusion using the micro-ultrasound FusionVu system. Clinically significant cancer was those with Gleason grade group ≥2. RESULTS: Overall, 39.5% were positive for clinically significant prostate cancer. Micro-ultrasound and mpMRI sensitivity was 94% vs. 90%, respectively (p=0.03), and NPV was 85% vs. 77%, respectively. Specificities of micro-ultrasound and MRI were both 22%, with similar PPV (44% vs. 43%). This represents the initial experience with the technology at most of the participating sites and, therefore, incorporates a learning curve. Number of cores, diagnostic strategy, blinding to MRI results, and experience varied between sites. CONCLUSIONS: In this initial multicenter registry, micro-ultrasound had comparable or higher sensitivity for clinically significant prostate cancer compared to mpMRI, with similar specificity. Micro-ultrasound is a low-cost, single-session option for prostate screening and targeted biopsy. Further larger-scale studies are required for validation of these findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.286
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it