MP19-18 MICROULTRASOUND IN CANCER-ACTIVE SURVEILLANCE (MUSIC-AS)
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Detection & Screening I (MP19)1 May 2024MP19-18 MICROULTRASOUND IN CANCER-ACTIVE SURVEILLANCE (MUSIC-AS) Patrick S. Albers, Betty Wang, Stacey Broomfield, Anaïs Medina Martin, Peter Metcalfe, Wendy Tu, Christopher Fung, and Adam Kinnaird Patrick S. AlbersPatrick S. Albers , Betty WangBetty Wang , Stacey BroomfieldStacey Broomfield , Anaïs Medina MartinAnaïs Medina Martin , Peter MetcalfePeter Metcalfe , Wendy TuWendy Tu , Christopher FungChristopher Fung , and Adam KinnairdAdam Kinnaird View All Author Informationhttps://doi.org/10.1097/01.JU.0001008716.22569.77.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Accurate assessment of tumor grade is critical for prostate cancer (PCa) Active Surveillance (AS). Multiple new technologies, including targeted biopsies and advanced imaging techniques like multiparametic magnetic resonance imaging (MRI) and high-resolution micro-ultrasound (microUS) may improve tumor risk stratification. The primary objective is to compare MRI and microUS for the detection of Gleason Grade Group ≥2 during AS. METHODS: Prospective, paired diagnostic trial of 210 men with Gleason Grade Group 1 PCa managed by AS undergoing confirmatory biopsy between 12/2022 and 10/2023 at an academic tertiary care centre. To date, 106 men have been consented for the study and 63 have undergone their confirmatory biopsies and have their pathology results available. Human research ethics board approval was obtained (HREBA.CC-22-0135). The primary outcome is the difference in detection of Grade Group ≥2 found using microUS+systematic biopsy versus MRI/US Fusion+systematic biopsy. Statistical analyses used are Chi square test, Fisher's exact test, and McNemar test. RESULTS: Of the 63 men biopsied thus far, average age of the participants was 62.2, with a median PSA of 7.4, and 30 (48%) with family history of prostate cancer in first degree relatives. 46 (73%) of the men had a PRI-MUS score ≥3, and 36 (57%) had a PI-RADS score ≥3. Gleason Grade Group ≥2 was identified in 27 (43%) men. There was no difference in the detection of Gleason Grade Group ≥2 between the imaging techniques, with all cancers detected by microUS+systematic biopsy as well as using MRI/US Fusion+systematic biopsy (p=0.99). CONCLUSIONS: The detection of upgrading to Gleason Grade Group ≥2 during AS appears similar when using microUS or MRI to inform prostate biopsy. Source of Funding: Alberta Cancer FoundationBird DogsUniversity Hospital Foundation © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e317 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Patrick S. Albers More articles by this author Betty Wang More articles by this author Stacey Broomfield More articles by this author Anaïs Medina Martin More articles by this author Peter Metcalfe More articles by this author Wendy Tu More articles by this author Christopher Fung More articles by this author Adam Kinnaird More articles by this author Expand All Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.498 | 0.204 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".