MP13-19 COMPARISON OF CANCER DETECTION RATES IN MICRO-ULTRASOUND BIOPSIES VERSUS ROBOTIC ULTRASOUND-MAGNETIC RESONANCE IMAGING FUSION BIOPSIES FOR PROSTATE CANCER
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Résumé
You have accessJournal of UrologyProstate Cancer: Detection & Screening I (MP13)1 Apr 2019MP13-19 COMPARISON OF CANCER DETECTION RATES IN MICRO-ULTRASOUND BIOPSIES VERSUS ROBOTIC ULTRASOUND-MAGNETIC RESONANCE IMAGING FUSION BIOPSIES FOR PROSTATE CANCER Oliver R. Claros*, Fabio Muttin, Rafael R. Tourinho-Barbosa, Anna C. Gallardo, Eric Barret, François Rozet, Nathalie Cathala, Dominique Prapotnich, Annick Mombet, Rafael Sanchez-Salas, and Xavier Cathelineau Oliver R. Claros*Oliver R. Claros* More articles by this author , Fabio MuttinFabio Muttin More articles by this author , Rafael R. Tourinho-BarbosaRafael R. Tourinho-Barbosa More articles by this author , Anna C. GallardoAnna C. Gallardo More articles by this author , Eric BarretEric Barret More articles by this author , François RozetFrançois Rozet More articles by this author , Nathalie CathalaNathalie Cathala More articles by this author , Dominique PrapotnichDominique Prapotnich More articles by this author , Annick MombetAnnick Mombet More articles by this author , Rafael Sanchez-SalasRafael Sanchez-Salas More articles by this author , and Xavier CathelineauXavier Cathelineau More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555295.45193.66AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: We aimed to compare the cancer detection rates in patients who underwent micro-ultrasound biopsy (MB) versus Robotic ultrasound-magnetic resonance imaging fusion biopsies (RFB) for prostate cancer. METHODS: Between February 2017 and September 2018, 451 biopsies were performed at our institution. We performed a matched pair analysis based on prostate volume and PSA. We selected 271 patients that underwent target biopsy that composed the population of the study. In total 223 men underwent RFB, and 48 underwent MB. The study cohort was divided into two groups: robotic ultrasound-magnetic resonance imaging fusion biopsy (Group A) and micro-ultrasound biopsy (Group B). Micro-ultrasound imaging was performed using the high resolution ExactVu system (29 MHz, Exact Imaging, Markham, Canada). RFB was performed using Artemis Device (Eigen, Grass Valley, CA). Biopsy samples were taken from targets in each modality, plus systematic samples. RESULTS: There were no differences according cancer detection rates except for target detection rates of clinically significant tumors. The prostate cancer detection rate was 67.7% (151) in group A and 62.5% (30) in group B (p=0.48) The detection of clinically significant cancer defined as patients with Gleason score greater or equal to 3+ 4 was 31.8%(71) in group A and 39.5% (19) in group B (p=0.31). The cancer detection rate of random biopsies were similar in group A and group B (21.5% vs. 22.91% respectively ; p=0.83). Patients from Group B had higher clinically significant tumours detection in target biopsies (37.5% vs. 22.86%; p=0.035). CONCLUSIONS: Our study suggests that micro-ultrasound biopsy may be comparable to RFB according to prostate cancer detection. Micro-ultrasound might play a role in cognitive fusion biopsies. Source of Funding: none Paris, France© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e184-e185 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Oliver R. Claros* More articles by this author Fabio Muttin More articles by this author Rafael R. Tourinho-Barbosa More articles by this author Anna C. Gallardo More articles by this author Eric Barret More articles by this author François Rozet More articles by this author Nathalie Cathala More articles by this author Dominique Prapotnich More articles by this author Annick Mombet More articles by this author Rafael Sanchez-Salas More articles by this author Xavier Cathelineau More articles by this author Expand All Advertisement PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».