MP09-09 CORRELATION BETWEEN PROSTATE MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING AND HIGH-RESOLUTION MICRO-ULTRASOUND
Notice bibliographique
Résumé
You have accessJournal of UrologyCME1 Apr 2023MP09-09 CORRELATION BETWEEN PROSTATE MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING AND HIGH-RESOLUTION MICRO-ULTRASOUND Nicholas Pickersgill, M. Hassan Alkazemi, Joel Vetter, Adam Ostergar, Nimrod Barashi, Grant Henning, and Arjun Sivaraman Nicholas PickersgillNicholas Pickersgill More articles by this author , M. Hassan AlkazemiM. Hassan Alkazemi More articles by this author , Joel VetterJoel Vetter More articles by this author , Adam OstergarAdam Ostergar More articles by this author , Nimrod BarashiNimrod Barashi More articles by this author , Grant HenningGrant Henning More articles by this author , and Arjun SivaramanArjun Sivaraman More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003224.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate multiparametric magnetic resonance imaging (pMRI) has emerged as a valuable tool in the diagnostic pathway for prostate cancer. The recent introduction of high-resolution micro-ultrasound (microUS) guided prostate biopsy aims to further improve the detection of clinically significant prostate cancer (CSCaP). The correlation between these two imaging modalities is poorly understood. We investigated correlation in lesion identification between microUS and pMRI. METHODS: We reviewed our prospectively maintained database of 200 consecutive patients who underwent transperineal microUS-guided biopsy with the ExactVu™platform (Exact Imaging, Markham, Canada) between February 2021 and April 2022. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was utilized to risk stratify prostate lesions, with PRI-MUS 3-5 defined as positive. pMRI lesions were classified according to PI-RADS version 2. Clinicopathologic outcomes were analyzed. Spearman correlation testing was computed to assess the relationship between PRI-MUS and PI-RADS. Patients with sufficient data for analysis were included. RESULTS: A total of 159 patients met inclusion criteria. Of these, 117 were biopsy-naïve, 19 had a prior negative biopsy and 20 were on active surveillance. Mean±standard deviation (SD) age was 66.6±7.7 years and PSA was 10.1±4.4 ng/mL. A total of 112 patients underwent multiparametric magnetic resonance imaging (mpMRI) prior to biopsy, of which 56 were found to have PIRADS 3-5 lesions. There was a weak positive correlation between PRI-MUS and PI-RADS (r=0.23, p=0.013) (Figure 1). CONCLUSIONS: This preliminary comparison between PRI-MUS and PI-RADS scoring demonstrates a weak positive correlation between the two modalities. This may be attributable to a significant number of patients with negative pMRI who were found to have PRI-MUS 3-5 lesions. Given the rising utilization of micro-US-guided prostate biopsy and widespread use of pMRI, further prospective studies are needed to compare their ability to detect clinically significant prostate cancer. Source of Funding: Midwest Stone Institute © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e107 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nicholas Pickersgill More articles by this author M. Hassan Alkazemi More articles by this author Joel Vetter More articles by this author Adam Ostergar More articles by this author Nimrod Barashi More articles by this author Grant Henning More articles by this author Arjun Sivaraman 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 | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 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) | 0,254 | 0,066 |
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 ».