PD09-11 POTENTIAL ROLE OF MICRO-ULTRASOUND IN THE DIFFERENTIATION BETWEEN MUSCLE-INVASIVE AND NON-MUSCLE INVASIVE BLADDER CANCER: A PROSPECTIVE ANALYSIS
Notice bibliographique
Résumé
You have accessJournal of UrologyBladder Cancer: Non-invasive I (PD09)1 Sep 2021PD09-11 POTENTIAL ROLE OF MICRO-ULTRASOUND IN THE DIFFERENTIATION BETWEEN MUSCLE-INVASIVE AND NON-MUSCLE INVASIVE BLADDER CANCER: A PROSPECTIVE ANALYSIS Pietro Diana, Giovanni Lughezzani, Alessandro Uleri, Nicola Frego, Roberto Contieri, Marco Paciotti, Vittorio Fasulo, Piergiuseppe Colombo, Nicolomaria Buffi, Alberto Saita, Paolo Casale, Rodolfo Hurle, and Massimo Lazzeri Pietro DianaPietro Diana More articles by this author , Giovanni LughezzaniGiovanni Lughezzani More articles by this author , Alessandro UleriAlessandro Uleri More articles by this author , Nicola FregoNicola Frego More articles by this author , Roberto ContieriRoberto Contieri More articles by this author , Marco PaciottiMarco Paciotti More articles by this author , Vittorio FasuloVittorio Fasulo More articles by this author , Piergiuseppe ColomboPiergiuseppe Colombo More articles by this author , Nicolomaria BuffiNicolomaria Buffi More articles by this author , Alberto SaitaAlberto Saita More articles by this author , Paolo CasalePaolo Casale More articles by this author , Rodolfo HurleRodolfo Hurle More articles by this author , and Massimo LazzeriMassimo Lazzeri More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001977.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Magnetic resonance imaging (MRI) has been proposed as a staging tool for bladder cancer (BC), but its use has been limited by its high costs and limited availability. Microultrasound (mUS) is a novel technology capable providing high-resolution images, which was initially developed for the diagnosis of PCa. In the setting of BC, a preliminary study has showed that mUS may be capable to differentiate the bladder wall layers, identify BC and differentiate between non-muscle invasive (NMIBC) and muscle-invasive BC (MIBC). The aim of this study is to confirm on a larger scale the potential role of mUS in the identification and characterization of BC. METHODS: This is an observational study of prospectively collected data performed in patients diagnosed with primary BC and scheduled for an endoscopic treatment. Micro-US was performed before transurethral resection (TUR) of bladder tumor using the ExactVu system with an EV29L 29-MHz side-fire transducer (Exact Imaging, Markham, Canada). The endpoints were to assess the diagnostic accuracy of mUS in identifying BC and in differentiating between NMIBC and MIBC comparing the mUS findings with the histopathological results. RESULTS: Between April 2018 and December 2020, we prospectively enrolled 94 consecutive patients with primary BC. Micro-US window was not acceptable in 10 patients and 2 patient presented with a tumor looking mass at both cystoscopy and abdominal US but histology was negative for bladder cancer showing chronic cystitis. In all the other 82 patients, mUS clearly identified the three bladder wall layers and the BC as heterogeneous structures protruding from the normal wall. The reported accuracy, sensitivity, specificity, and positive, and negative predictive values for mUS were 82.9%, 87.5%, 81%, 65.6%, and 94%, respectively. The ROC curve analysis for the mUS in detecting MIBC shows an AUC of 0.843 (CI 95% 0.746-0.940). CONCLUSIONS: These results confirm in a larger population the potential role of mUS to differentiate the bladder wall layers and reliably differentiate between NMIBC and MIBC in the great majority of patients. In consequence, mUS may represent a cheaper and less time-consuming alternative to mpMRI. Further comparative studies between mUS and MRI are still warranted to validate this imaging technique in the BC staging before its introduction in clinical practice. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e124-e124 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Pietro Diana More articles by this author Giovanni Lughezzani More articles by this author Alessandro Uleri More articles by this author Nicola Frego More articles by this author Roberto Contieri More articles by this author Marco Paciotti More articles by this author Vittorio Fasulo More articles by this author Piergiuseppe Colombo More articles by this author Nicolomaria Buffi More articles by this author Alberto Saita More articles by this author Paolo Casale More articles by this author Rodolfo Hurle More articles by this author Massimo Lazzeri More articles by this author Expand All Advertisement Loading ...
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».