MP32-17 PREDICTING THE MIBC IN STALKED TUMOR OF VI-RADS 2 USING NOMOGRAM OF MRI CHARACTERISTICS

Abstract

You have accessJournal of UrologyCME1 Apr 2023MP32-17 PREDICTING THE MIBC IN STALKED TUMOR OF VI-RADS 2 USING NOMOGRAM OF MRI CHARACTERISTICS Qiang Lv, Xiao Yang, Qiang Cao, and Lingkai Cai Qiang LvQiang Lv More articles by this author , Xiao YangXiao Yang More articles by this author , Qiang CaoQiang Cao More articles by this author , and Lingkai CaiLingkai Cai More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003265.17AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Background: The vesical imaging-reporting and data system (VI-RADS) scores was created to report the staging of bladder cancer (BCa). A proportion of BCa with stalk pathologized as MIBC. Purpose: To measure the MRI characteristics of the tumor and the stalk and establish a model for predicting muscle-invasive bladder cancer (MIBC) in VI-RADS 2. METHODS: From November 2012 and May 2022, a total of 178 patients with bladder cancer with stalk were included in this study and divided into training and validation cohorts by a ratio of 7:3. The univariable logistic regression analysis and Lasso regression were utilized to select the most useful predictive features from among 22 variables. Then, a logistic regression analysis was used to develop the prediction model with a nomogram. The area under the curves (AUCs) of receiver operating characteristic (ROC) curves and calibration curves were performed to demonstrate the performance and accuracy of the nomogram. The decision curve analyses were applied to assess the clinical benefit of the nomogram. RESULTS: Four variables as potential risk factors for MIBC of the stalk were selected, including the size of the tumor over 3cm, the increased width of the stalk, the morphology of the stalk and the decreased normalized T value. The AUCs of the model for predicting MIBC were 0.95 (95%CI: 0.91-0.99) in the training cohort and 0.91 (95%CI: 0.79-1.00) in the validation cohort. The calibration curve of the nomogram suggested excellent agreement. The decision curve analyses curve indicated that using the nomogram to predict MIBC added more net benefit than the all or none strategies. CONCLUSIONS: In this study, we constructed the MIBC prediction model by combining clinical data and MRI features of the stalk and tumor in VI-RADS 2. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e448 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Qiang Lv More articles by this author Xiao Yang More articles by this author Qiang Cao More articles by this author Lingkai Cai More articles by this author Expand All Advertisement PDF downloadLoading ...