Pd36-09 Initial Experience With Artificial Intelligence-Enabled Multispectral Imaging to Identify Cancerous Margins in Robotic-Assisted Radical Prostatectomy

You have accessJournal of UrologySurgical Technology & Simulation: Artificial Intelligence III (PD36)1 May 2024PD36-09 INITIAL EXPERIENCE WITH ARTIFICIAL INTELLIGENCE-ENABLED MULTISPECTRAL IMAGING TO IDENTIFY CANCEROUS MARGINS IN ROBOTIC-ASSISTED RADICAL PROSTATECTOMY Ahmed Gamal, Shady Saikali, Abdel Rahman Jaber, Marcio Covas Moschovas, Travis Rogers, and Vipul Patel Ahmed GamalAhmed Gamal , Shady SaikaliShady Saikali , Abdel Rahman JaberAbdel Rahman Jaber , Marcio Covas MoschovasMarcio Covas Moschovas , Travis RogersTravis Rogers , and Vipul PatelVipul Patel View All Author Informationhttps://doi.org/10.1097/01.JU.0001008916.72488.6a.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: MarginAssure Imaging System developed by CytoVeris uses a Multi-Spectral Tissue Auto-Fluorescence Imaging (MS-TAFI) concept and employs AI-based machine learning algorithms in tumor detection. This platform is capable of analyzing the unique "optical fingerprint" of tissue based on its intrinsic biomolecular and morphological characteristics without requiring the use of dyes or imaging agents. The AI-generated output produced by the system displays the presence or absence of cancerous tissue. In this scenario, using this technology, we aim to identify in real time extracapsular extension (ECE) and PSM. METHODS: This is a prospective study performed from March 2023 to July 2023 in our center. We evaluated 511 margins from 179 patients and divided the machine learning process into two phases: Phase 1 (training) consists of using MarginAssure to image excised prostate specimens and correlate the results with clinical data including preoperative MRI images and biopsy results as well as postoperative histopathology diagnosis to develop the "labeled" data. Phase 2 (testing) will be the validation of the device on immediately excised prostate specimens before fixation in the intraoperative setting. Postoperatively, the histopathology "gold standard" will be the determinate of positive or negative margins. RESULTS: The median age 65, Median AUA 14, median SHIM 19, Overall PSM 22% and overall EPE 50%. Our analysis described76.9% accuracy, 74.4% AUC, 76.5% specificity, and 91.6% sensitivity, 95% confidence interval is (76 +/- 0.1568). These early, initial results validate the feasibility of the approach. CONCLUSIONS: Initial results showed that the MarginAssure Imaging System has the potential to differentiate between cancerous and benign tissue which may enhance the precision of tumor resection during radical prostatectomy. We described acceptable sensitivity and specificity rates of detection. Next steps would include building a more comprehensive database for algorithm training/testing. Source of Funding: No Fund © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e796 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Ahmed Gamal More articles by this author Shady Saikali More articles by this author Abdel Rahman Jaber More articles by this author Marcio Covas Moschovas More articles by this author Travis Rogers More articles by this author Vipul Patel More articles by this author Expand All Advertisement PDF downloadLoading ...