MP17-15 INFRARED-(IR)-IMAGING CLASSIFIES PROSTATE CANCER LABEL-FREE: A PROSPECTIVE IR-PROSPECT-STUDY SHOWS POTENTIAL FOR CLINICAL APPLICATION AND RESEARCH

Abstract

You have accessJournal of UrologyCME1 Apr 2023MP17-15 INFRARED-(IR)-IMAGING CLASSIFIES PROSTATE CANCER LABEL-FREE: A PROSPECTIVE IR-PROSPECT-STUDY SHOWS POTENTIAL FOR CLINICAL APPLICATION AND RESEARCH Henning Bahlburg, Claus Kuepper, Frederik Grosserueschkamp, Nina Goertzen, Carlo Sternemann, Sebastian Berg, Karl Tully, Axel Mosig, Rein-Jueri Palisaar, Andrea Tannapfel, Klaus Gerwert, Joachim Noldus, and Florian Roghmann Henning BahlburgHenning Bahlburg More articles by this author , Claus KuepperClaus Kuepper More articles by this author , Frederik GrosserueschkampFrederik Grosserueschkamp More articles by this author , Nina GoertzenNina Goertzen More articles by this author , Carlo SternemannCarlo Sternemann More articles by this author , Sebastian BergSebastian Berg More articles by this author , Karl TullyKarl Tully More articles by this author , Axel MosigAxel Mosig More articles by this author , Rein-Jueri PalisaarRein-Jueri Palisaar More articles by this author , Andrea TannapfelAndrea Tannapfel More articles by this author , Klaus GerwertKlaus Gerwert More articles by this author , Joachim NoldusJoachim Noldus More articles by this author , and Florian RoghmannFlorian Roghmann More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003237.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The Goal of this study was to evaluate whether artificial intelligence (AI) is suited to classify prostate cancer (PCa) label-free. In the last decade, IR-microscopy was able to showcase its potential to classify different tissues and pathologies in several studies. Recorded IR-Spectra reflect the biochemical status of the examined cell. The application of quantum-cascade lasers as source of light has accelerated data acquisition and thus enabled integration into clinical research pathways METHODS: In this study, tissue from 258 patients was investigated. Initially, AI with Random Forrest (RF) algorithm was applied. Prostatic tissue showed to be morphologically more demanding than expected. As the study population increased, a robust deep-learning AI was implemented. RESULTS: Deep-learning AI reached an AUC of 0.96 with a sensitivity of ∼98% and a specificity of ∼83% when classifying PCa label-free. This marks an improvement compared to RF, which showed a sensitivity of 82% and a specificity of 69%. CONCLUSIONS: AI-based IR-Imaging detects PCa with a sensitivity of 98%. Further improvement may be achieved by additional training and increase in sample size. Subsequently, laser-assisted micro-dissection may allow precise and homogenous sampling for detailed molecular analysis of tumor tissues. Results may be used to train AI in the detection of molecular tumor characteristics such as oncological targets. Source of Funding: This project was funded by the Ministry of Culture and Research of the Federal State of Northrine Westphalia © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e218 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Henning Bahlburg More articles by this author Claus Kuepper More articles by this author Frederik Grosserueschkamp More articles by this author Nina Goertzen More articles by this author Carlo Sternemann More articles by this author Sebastian Berg More articles by this author Karl Tully More articles by this author Axel Mosig More articles by this author Rein-Jueri Palisaar More articles by this author Andrea Tannapfel More articles by this author Klaus Gerwert More articles by this author Joachim Noldus More articles by this author Florian Roghmann More articles by this author Expand All Advertisement PDF downloadLoading ...