Pd36-12 Artificial Intelligence as a Time-Efficient and Quality Tool for Contouring in Prostate Cancer Diagnostics

You have accessJournal of UrologySurgical Technology & Simulation: Artificial Intelligence III (PD36)1 May 2024PD36-12 ARTIFICIAL INTELLIGENCE AS A TIME-EFFICIENT AND QUALITY TOOL FOR CONTOURING IN PROSTATE CANCER DIAGNOSTICS Puranjay Shori, Jong H. Kim, Robert I. Carey, and Victoria Y. Bird Puranjay ShoriPuranjay Shori , Jong H. KimJong H. Kim , Robert I. CareyRobert I. Carey , and Victoria Y. BirdVictoria Y. Bird View All Author Informationhttps://doi.org/10.1097/01.JU.0001008916.72488.6a.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: This study compares artificial intelligence (AI) derived and human-derived whole gland segmentation of the prostate, seminal vesicle, and urethra through magnetic resonance imaging (MRI) and evaluates the practical use of this technology to streamline workflow for procedures such as MRI-ultrasound fusion prostate biopsies. METHODS: The AI-generated "auto contours" for prostate MRIs of 31 patients were generated to produce contours of the prostate, seminal vesicle, and urethra. These MRIs were also contoured manually by both a board-certified urologist and a radiologist, and the volumetric conformity of the 3 groups of contours was evaluated through the Dice and Jaccard coefficients, as well as other metrics such as the Hausdorff distance (HD), and Mean Distance to Agreement (MDA). The elapsed time to produce contours was also recorded. RESULTS: The average volumetric Dice and Jaccard coefficients, HD, and MDA for the AI and urologist contoured images (AI-U) were 0.875, 0.779, 9.186 mm, and 1.410 mm for the whole gland segmentation of the prostate, 0.377, 0.260, 14.708 mm, and 4.260 mm for the seminal vesicle, and 0.283, 0.178, 18.117 mm, and 4.907 mm for the urethra; for the AI and radiologist contours (AI-R), the values were 0.757, 0.614, 17.562 mm, and 3.050 mm for the prostate, 0.451, 0.315 16.069 mm, and 4.075 mm for the seminal vesicle, and 0.162, 0.092, 19.956 mm, and 4.798 mm for the urethra. In comparing the contours of the urologist to the radiologist (U-R), the values of the prostate were 0.769, 0.630, 15.109 mm, and 2.733 mm, for the seminal vesicle, 0.471, 0.333, 12.981 mm, 3.264 mm, and for the urethra, 0.144, 0.080, 13.560 mm, and 3.406 mm. For the prostate and urethra, the AI-U comparison differed from the other comparisons (p<0.05). For the seminal vesicle, no difference in the 3 Dice coefficients was observed (p>0.05). The average times to produce contours for the AI, urologist, and radiologist were 96.5 seconds, 285.8 seconds, and 217.9 seconds, respectively (p<0.05 for each time). CONCLUSIONS: The results suggest that, for the seminal vesicle, no statistical difference between the Dice similarities of AI-U, AI-R, and U-R was observed. For the prostate and urethra, while AI-U had a higher conformity than AI-R and U-R, which presented similar conformities, it is unlikely the lower conformity is linked to the AI's accuracy. Hence, AI varies in conformity as much as any other physician and generates contours in less time. Overall, current AI software holds potential as an effort-reducing tool for streamlining prostate cancer diagnostics in the clinical setting. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e797 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Puranjay Shori More articles by this author Jong H. Kim More articles by this author Robert I. Carey More articles by this author Victoria Y. Bird More articles by this author Expand All Advertisement PDF downloadLoading ...