MP09-11 THE APPLICATION OF ARTIFICIAL INTELLIGENCE FOR RENAL STONE VOLUME DETERMINATION: READY FOR PRIME TIME? (2023)

You have accessJournal of UrologyCME1 Apr 2023MP09-11 THE APPLICATION OF ARTIFICIAL INTELLIGENCE FOR RENAL STONE VOLUME DETERMINATION: READY FOR PRIME TIME? Andrei D. Cumpanas, Kalon L. Morgan, Chanon Chantaduly, Rohit Bhatt, Antonio R. H. Gorgen, Allen Rojhani, Amanda McCormac, Candice Minh Tran, Paul Piedras, Seyed Amiryaghoub Lavasani, Akhil Peta, Andrew Brevick, Lilian Xie, Rajiv Karani, Zachary E. Tano, Sohrab N. Ali, Pengbo Jiang, Roshan M. Patel, Jaime Landman, Peter Chang, and Ralph V. Clayman Andrei D. CumpanasAndrei D. Cumpanas More articles by this author , Kalon L. MorganKalon L. Morgan More articles by this author , Chanon ChantadulyChanon Chantaduly More articles by this author , Rohit BhattRohit Bhatt More articles by this author , Antonio R. H. GorgenAntonio R. H. Gorgen More articles by this author , Allen RojhaniAllen Rojhani More articles by this author , Amanda McCormacAmanda McCormac More articles by this author , Candice Minh TranCandice Minh Tran More articles by this author , Paul PiedrasPaul Piedras More articles by this author , Seyed Amiryaghoub LavasaniSeyed Amiryaghoub Lavasani More articles by this author , Akhil PetaAkhil Peta More articles by this author , Andrew BrevickAndrew Brevick More articles by this author , Lilian XieLilian Xie More articles by this author , Rajiv KaraniRajiv Karani More articles by this author , Zachary E. TanoZachary E. Tano More articles by this author , Sohrab N. AliSohrab N. Ali More articles by this author , Pengbo JiangPengbo Jiang More articles by this author , Roshan M. PatelRoshan M. Patel More articles by this author , Jaime LandmanJaime Landman More articles by this author , Peter ChangPeter Chang More articles by this author , and Ralph V. ClaymanRalph V. Clayman More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003224.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Given the irregular shape of most renal stones, linear measurements as well as the use of the ellipsoid formula have proven inaccurate in depicting stone volume. In contrast, CT-based, 3D-stone volume measurement have proven to be a far more accurate determination of stone volume; however, using a 3D slicer program to derive CT-based stone volume is both time intensive and subject to human error. Accordingly, we sought to train a deep learning convolutional neural network (CNN) to automate kidney segmentation and CT-based stone volume calculation. METHODS: A total of 322 CT exams in patients with renal stones were used in this study. A total of 80% of the data was used for algorithm training while the remaining 20% of the data used for algorithm validation. “Ground truth” for actual stone volume, was determined by manual segmentation of the stones on the 322 CT scans using the 3D Slicer software program. Using an initial seed point manually identified for each stone, a 16 layer fully convolutional contracting-expanding neural network spanning 473,410 parameters, was designed to detect and segment renal calculi. To assess the accuracy of the CNN in identifying and calculating the stone volume, both a Pearson correlation coefficient and a Dice Score were calculated (Figure 1). Statistical analysis was aggregated following a five-fold cross-validation. RESULTS: The CNN algorithm calculated stone volumes had a Dice score of 0.967 and a Pearson correlation coefficient (R) of 0.999 compared to the ground truth volumes. CONCLUSIONS: A deep learning CNN developed at our institution was able to automatically segment renal stones providing an accurate, efficient, and consistent tool for determining stone volume. Source of Funding: None. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e108 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrei D. Cumpanas More articles by this author Kalon L. Morgan More articles by this author Chanon Chantaduly More articles by this author Rohit Bhatt More articles by this author Antonio R. H. Gorgen More articles by this author Allen Rojhani More articles by this author Amanda McCormac More articles by this author Candice Minh Tran More articles by this author Paul Piedras More articles by this author Seyed Amiryaghoub Lavasani More articles by this author Akhil Peta More articles by this author Andrew Brevick More articles by this author Lilian Xie More articles by this author Rajiv Karani More articles by this author Zachary E. Tano More articles by this author Sohrab N. Ali More articles by this author Pengbo Jiang More articles by this author Roshan M. Patel More articles by this author Jaime Landman More articles by this author Peter Chang More articles by this author Ralph V. Clayman More articles by this author Expand All Advertisement PDF downloadLoading ...