V12-01 A NEW TOOL ABLE TO REDUCE THE POSITIVE SURGICAL MARGIN RATE DURING ROBOTIC PROSTATECTOMY: ARTIFICIAL INTELLIGENCE 3D AUGMENTED REALITY GUIDED SELECTIVE BIOPSY

You have accessJournal of UrologyProstate Oncology I (Prostatectomy) (V12)1 Sep 2021V12-01 A NEW TOOL ABLE TO REDUCE THE POSITIVE SURGICAL MARGIN RATE DURING ROBOTIC PROSTATECTOMY: ARTIFICIAL INTELLIGENCE 3D AUGMENTED REALITY GUIDED SELECTIVE BIOPSY Porpiglia Francesco, Enrico Checcucci, Daniele Amparore, Sabrina De Cillis, Gabriele Volpi, Federica Massa, Enrico Bollito, Pietro Piazzolla, Andrea Bellin, Matteo Manfredi, Enrico Vezzetti, and Cristian Fiori Porpiglia FrancescoPorpiglia Francesco More articles by this author , Enrico CheccucciEnrico Checcucci More articles by this author , Daniele AmparoreDaniele Amparore More articles by this author , Sabrina De CillisSabrina De Cillis More articles by this author , Gabriele VolpiGabriele Volpi More articles by this author , Federica MassaFederica Massa More articles by this author , Enrico BollitoEnrico Bollito More articles by this author , Pietro PiazzollaPietro Piazzolla More articles by this author , Andrea BellinAndrea Bellin More articles by this author , Matteo ManfrediMatteo Manfredi More articles by this author , Enrico VezzettiEnrico Vezzetti More articles by this author , and Cristian FioriCristian Fiori More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002093.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To test our new Artificial Intelligence based Automatic Augmented Reality system in order to detect tumoral extracapsular extension (ECE) at the level of NVBs during RARP. METHODS: A dedicated protocol was designed and patients with suspect ECE, as reported at preoperative high-resolution multi-parametric magnetic imaging (mpMRI, 1mm slice), were enrolled between December 2020 and January 2021. 3D reconstructions were created and subsequently overlapped over the endoscopic view during RARP thanks to the Da Vinci console’s Tile-Pro software, allowing to perform an AR-RARP. Specifically for this study, a new software able to automatically overlap the 3D-reconstruction thanks to the catheter was developed, using Artificial Intelligence Convolutional Neuronal Network (CNN) algorithms. After the extirpative phase of standard NS-RARP, with a careful hemostasis’ control, a Foley catheter was introduced in the operative field. The Artificial Intelligence based Automatic Augmented Reality system was able to detect the catheter and determine its space orientation. The virtual model was subsequently anchored to the image and virtually projected in the operatory field. The AR-image was displayed in the Da Vinci console thanks to the Tile-Pro software and the surgeon was then able to modify the reconstruction, zooming it in or out while maintaining the proportion throughout the maneuver. The transparency of 3D-models could be modulated, highlighting the extracapsular extension of the tumour and hiding the remaining part of the organ. Selective biopsies guided by 3D AR images, were then performed. At the end of this phase, the visual correspondence between the virtual reconstruction and the actual prostate was checked by re-inserting the real prostate in the operatory field, proving the precise overlapping between the model and the organ. RESULTS: 10 patients with suspicious ECE detected by preoperative mpMRI were enrolled. The final pathology confirmed ECE (pT3a/b) in 8/10 cases, with a Cohen Kappa coefficient (κ) of 0,68 and with a PSM rate of 30%. AR guided biopsies of the surgical bed revealed the presence of cancer in 75% (6/8) of the cases, confirming the accuracy of our new technology. CONCLUSIONS: The current findings suggest that Artificial Intelligence with CNNs allows to correctly overlap the 3D model, automatically. The use of this technology for the identification of ECE in the resection bed might reduce PSMs rates, improving the oncological outcomes in patients affected by locally advanced disease. Source of Funding: none © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1023-e1023 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Porpiglia Francesco More articles by this author Enrico Checcucci More articles by this author Daniele Amparore More articles by this author Sabrina De Cillis More articles by this author Gabriele Volpi More articles by this author Federica Massa More articles by this author Enrico Bollito More articles by this author Pietro Piazzolla More articles by this author Andrea Bellin More articles by this author Matteo Manfredi More articles by this author Enrico Vezzetti More articles by this author Cristian Fiori More articles by this author Expand All Advertisement PDF downloadLoading ...