Skill-assessment during robot-assisted radioguided surgery - using artificial intelligence to extract kinematic metrics of DROP-IN gamma probe use

You have accessJournal of UrologyCME1 Apr 2023MP61-15 SKILL-ASSESSMENT DURING ROBOT-ASSISTED RADIOGUIDED SURGERY - USING ARTIFICIAL INTELLIGENCE TO EXTRACT KINEMATIC METRICS OF DROP-IN GAMMA PROBE USE Samaneh Azargoshasb, Hilda A De Barros, Daphne D.D. Rietbergen, Paolo Dell'oglio, Pim J Van Leeuwen, Christian Wagner, Tobias Maurer, Henk G. Van der poel, Matthias N. Van Oosterom, and Fijs W. B. Van Leeuwen Samaneh AzargoshasbSamaneh Azargoshasb More articles by this author , Hilda A De BarrosHilda A De Barros More articles by this author , Daphne D.D. RietbergenDaphne D.D. Rietbergen More articles by this author , Paolo Dell'oglioPaolo Dell'oglio More articles by this author , Pim J Van LeeuwenPim J Van Leeuwen More articles by this author , Christian WagnerChristian Wagner More articles by this author , Tobias MaurerTobias Maurer More articles by this author , Henk G. Van der poelHenk G. Van der poel More articles by this author , Matthias N. Van OosteromMatthias N. Van Oosterom More articles by this author , and Fijs W. B. Van LeeuwenFijs W. B. Van Leeuwen More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003319.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Radioguided prostate cancer (PCa) surgery has been greatly facilitated by the introduction of the steerable DROP-IN gamma probe technology. Reported indications include sentinel node (SN) resections and prostate-specific membrane antigen (PSMA)-targeted resections. Both make use of 99mTc-labeled imaging vectors. As result of the targeting mechanisms used the signal- and background intensities in these procedures, however, differ substantially. To study how this reflects on the surgical decision-making process we used computer-vision strategies to compare DROP-IN gamma probe use during SN- and PSMA-targeted surgeries. METHODS: A DROP-IN gamma probe was applied during 45 robot-assisted PCa surgeries from 2018 to 2021 at single tertiary care referral centre: SN resections [n=25; primary surgery; intraprostatic injection of indocyanine green (ICG)-99mTc-nanocolloid (∼200MBq, 5-6h prior to surgery)], PSMA-targeted resections [n=20; salvage surgery; intravenous injection of 99mTc-PSMA I&S (∼550MBq, 16-22h prior to surgery)}. Preoperative imaging-roadmaps were created using SPECT/CT and PET/CT imaging. Using custom tracking algorithms, based on a neural network architecture, the DROP-IN probe trajectories were extracted from endoscopic videos. Trajectories were then processed to extract key kinematic performance metrics. To allow for skill-assessment, the metrics were incorporated in decision-making and dexterity scores. RESULTS: The nodal signal intensities in PSMA- vs SN-targeted resections were 550 vs. 1200 counts in preoperative SPECT-CT scans (p=0.098) and 150 vs 1050 counts/s with regard to intraoperative probe readouts (p<0.001). Due to the relatively high background signals observed during PSMA tracing a 2-fold reduction in the intraoperative signal to background ratio (SBR) (1.8 vs. 3.6; p<0.001) was observed in this setting. Kinematic analysis revealed significant differences in a number of metrics, e.g., target identification time (368 sec per PSMA lesion vs. 75 sec per SLN; p<0.001), number of probe pick-ups (5 vs. 1; p<0.001), and reduction in dexterity (281-fold; p<0.001) and decision-making scores (3.9-fold; p<0.001) during PSMA-targeted resections. CONCLUSIONS: DROP-IN technology facilitates robotic radioguided surgery in SN and PSMA-targeted resections. However, a profound performance difference was observed in favour of SN-targeted resections. In particular, the SBR<2 as found mostly in PSMA-targeted resections directly converted to a decline in dexterity and decision-making. These findings might be related to limited previously experience in PSMA-targeted surgery. Source of Funding: This research was supported by an NWO-TTW-VICI grant (TTW 16141) and with hardware by Eurorad S.A. and Intuitive Inc. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e858 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Samaneh Azargoshasb More articles by this author Hilda A De Barros More articles by this author Daphne D.D. Rietbergen More articles by this author Paolo Dell'oglio More articles by this author Pim J Van Leeuwen More articles by this author Christian Wagner More articles by this author Tobias Maurer More articles by this author Henk G. Van der poel More articles by this author Matthias N. Van Oosterom More articles by this author Fijs W. B. Van Leeuwen More articles by this author Expand All Advertisement PDF downloadLoading ...