The Current Status and Challenges in Augmented-Reality Navigation System for Robot-Assisted Laparoscopic Partial Nephrectomy

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Abstract

Robot-assisted surgeries have enabled surgeons to perform complex procedures more precisely and easily as compared with the conventional laparoscopic surgery. These new technologies have expanded the indications of the nephron-sparing surgery to cases that are anatomically more complicated. One of the challenging cases is that of the completely endophytic tumors because surgeons do not have any visual clues about tumor location on the kidney surface. In addition, these tumors pose technical challenges for their localization and resection, thereby likely increasing the possibility of perioperative complications. Since April 2014, we have been developing a visual support system for performing robot-assisted laparoscopic partial nephrectomy (RAPN) using the augmented-reality (AR) technology. The AR-based navigation system for RAPN can help identify the vasculature structure and tumor location easily and objectively. Moreover, image registration and organ tracking are critical to improving the accuracy of the system. Notably, tissue deformation, manual adjustment, and depth perception are the key elements for achieving precise image registration. Thus, console surgeons must effectively understand the properties and weak points of the AR navigation system and, accordingly, manipulate the laparoscopic camera and robot forceps to facilitate image registration and organ tracking. The cooperation of the console surgeon can result in a better collaboration between the real-time operation image and three-dimensional computer graphics models in the navigation system. We expect our system will offer significant benefits to both surgeons and patients.

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Hamada, A., Sawada, A., Kono, J., Koeda, M., Onishi, K., Kobayashi, T., … Ogawa, O. (2020). The Current Status and Challenges in Augmented-Reality Navigation System for Robot-Assisted Laparoscopic Partial Nephrectomy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12182 LNCS, pp. 620–629). Springer. https://doi.org/10.1007/978-3-030-49062-1_42

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