Augmented Reality Based Surgical Navigation of Complex Pelvic Osteotomies

Abstract

first_page loading... settings Open AccessArticle Augmented Reality Based Surgical Navigation of Complex Pelvic Osteotomies—A Feasibility Study on Cadavers by Joëlle Ackermann 1,2,† [ORCID] , Florentin Liebmann 1,2,*,† [ORCID] , Armando Hoch 3 [ORCID] , Jess G. Snedeker 2,3, Mazda Farshad 3, Stefan Rahm 3, Patrick O. Zingg 3 and Philipp Fürnstahl 1 1 Research in Orthopedic Computer Science, Balgrist University Hospital, University of Zurich, 8008 Zurich, Switzerland 2 Laboratory for Orthopaedic Biomechanics, ETH Zurich, 8093 Zurich, Switzerland 3 Department of Orthopedics, Balgrist University Hospital, University of Zurich, 8008 Zurich, Switzerland * Author to whom correspondence should be addressed. † These authors contributed equally to this work. Academic Editor: Jiro Tanaka Appl. Sci. 2021, 11(3), 1228; https://doi.org/10.3390/app11031228 Received: 20 December 2020 / Revised: 13 January 2021 / Accepted: 25 January 2021 / Published: 29 January 2021 (This article belongs to the Special Issue Artificial Intelligence (AI) and Virtual Reality (VR) in Biomechanics) Download PDF Browse Figures Citation Export Abstract Augmented reality (AR)-based surgical navigation may offer new possibilities for safe and accurate surgical execution of complex osteotomies. In this study we investigated the feasibility of navigating the periacetabular osteotomy of Ganz (PAO), known as one of the most complex orthopedic interventions, on two cadaveric pelves under realistic operating room conditions. Preoperative planning was conducted on computed tomography (CT)-reconstructed 3D models using an in-house developed software, which allowed creating cutting plane objects for planning of the osteotomies and reorientation of the acetabular fragment. An AR application was developed comprising point-based registration, motion compensation and guidance for osteotomies as well as fragment reorientation. Navigation accuracy was evaluated on CT-reconstructed 3D models, resulting in an error of 10.8 mm for osteotomy starting points and 5.4° for osteotomy directions. The reorientation errors were 6.7°, 7.0° and 0.9° for the x-, y- and z-axis, respectively. Average postoperative error of LCE angle was 4.5°. Our study demonstrated that the AR-based execution of complex osteotomies is feasible. Fragment realignment navigation needs further improvement, although it is more accurate than the state of the art in PAO surgery.