A case series study of augmented reality in laparoscopic liver resection with a deformable preoperative model

Background: Previous work in augmented reality (AR) guidance in monocular laparoscopic hepatectomy requires the surgeon to manually overlay a rigid preoperative model onto a laparoscopy image. This may be fairly inaccurate because of significant liver deformation. We have proposed a technique which overlays a deformable preoperative model semi-automatically onto a laparoscopic image using a new software called Hepataug. The aim of this study is to show the feasibility of Hepataug to perform AR with a deformable model in laparoscopic hepatectomy.

Methods: We ran Hepataug during the procedures, as well as the usual means of laparoscopic ultrasonography (LUS) and visual inspection of the preoperative CT or MRI. The primary objective was to assess the feasibility of Hepataug, in terms of minimal disruption of the surgical workflow. The secondary objective was to assess the potential benefit of Hepataug, by subjective comparison with LUS.

Results: From July 2017 to March 2019, 17 consecutive patients were included in this study. AR was feasible in all procedures, with good correlation with LUS. However, for 2 patients, LUS did not reveal the location of the tumors. Hepataug gave a prediction of the tumor locations, which was confirmed and refined by careful inspection of the preoperative CT or MRI.

Conclusion: Hepataug showed a minimal disruption of the surgical workflow and can thus be feasibly used in real hepatectomy procedures. Thanks to its new mechanism of semi-automatic deformable alignment, Hepataug also showed a good agreement with LUS and visual CT or MRI inspection in subsurface tumor localization. Importantly, Hepataug yields reproducible results. It is easy to use and could be deployed in any existing operating room. Nevertheless, comparative prospective studies are needed to study its efficacy.