Towards cybernetic surgery: robotic and augmented reality-assisted liver segmentectomy
Augmented reality (AR) in surgery consists in the fusion of synthetic computer-generated images (3D virtual model) obtained from medical imaging preoperative workup and real-time patient images in order to visualize unapparent anatomical details. The 3D model could be used for a preoperative planning of the procedure. The potential of AR navigation as a tool to improve safety of the surgical dissection is outlined for robotic hepatectomy.
Materials and methods
Three patients underwent a fully robotic and AR-assisted hepatic segmentectomy. The 3D virtual anatomical model was obtained using a thoracoabdominal CT scan with a customary software (VR-RENDER®, IRCAD). The model was then processed using a VR-RENDER® plug-in application, the Virtual Surgical Planning (VSP®, IRCAD), to delineate surgical resection planes including the elective ligature of vascular structures. Deformations associated with pneumoperitoneum were also simulated. The virtual model was superimposed to the operative field. A computer scientist manually registered virtual and real images using a video mixer (MX 70; Panasonic, Secaucus, NJ) in real time.
Two totally robotic AR segmentectomy V and one segmentectomy VI were performed. AR allowed for the precise and safe recognition of all major vascular structures during the procedure. Total time required to obtain AR was 8 min (range 6–10 min). Each registration (alignment of the vascular anatomy) required a few seconds. Hepatic pedicle clamping was never performed. At the end of the procedure, the remnant liver was correctly vascularized. Resection margins were negative in all cases. The postoperative period was uneventful without perioperative transfusion.
AR is a valuable navigation tool which may enhance the ability to achieve safe surgical resection during robotic hepatectomy.
KeywordsAugmented reality Computer-assisted surgery Surgical margin Hepatectomy Robotic surgery Surgical planning
The authors are grateful to Anne Blandine Mackowski and Mourad Bouhadjar for the 3D reconstruction and to the IRCAD audiovisual team for their technical support. In addition, the authors would like to thank Christopher Burel and Guy Temporal for their valuable assistance in proofreading the manuscript.
This work is part of the eHealth project PASSPORT funded by the ICT program of the European Community as part of the 7th Framework Program.
Conflicts of interest
The authors have no conflicts of interest or financial ties to disclose.
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