Integration of three-dimensional liver models in a multimodal image-guided robotic liver surgery cockpit

Bijlstra, O.D.; Broersen, A.; Oosterveer, T.T.M.; Faber, R.A.; Achterberg, F.B.; Hurks, R.; Burgmans, M.C.; Dijkstra, J.; Mieog, J.S.D.; Vahrmeijer, A.L.; Swijnenburg, R.J.

doi:doi:10.3390/life12050667

Background: Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci (R) robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; Methods: in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted...Show moreBackground: Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci (R) robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; Methods: in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted questionnaire; Results: Implementation and applicability of the 3D model in the surgical cockpit was feasible in all patients and the quality of the 3D reconstructions was high in 14 (93%) of cases. Tumor diameters measured on CT and/or MR imaging were comparable to automated measurements using the segmentation software and 3D models; Conclusions: the 3D model was successfully incorporated in the robotic surgery console as part of a multimodality imaging platform and aided the surgeon in planning and guidance of the resection. Future studies should focus on further automation of 3D rendering and progress into augmented reality.Show less

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Integration of three-dimensional liver models in a multimodal image-guided robotic liver surgery cockpit