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Intelligent Imaging in Robotic-Assisted Liver Resection

Kevin M Sullivan, MD1, Kevin P Labadie, MD1, Kyle Miller, MD, MBA2, James O Park, MD1. 1University of Washington, 2Intuitive Surgical

Background: Current standards of care in the preoperative planning for liver resection includes two dimensional (2D) cross sectional multiphase, computed tomography (CT) or magnetic resonance (MR) imaging to determine the type of resection based on tumor size, number, and location, as well as accurate identification of hepatic vasculature and biliary structures. Three dimensional (3D) printing technology has been shown to improve the surgical trainees’ understanding of liver anatomy (1). Surgeons use ultrasound for intraoperative guidance, however, it is operator dependent, projects images in 2D, and requires a dedicated port and instrument during minimally invasive surgery. Augmented reality (AR) overlay of 3D reconstructions from 2D imaging have been successfully used in minimally invasive gynecologic and urologic surgery (2,3), but has not before been used in hepatobiliary applications.

Methods: A porcine model was used to determine feasibility of creating robotic overlays of the 3D reconstruction from digital imaging and communications in medicine (DICOM) data of 2D CT images. Following induction of general anesthesia, the porcine liver was accessed through a mini-laparotomy, and radiopaque cement was injected into several segments of the liver to model hepatic tumors. The incision was closed and CT images were acquired. The DICOM data from the CT images was used to create 3D reconstructions of the hepatic anatomy and tumors. The robot was docked and the 3D reconstruction was projected onto the console field of view.

Results: A 3D model of the major hepatic vasculature and the tumors was successfully generated using 2D DICOM data from CT images (Figure 1). These interactive reconstructions were useful in planning the robotic-assisted partial hepatectomy. Within the robotic console, 3D reconstructions of the tumors and the surrounding vasculature were successfully overlaid onto the liver (Figure 2) as confirmed by ultrasound. The vessels could be anticipated and avoided without the need for intraoperative ultrasonography.

Conclusions: 3D reconstructions were successfully created from the 2D CT images, and were useful in both preoperative planning as well as intraoperative console overlay during robotic resection.  Further steps for the application of AR to hepatobiliary surgery include improving technical challenges such as co-registration of the overlaid images with the mobile liver and improved resolution of small vessels. However, the technology appears promising in various fields including patient education, surgical trainee education, tumor board evaluations, preoperative planning, and intraoperative navigation.

References:

1. Marconi S, et al. Value of 3D printing for the comprehension of surgical anatomy. Surg Endosc. 2017 Oct;31(10):4102-4110.
2. Bourdel N, et al. Augmented reality in gynecologic surgery: evaluation of potential benefits for myomectomy in an experimental uterine model. Surg Endosc. 2017 Jan;31(1):456-461.
3. Chauvet P, et al. Augmented reality in a tumor resection model. Surg Endosc. 2018 Mar;32(3):1192-1201.


Presented at the SAGES 2017 Annual Meeting in Houston, TX.

Abstract ID: 98628

Program Number: ETP769

Presentation Session: Emerging Technology Poster Session (Non CME)

Presentation Type: Poster

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