**7.1. Near-infrared fluorescent imaging in hepatic surgery**

New technologies continue to be developed to enhance minimally invasive liver surgery. One example is intra-operative near-infrared fluorescence (NIF) imaging. NIF imaging has become commonplace in many laparoscopic and robotic camera systems enabling the identification of various dyes, such as indocyanine green, injected preoperatively. Indocyanine green is a green dye that is preferentially metabolized by hepatocytes and excreted in the biliary tree. It lights up the biliary tree and has been utilized for robotic and laparoscopic assisted cholecystectomy. It has been more recently utilized to guide parenchymal dissection after vascular control by identifying perfused from poorly perfused hepatic parenchyma.

### **7.2. Intelligent imaging in robotic-assisted surgery**

Future directions within the realm of robotic liver surgery include the application of preoperative planning with virtual reality (VR) models and real-time augmented reality (AR) intraoperative endoscopic overlays to aid with surgical navigation on *da Vinci* ® surgical systems. The current practice standard for operative planning involves preoperative cross-sectional imaging using contrast-enhanced, multiphase liver protocol computed tomography (CT) or magnetic resonance imaging (MRI) scans to evaluate the tumor's extent (size and number) and location with respect to critical structures including the major vasculature and biliary architecture. Surgeons rely on years of training to develop the ability to mentally reconstruct 2D images into a mental 3D model in order to preoperatively plan for a surgery while referencing the 2D images intraoperatively.

Computer-based three-dimensional (3D) reconstructions of liver tumors have been shown to increase accuracy of tumor localization and precision of operative planning for liver surgery [46]. While useful for operative planning, intraoperative review of 2D images on a traditional PACS system requires diversion of attention away from the operative field. Intraoperative ultrasound is routinely used for real-time localization of liver tumors and

identification of vessels and biliary structures. However, its use is limited in minimally invasive liver surgery due to the need for an additional port site and the need to interpret the 2D ultrasound images and mentally reconstruct the 3D anatomy being projected based on the orientation of the ultrasound probe. Preoperative planning with a VR model (**Figure 6**) and the application of AR endoscopic overlay (**Figure 7**) of patient-specific anatomy into the robotic surgical system could potentially improve surgical efficiency in real-time with

**Figure 7.** Real-time endoscopic overlay of 3D reconstruction over the surgical field on the *da Vinci* ® Xi Surgical System. The relationship between the tumor (light pink) and adjacent vasculature including the hepatic veins (light blue), hepatic arteries (red) and portal veins (blue) is present on the overlay. After initial registration, the overlay is mapped onto the

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AR may be developed to overlay accurate 3D reconstruction data onto the operative field itself, thereby eliminating the need to divert the attention from the operative field and to translate the 2D images into a 3D construct. These advancements with planning and guidance can potentially reduce the cognitive load burden on the surgeon. Augmented reality for spatial recognition has been shown to improve localization accuracy in an experimental model of uterine myomectomy [47],and our recent experience has shown promise and feasibility in an experimental porcine liver model (**Figures 1** and **2**). Next steps in the application of VR and AR to hepatobiliary surgery include overcoming technical obstacles of continuous coregistration to a mobile liver with tissue deformation while continuing to define the utility of the technology with patient education, tumor board evaluations, preoperative planning and

intelligent surgical navigation.

patient-specific anatomy changing in real-time with camera movement.

intraoperative navigation.

**Figure 6.** Virtual 3D model of the liver. Porcine experimental model with implanted radiopaque tumor within the liver parenchyma. Preoperatively, CT images were obtained of the porcine liver with 3D segmented reconstructions created from the DICOM images. The 3D reconstructions can be viewed for preoperative planning with intuitive Surgical's *da Vinci*® Surgical System.

**7.2. Intelligent imaging in robotic-assisted surgery**

70 Liver Cancer

encing the 2D images intraoperatively.

*Vinci*® Surgical System.

Future directions within the realm of robotic liver surgery include the application of preoperative planning with virtual reality (VR) models and real-time augmented reality (AR) intraoperative endoscopic overlays to aid with surgical navigation on *da Vinci* ® surgical systems. The current practice standard for operative planning involves preoperative cross-sectional imaging using contrast-enhanced, multiphase liver protocol computed tomography (CT) or magnetic resonance imaging (MRI) scans to evaluate the tumor's extent (size and number) and location with respect to critical structures including the major vasculature and biliary architecture. Surgeons rely on years of training to develop the ability to mentally reconstruct 2D images into a mental 3D model in order to preoperatively plan for a surgery while refer-

Computer-based three-dimensional (3D) reconstructions of liver tumors have been shown to increase accuracy of tumor localization and precision of operative planning for liver surgery [46]. While useful for operative planning, intraoperative review of 2D images on a traditional PACS system requires diversion of attention away from the operative field. Intraoperative ultrasound is routinely used for real-time localization of liver tumors and

**Figure 6.** Virtual 3D model of the liver. Porcine experimental model with implanted radiopaque tumor within the liver parenchyma. Preoperatively, CT images were obtained of the porcine liver with 3D segmented reconstructions created from the DICOM images. The 3D reconstructions can be viewed for preoperative planning with intuitive Surgical's *da*  **Figure 7.** Real-time endoscopic overlay of 3D reconstruction over the surgical field on the *da Vinci* ® Xi Surgical System. The relationship between the tumor (light pink) and adjacent vasculature including the hepatic veins (light blue), hepatic arteries (red) and portal veins (blue) is present on the overlay. After initial registration, the overlay is mapped onto the patient-specific anatomy changing in real-time with camera movement.

identification of vessels and biliary structures. However, its use is limited in minimally invasive liver surgery due to the need for an additional port site and the need to interpret the 2D ultrasound images and mentally reconstruct the 3D anatomy being projected based on the orientation of the ultrasound probe. Preoperative planning with a VR model (**Figure 6**) and the application of AR endoscopic overlay (**Figure 7**) of patient-specific anatomy into the robotic surgical system could potentially improve surgical efficiency in real-time with intelligent surgical navigation.

AR may be developed to overlay accurate 3D reconstruction data onto the operative field itself, thereby eliminating the need to divert the attention from the operative field and to translate the 2D images into a 3D construct. These advancements with planning and guidance can potentially reduce the cognitive load burden on the surgeon. Augmented reality for spatial recognition has been shown to improve localization accuracy in an experimental model of uterine myomectomy [47],and our recent experience has shown promise and feasibility in an experimental porcine liver model (**Figures 1** and **2**). Next steps in the application of VR and AR to hepatobiliary surgery include overcoming technical obstacles of continuous coregistration to a mobile liver with tissue deformation while continuing to define the utility of the technology with patient education, tumor board evaluations, preoperative planning and intraoperative navigation.
