Augmented reality technology for preoperative planning and intraoperative navigation during hepatobiliary surgery: A review of current methods - Tang, Rui; Ma, Long-Fei; Rong, Zhi-Xia; Li, Mo-Dan; Zeng, Jian-Ping; Wang, Xue-Dong; Liao, Hong-En; Dong, Jia-Hong (Hepatobiliary & pancreatic diseases international, 2018)
Augmented reality (AR) technology is used to reconstruct three-dimensional (3D) images of hepatic and biliary structures from computed tomography and magnetic resonance imaging data, and to superimpose the virtual images onto a view of the surgical field. In liver surgery, these superimposed virtual images help the surgeon to visualize intrahepatic structures and therefore, to operate precisely and to improve clinical outcomes. The keywords “augmented reality”, “liver”, “laparoscopic” and “hepatectomy” were used for searching publications in the PubMed database. The primary source of literatures was from peer-reviewed journals up to December 2016. Additional articles were identified by manual search of references found in the key articles. In general, AR technology mainly includes 3D reconstruction, display, registration as well as tracking techniques and has recently been adopted gradually for liver surgeries including laparoscopy and laparotomy with video-based AR assisted laparoscopic resection as the main technical application. By applying AR technology, blood vessels and tumor structures in the liver can be displayed during surgery, which permits precise navigation during complex surgical procedures. Liver transformation and registration errors during surgery were the main factors that limit the application of AR technology. With recent advances, AR technologies have the potential to improve hepatobiliary surgical procedures. However, additional clinical studies will be required to evaluate AR as a tool for reducing postoperative morbidity and mortality and for the improvement of long-term clinical outcomes. Future research is needed in the fusion of multiple imaging modalities, improving biomechanical liver modeling, and enhancing image data processing and tracking technologies to increase the accuracy of current AR methods.