Augmented reality technology for preoperative planning and intraoperative navigation during hepatobiliary surgery: A review of current methods

医学 增强现实 手术计划 腹腔镜检查 成像技术 影像引导手术 肝切除术 腹腔镜手术 放射科 磁共振成像 虚拟现实 模式 医学物理学 外科 人工智能 计算机科学 切除术 社会学 社会科学
作者
Rui Tang,Longfei Ma,Zhixia Rong,Mo Dan Li,Jianwei Zeng,Xuedong Wang,Hongen Liao,Jiahong Dong
出处
期刊:Hepatobiliary & Pancreatic Diseases International [Elsevier BV]
卷期号:17 (2): 101-112 被引量:87
标识
DOI:10.1016/j.hbpd.2018.02.002
摘要

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.
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