Current Status and Prospects of Three-dimensional Visualization in Precision Liver Resection
Year: 2025
Type: article
Abstract: Three-dimensional (3D) reconstruction technology, as a vital component of digital medicine, has emerged as a powerful tool in the field of hepatic surgery, particularly in the context of precision liver resection. This review examines the current applications and future prospects of 3D reconstruction technology in hepatic surgery, with a focus on its clinical progress in preoperative assessment, vascular protection, surgical planning, and intraoperative navigation. By accurately calculating liver volume, evaluating liver function reserves, and optimizing surgical strategies, 3D reconstruction significantly enhances the safety and efficacy of liver resection. In terms of vascular protection, 3D reconstruction enables precise localization of tumors relative to vascular structures and identification of vascular variations, thereby reducing intraoperative bleeding risks. For surgical planning, the integration of 3D reconstruction with virtual reality (VR) and augmented reality (AR) technologies allows for the creation of virtual surgical scenarios, optimization of surgical pathways, and reduction of operative time. In intraoperative navigation, 3D reconstruction combined with laparoscopic ultrasound, indocyanine green (ICG) fluorescence imaging, 3D printing, and mixed reality (MR) technologies has enabled real-time navigation, thereby improving surgical precision. Despite these advancements, 3D reconstruction technology still faces challenges, including high costs, time-consuming processes, data quality limitations, and suboptimal reconstruction of intrahepatic bile ducts. Looking ahead, the incorporation of artificial intelligence and big data into 3D reconstruction is expected to further refine preoperative planning and intraoperative navigation, driving the field of hepatic surgery toward greater intelligence and precision.
Source: Clinical Medicine Frontiers
Authors: Mengna Zhang, Zhiqi Dai, Yini Xu, Jinghui Zhang, Jun Yu
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4408840899