Three-dimensional (3D) visualization involves feature extraction and 3D reconstruction of CT images using a computer processing technology. It is a tool for displaying, describing, and interpreting 3D anatomy and morphological features of organs, thus providing intuitive, stereoscopic, and accurate methods for clinical decision-making. It has played an increasingly significant role in the diagnosis and management of liver diseases. Over the last decade, it has been proven safe and effective to use 3D simulation software for pre-hepatectomy assessment, virtual hepatectomy, and measurement of liver volumes in blood flow areas of the portal vein; meanwhile, the use of 3D models in combination with hydrodynamic analysis has become a novel non-invasive method for diagnosis and detection of portal hypertension. We herein describe the progress of research on 3D visualization, its workflow, current situation, challenges, opportunities, and its capacity to improve clinical decision-making, emphasizing its utility for patients with liver diseases. Current advances in modern imaging technologies have promised a further increase in diagnostic efficacy of liver diseases. For example, complex internal anatomy of the liver and detailed morphological features of liver lesions can be reflected from CT-based 3D models. A meta-analysis reported that the application of 3D visualization technology in the diagnosis and management of primary hepatocellular carcinoma has significant or extremely significant differences over the control group in terms of intraoperative blood loss, postoperative complications, recovery of postoperative liver function, operation time, hospitalization time, and tumor recurrence on short-term follow-up. However, the acquisition of high-quality CT images and the use of these images for 3D visualization processing lack a unified standard, quality control system, and homogeneity, which might hinder the evaluation of application efficacy in different clinical centers, causing enormous inconvenience to clinical practice and scientific research. Therefore, rigorous operating guidelines and quality control systems need to be established for 3D visualization of liver to develop it to become a mature technology. Herein, we provide recommendations for the research on diagnosis and management of 3D visualization in liver diseases to meet this urgent need in this research field.

The aim of this retrospective study was to compare the outcomes of operations based on 3-dimensional (3D) operation planning with non 3D-assisted operations in the treatment of centrally located hepatocellular carcinoma. From April 2008 to March 2014, 116 patients with centrally located hepatocellular carcinoma received surgical treatment in our department. Among these cases, a total of 60 patients received resection with operation planning based on 3D reconstructions (group A); the remaining 56 received treatment with the aid of traditional imaging (group B). Three-dimensional surgical planning, including the classification system for centrally located hepatocellular carcinoma, was elaborated in the study. Compared with group B, group A was linked to shorter operation time (294.5 ± 61.9 minutes vs 324.3 ± 83.1 minutes; p = 0.028) and lower rate of hepatic inflow occlusion (51.7% vs 71.4%; p = 0.029). No differences were found in surgical methods, intraoperative blood transfusion, and intraoperative blood loss. The groups were similar in their rates of complications, except that group B was more liable to have Clavien Grade III to V complications (3.3% vs 14.3%; p = 0.048). In addition, a significant difference in ascites was found across the 2 cohorts (2 in group A and 8 in group B; p = 0.048), and the 2 groups also differed significantly in total bilirubin (23.2 ± 16.1 g/L vs 31.1 ± 24.1 g/L; p = 0.032) and albumin (29.3 ± 5.2 g/L vs 27.8 ± 7.9 g/L; p = 0.033). Compared with non 3D-assisted operations, the operation planning based on 3D reconstruction is a more effective and reasonable method in the treatment of centrally located hepatocellular carcinoma. In addition, the classification system may facilitate the 3D operation planning.

Despite tremendous advances in traditional imaging technology over the past few decades, the intraoperative identification of lesions is still based on naked eye observation or pre-operative image evaluation. However, these two-dimensional image data cannot objectively reflect the complex anatomical structure of the liver and the detailed morphological features of the lesion, which directly limits the clinical application value of these imaging data in surgery in that it cannot improve the curative efficacy of surgery and the prognosis of the patient. This traditional mode of diagnosis and treatment has been changed by digital medical imaging technology in the new era with its significant function of accurate and efficient diagnosis of diseases, selection of reasonable treatment schemes, improvement of radical resection rate and reduction of surgical risk. In this paper, we reviewed the latest application of digital intelligent diagnosis and treatment technology related to liver surgery in the hope that it may help to achieve accurate treatment of liver surgery diseases.