Global practice patterns of preoperative image reconstruction for liver surgery.

BACKGROUND: Three-dimensional (3-D) liver modeling is used globally; however, its actual practice is limited to a few centers. This study aimed to assess practice patterns and barriers to the use of 3-D modeling among liver surgeons worldwide. METHODS: A survey approved by the International Hepato-Pancreato-Biliary Association research council consisting of 27 questions was conducted using an online questionnaire. Incomplete responses were excluded. RESULTS: Of 235 respondents from 46 countries, 81.3% reported experience with 3-D modeling; however, only 21% used it in > 75% of cases. Surgeons using 3-D reconstruction were older (P = .025), worked more frequently at academic facilities (P = .007), and had more years of experience (P = .001), especially in minimally invasive liver surgery (MILS) (P = .038). In addition, 3-D rendering was performed by surgeons in 50.8% of cases. Liver volumetry was the most frequent indication (80.1%), and decreased postoperative complications were the main perceived benefit (53.6%). CONCLUSIONS: More experience in liver surgery because of seniority, case volume, and openness to novel technology (MILS) is associated with a greater appreciation for the value of 3-D modeling. Our results suggest the need for senior surgeons to help early-career surgeons consider 3-D modeling for the reported benefit of reduced intra- and postoperative complications.

Two-step artificial intelligence algorithm for liver segmentation automates anatomic virtual hepatectomy.

BACKGROUND: Anatomic virtual hepatectomy with precise liver segmentation for hemilivers, sectors, or Couinaud's segments using conventional three-dimensional simulation is not automated and artificial intelligence (AI)-based algorithms have not yet been applied. METHODS: Computed tomography data of 174 living-donor candidates for liver transplantation (training data) were used for developing a new two-step AI algorithm to automate liver segmentation that was validated in another 51 donors (validation data). The Pure-AI (no human intervention) and ground truth (GT, full human intervention) data groups were compared. RESULTS: In the Pure-AI group, the median Dice coefficients of the right and left hemilivers were highly similar, 0.95 and 0.92, respectively; sectors, posterior to lateral: 0.86-0.92, and Couinaud's segments 1-8: 0.71-0.89. Labeling of the first-order branch as hemiliver, right or left portal vein perfectly matched; 92.8% of the second-order (sectors); 91.6% of third-order (segments) matched between the Pure-AI and GT data. CONCLUSIONS: The two-step AI algorithm for liver segmentation automates anatomic virtual hepatectomy. The AI-based algorithm correctly divided all hemilivers, and more than 90% of the sectors and segments.

Real-time navigation for laparoscopic hepatectomy using image fusion of preoperative 3D surgical plan and intraoperative indocyanine green fluorescence imaging.

BACKGROUND: Understanding the internal anatomy of the liver remains a major challenge in anatomical liver resection. Although virtual hepatectomy and indocyanine green (ICG) fluorescence imaging techniques have been widely used in hepatobiliary surgery, limitations in their application for real-time navigation persist. OBJECTIVE: The aim of the present study was to evaluate the feasibility and clinical utility of the novel laparoscopic hepatectomy navigation system (LHNS), which fuses preoperative three-dimensional (3D) models with ICG fluorescence imaging to achieve real-time surgical navigation. METHODS: We conducted a retrospective review of clinical outcome for 64 patients who underwent laparoscopic hepatectomy from January 2018 to December 2018, including 30 patients who underwent the procedure using the LHNS (LHNS group) and 34 patients who underwent the procedure without LHNS guidance (Non-LHNS group). RESULTS: There was no significant difference in preoperative characteristics between the two groups. The LHNS group had a significantly less blood loss (285.0 ± 163.0 mL vs. 391.1 ± 242.0 mL; P = 0.047), less intraoperative blood transfusion rate (13.3% vs. 38.2%; P = 0.045), and shorter postoperative hospital stay (7.8 ± 2.1 days vs. 10.6 ± 3.8 days; P < 0.001) than the Non-LHNS group. There was no statistical difference in operative time and the overall complication rate between the two groups. The liver transection line was clearly delineated by the LHNS in 27 patients; however, the projection of boundary was unclear in 2 cases, and in 1 case, the boundary was not clearly displayed by ICG fluorescence imaging. CONCLUSIONS: We developed the LHNS to address limitations of current intraoperative imaging systems. The LHNS is hopefully to become a promising real-time navigation system for laparoscopic hepatectomy.

Practical Contribution of Virtual Hepatectomy for Colorectal Liver Metastases: a Propensity-Matched Analysis of Clinical Outcome.

BACKGROUND: Recent improvements in imaging technologies have enabled surgeons to perform precise planning using virtual hepatectomy (VH). However, the practical and clinical benefits of VH remain unclear. This study sought to assess how three-dimensional analysis using a VH contributed to preoperative planning and postoperative outcome in patients undergoing liver surgery for the treatment of colorectal liver metastases (CRLM). METHODS: From 2007 to 2017, a total of 473 CRLM patients who received curative hepatectomy were retrospectively assessed. A 1:1 matched propensity analysis was performed between patients who did not receive a VH (without 3D group: n = 188) and received a VH (3D(+) group: n = 285). RESULT: The rate of VH increased over the study period (P < 0.001). After propensity score matching (n = 150 for each group), no significant differences were observed in the intraoperative and postoperative outcome, including liver transection time, blood loss, or morbidity between the groups. More patients received a small anatomical resection (plus limited resections) in the 3D(+) group (25 vs 11%, [P = 0.03]). A submillimeter margin was less frequent in the 3D(+) group. No significant differences in the 5-year overall survival and disease-free survival rates were seen between the without 3D group and the 3D(+) group (38.0 vs. 45.9% [P = 0.99], 11.1 vs. 21.7%, respectively [P = 0.109]). CONCLUSION: Although VH did not significantly influenced on the long-term outcome after hepatectomy, a more parenchymal-sparing operative procedure (anatomical resections, plus limited resections) was selected and the risk of a submillimeter surgical margin was reduced after introduction of VH.

Parenchyma-preserving hepatectomy based on portal ramification and perfusion of the right anterior section: preserving the ventral or dorsal area.

BACKGROUND: Anatomical hepatectomy aims to eliminate the spread of malignant tumor cells via portal vein systemically. An anatomical concept of the right anterior section (RAS) and preservation of the liver parenchyma within the RAS has been proposed. METHODS: We focused on the anatomical concept of the RAS based on portal perfusion and described surgical procedures to preserve the ventral or dorsal RAS using preoperative simulation. RESULTS: In 370 patients undergoing a preoperative simulation, the ramification of the tertiary portal branches of the RAS could be divided into three types including the cranio-caudal type; Couinaud's classification in 50% of patients, ventro-dorsal type in 26% of patients, and multiple type in 24% of patients. Then in 32 patients of the ventro-dorsal type, curative parenchyma-sparing hepatectomy of the RAS was performed, preserving the ventral and dorsal RAS in 14 and 18 patients, respectively. There were no differences in the postoperative complications and long-term survival compared with the results obtained after segment 5 or 8 resection (n = 33). CONCLUSION: Three-dimensional simulation revealed three types of portal vein ramification of the RAS. Parenchyma-preserving hepatectomy based on the precise portal ramification may contribute to safe and curative hepatectomy in selected cases with liver neoplasm involving the RAS.

Novel 3-dimensional virtual hepatectomy simulation combined with real-time deformation.

AIM: To develop a novel 3-dimensional (3D) virtual hepatectomy simulation software, Liversim, to visualize the real-time deformation of the liver. METHODS: We developed a novel real-time virtual hepatectomy simulation software program called Liversim. The software provides 4 basic functions: viewing 3D models from arbitrary directions, changing the colors and opacities of the models, deforming the models based on user interaction, and incising the liver parenchyma and intrahepatic vessels based on user operations. From April 2010 through 2013, 99 patients underwent virtual hepatectomies that used the conventional software program SYNAPSE VINCENT preoperatively. Between April 2012 and October 2013, 11 patients received virtual hepatectomies using the novel software program Liversim; these hepatectomies were performed both preoperatively and at the same that the actual hepatectomy was performed in an operating room. The perioperative outcomes were analyzed between the patients for whom SYNAPSE VINCENT was used and those for whom Liversim was used. Furthermore, medical students and surgical residents were asked to complete questionnaires regarding the new software. RESULTS: There were no obvious discrepancies (i.e., the emergence of branches in the portal vein or hepatic vein or the depth and direction of the resection line) between our simulation and the actual surgery during the resection process. The median operating time was 304 min (range, 110 to 846) in the VINCENT group and 397 min (range, 232 to 497) in the Liversim group (P = 0.30). The median amount of intraoperative bleeding was 510 mL (range, 18 to 5120) in the VINCENT group and 470 mL (range, 130 to 1600) in the Liversim group (P = 0.44). The median postoperative stay was 12 d (range, 6 to 100) in the VINCENT group and 13 d (range, 9 to 21) in the Liversim group (P = 0.36). There were no significant differences in the preoperative outcomes between the two groups. Liversim was not found to be clinically inferior to SYNAPSE VINCENT. Both students and surgical residents reported that the Liversim image was almost the same as the actual hepatectomy. CONCLUSION: Virtual hepatectomy with real-time deformation of the liver using Liversim is useful for the safe performance of hepatectomies and for surgical education.