BACKGROUND: The purpose of this study was to determine the clinical value of three-dimensional (3D) computer reconstruction technology in pre-operative assessment and surgical planning for liver autotransplantation in patients with end-stage hepatic alveolar echinococcosis (HAE). STUDY DESIGN: Fifteen end-stage HAE patients received surgical treatment in our hospital between May 2011 and July 2014. 3D reconstruction and virtual surgeries were performed on diseased livers using a 3D reconstruction system for liver (IQQA-Liver). The feasibility and safety of liver autotransplantation were assessed for successful implementation of surgery. The results were compared with intraoperative conditions and computed tomography (CT) to verify the accuracy of pre-operative evaluation. RESULTS: Fifteen patients underwent liver resections and liver autotransplantation using surgical strategies consistent with pre-operative surgical planning in 3D reconstruction. Furthermore, there was no significant difference between whole-liver volume (2848.26 ± 798.41 vs. 2598.70 ± 822.45 cm(3), t = -4.635, P > 0.05) and lesion volume (1159.09 ± 789.47 vs. 1213.14 ± 813.76 cm(3), t = -1.959, P > 0.05) measured by 3D and traditional two-dimensional (2D) manual tracing from CT. The remaining liver volumes calculated by 3D and 2D CT were 810.47 ± 214.05 and 892.00 ± 262.36 cm(3) (t = -3.275, P > 0.05), with an average error rate of 6.2 and 16.5%, respectively. The pre-operative remaining liver volumes estimated by the two methods were positively correlated with the actual weight (783.67 ± 217.74 g) after the surgery (r three-dimensional = 0.976, r multislice CT = 0.883, P < 0.01). CONCLUSIONS: An individualized liver reconstruction technique can provide comprehensive anatomic information on livers of patients with end-stage HAE. Pre-operative virtual surgery can effectively improve the success rate of liver autotransplantation and reduce the risks of surgery.
BACKGROUND: The purpose of this study was to determine the clinical value of three-dimensional (3D) computer reconstruction technology in pre-operative assessment and surgical planning for liver autotransplantation in patients with end-stage hepatic alveolar echinococcosis (HAE). STUDY DESIGN: Fifteen end-stage HAE patients received surgical treatment in our hospital between May 2011 and July 2014. 3D reconstruction and virtual surgeries were performed on diseased livers using a 3D reconstruction system for liver (IQQA-Liver). The feasibility and safety of liver autotransplantation were assessed for successful implementation of surgery. The results were compared with intraoperative conditions and computed tomography (CT) to verify the accuracy of pre-operative evaluation. RESULTS: Fifteen patients underwent liver resections and liver autotransplantation using surgical strategies consistent with pre-operative surgical planning in 3D reconstruction. Furthermore, there was no significant difference between whole-liver volume (2848.26 ± 798.41 vs. 2598.70 ± 822.45 cm(3), t = -4.635, P > 0.05) and lesion volume (1159.09 ± 789.47 vs. 1213.14 ± 813.76 cm(3), t = -1.959, P > 0.05) measured by 3D and traditional two-dimensional (2D) manual tracing from CT. The remaining liver volumes calculated by 3D and 2D CT were 810.47 ± 214.05 and 892.00 ± 262.36 cm(3) (t = -3.275, P > 0.05), with an average error rate of 6.2 and 16.5%, respectively. The pre-operative remaining liver volumes estimated by the two methods were positively correlated with the actual weight (783.67 ± 217.74 g) after the surgery (r three-dimensional = 0.976, r multislice CT = 0.883, P < 0.01). CONCLUSIONS: An individualized liver reconstruction technique can provide comprehensive anatomic information on livers of patients with end-stage HAE. Pre-operative virtual surgery can effectively improve the success rate of liver autotransplantation and reduce the risks of surgery.
Authors: Maria Baimas-George; Kyle J Thompson; Michael D Watson; David A Iannitti; John B Martinie; Erin H Baker; David Levi; Dionisios Vrochides Journal: Langenbecks Arch Surg Date: 2021-02-16 Impact factor: 3.445
Authors: Yu Zhang; Eric C H Lai; Chong Yang; Hongji Yang; Jun Liu; Guo Zhou; Di Xian; Shaoping Deng; Wan Yee Lau Journal: Int J Surg Case Rep Date: 2020-03-28