ASO Author Reflections: Laparoscopic Anatomical Segment 8 Resection Using Digital Intelligent Liver Surgery Technologies: The Combination of Multiple Navigation Approaches

Overview

Journal Ann Surg Oncol

Publisher Springer

Specialty Oncology

Date 2023 Aug 23

PMID 37610492

Authors

Haisu Tao

Chihua Fang

Jian Yang

Affiliations

Soon will be listed here.

Citing Articles

A pilot study of virtual liver segment projection technology in subsegment-oriented laparoscopic anatomical liver resection when indocyanine green staining fails (with video).

Zeng X, Deng H, Dong Y, Hu H, Fang C, Xiang N Surg Endosc. 2024; 38(7):4057-4066.

PMID: 38806957 DOI: 10.1007/s00464-024-10912-w.

References

Abu Hilal M, Aldrighetti L, Dagher I, Edwin B, Troisi R, Alikhanov R . The Southampton Consensus Guidelines for Laparoscopic Liver Surgery: From Indication to Implementation. Ann Surg. 2017; 268(1):11-18. DOI: 10.1097/SLA.0000000000002524. View

Chieh A, Chan A, Rotellar F, Kim K . Laparoscopic major liver resections: Current standards. Int J Surg. 2020; 82S:169-177. DOI: 10.1016/j.ijsu.2020.06.051. View

Linn Y, Wu A, Han H, Liu R, Chen K, Fuks D . Systematic review and meta-analysis of difficulty scoring systems for laparoscopic and robotic liver resections. J Hepatobiliary Pancreat Sci. 2022; 30(1):36-59. DOI: 10.1002/jhbp.1211. View

Ban D, Tanabe M, Ito H, Otsuka Y, Nitta H, Abe Y . A novel difficulty scoring system for laparoscopic liver resection. J Hepatobiliary Pancreat Sci. 2014; 21(10):745-53. DOI: 10.1002/jhbp.166. View

Efanov M, Salimgereeva D, Alikhanov R, Wu A, Geller D, Cipriani F . Comparison between the difficulty of laparoscopic limited liver resections of tumors located in segment 7 versus segment 8: An international multicenter propensity-score matched study. J Hepatobiliary Pancreat Sci. 2022; 30(2):177-191. DOI: 10.1002/jhbp.1210. View

Li P, Wang M, Yang Y, Liu H, Pan Z, Jiang B . Preoperative three-dimensional versus two-dimensional evaluation in assessment of patients undergoing major liver resection for hepatocellular carcinoma: a propensity score matching study. Ann Transl Med. 2020; 8(5):182. PMC: 7154448. DOI: 10.21037/atm.2020.01.106. View

Hou J, Deng Z, Liu Y, Xu S, Li Z, Sun J . A Bibliometric Analysis of the Role of 3D Technology in Liver Cancer Resection. World J Surg. 2023; 47(6):1548-1561. DOI: 10.1007/s00268-023-06950-5. View

Fang C, An J, Bruno A, Cai X, Fan J, Fujimoto J . Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases. Hepatol Int. 2020; 14(4):437-453. PMC: 7366600. DOI: 10.1007/s12072-020-10052-y. View

Fang C, Tao H, Yang J, Fang Z, Cai W, Liu J . Impact of three-dimensional reconstruction technique in the operation planning of centrally located hepatocellular carcinoma. J Am Coll Surg. 2014; 220(1):28-37. DOI: 10.1016/j.jamcollsurg.2014.09.023. View

10.

Prevost G, Eigl B, Paolucci I, Rudolph T, Peterhans M, Weber S . Efficiency, Accuracy and Clinical Applicability of a New Image-Guided Surgery System in 3D Laparoscopic Liver Surgery. J Gastrointest Surg. 2019; 24(10):2251-2258. DOI: 10.1007/s11605-019-04395-7. View

11.

Zeng X, Zhu W, Lin W, Tian J, Yang J, Fang C . Laparoscopic Anatomical Extended Right Posterior Sectionectomy Using Virtual Liver Segment Projection Navigation and Indocyanine Green Fluorescence Imaging. Ann Surg Oncol. 2022; 30(1):375-376. DOI: 10.1245/s10434-022-12551-8. View

12.

Zhang P, Luo H, Zhu W, Yang J, Zeng N, Fan Y . Real-time navigation for laparoscopic hepatectomy using image fusion of preoperative 3D surgical plan and intraoperative indocyanine green fluorescence imaging. Surg Endosc. 2019; 34(8):3449-3459. DOI: 10.1007/s00464-019-07121-1. View

13.

Kitaguchi D, Takeshita N, Hasegawa H, Ito M . Artificial intelligence-based computer vision in surgery: Recent advances and future perspectives. Ann Gastroenterol Surg. 2022; 6(1):29-36. PMC: 8786689. DOI: 10.1002/ags3.12513. View

14.

Mascagni P, Vardazaryan A, Alapatt D, Urade T, Emre T, Fiorillo C . Artificial Intelligence for Surgical Safety: Automatic Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy Using Deep Learning. Ann Surg. 2020; 275(5):955-961. DOI: 10.1097/SLA.0000000000004351. View

15.

Madani A, Namazi B, Altieri M, Hashimoto D, Rivera A, Pucher P . Artificial Intelligence for Intraoperative Guidance: Using Semantic Segmentation to Identify Surgical Anatomy During Laparoscopic Cholecystectomy. Ann Surg. 2020; 276(2):363-369. PMC: 8186165. DOI: 10.1097/SLA.0000000000004594. View