Evidence map›Paper›PMID 38806957›Full record

ArticleSurgical endoscopy2024

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

Xiaojun Zeng, Haowen Deng, Yanchen Dong, Haoyu Hu, Chihua Fang, Nan Xiang

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Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Xiaojun Zeng *Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Haowen Deng *Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Yanchen Dong *School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, 510515, China.
Haoyu HuDepartment of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Chihua FangDepartment of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China. fangchihua@smu.edu.cn.
Nan XiangDepartment of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China. zjyyxn@126.com.ORCID 0000-0002-0506-9889

Funding

the Clinical Research Startup Program of Southern Medical University CX2017N010/C1034360the National Natural Science Foundation of China Mathematics Tianyuan Foundation 12026602the Natural Science Foundation of Guangdong Province, China 2022A1515010176
6 · The paper itself

Abstract

backgroundPrecision surgery for liver tumors favors laparoscopic anatomical liver resection (LALR), involving the removal of specific liver segments or subsegments. Indocyanine green (ICG)-negative staining is a commonly used method for defining resection boundaries but may be prone to failure. The challenge arises when ICG staining fails, as it cannot be repeated during surgery. In this study, we employed the virtual liver segment projection (VLSP) technology as a salvage approach for precise boundary determination. Our aim was to assess the feasibility of the VLSP to be used for the determination of the boundaries of the liver resection in this situation.

methodsBetween January 2021 and June 2023, 12 consecutive patients undergoing subsegment-oriented LALR were included in this pilot series. The VLSP technology was utilized to define the resection boundaries at the time of ICG-negative staining failure. Routine surgical parameters and short-term outcomes were evaluated to assess the safety of VLSP in this procedure. In addition, its feasibility was assessed by analyzing the accuracy between the predicted resected liver volume (PRLV) and actual resected liver volume (ARLV).

resultsOf the 12 enrolled patients, the mean operation time was 444.58 ± 101.70 min (range 290-570 min), with a mean blood loss of 125.00 ± 96.53 ml (range 50-400 mL). One patient (8.3%) was converted to laparotomy for subsequent parenchymal transection, four (33.3%) received blood transfusions and four (33.3%) had postoperative complications. All patients received an R0 resection. The Pearson correlation coefficient (r) between PRLV and ARLV was 0.98 (R

conclusionFailure of intraoperative ICG-negative staining during subsegment-oriented LALR is possible, and VLSP may be an alternative to define the resection boundaries in such cases.

Indexed as

Coloring AgentsFeasibility StudiesHepatectomyIndocyanine GreenLaparoscopyLiver NeoplasmsAgedFemaleHumansLiverMaleMiddle AgedOperative TimePilot ProjectsStaining and LabelingSurgery, Computer-AssistedColoring AgentsIndocyanine GreenAnatomical liver resectionAugmented reality navigationICG fluorescence imagingSubsegmentectomyVirtual liver segment projection

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.