Accuracy of actual resected liver volume in anatomical liver resections guided by 3-dimensional parenchymal staining using fusion indocyanine green fluorescence imaging.

JOURNAL OF SURGICAL ONCOLOGY(2018)

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摘要
Background Methods The aim of this study was to assess the accuracy of actual resected liver volume (ARLV) in anatomical liver resections (ALRs) guided by 3-dimensional parenchymal staining using fusion indocyanine green fluorescence imaging (IGFI). Patients eligible for hepatic resection were enrolled in the current study from January 2016 to November 2017. All patients underwent surgery planning based on Medical Image Three-Dimensional Visualization System (MI-3DVS) before the operation, in which predicted resected liver volumes (PRLVs) were calculated. Under 3-dimensional guidance by fusion IGFI, ALRs were performed and ARLVs were measured. Simple linear regression, intra-class correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate the relationship and agreement between PRLV and ARLV. Results Conclusions Of the 27 patients who achieved valid demarcation by fusion IGFI, 12 (44.4%) received hemihepatectomy, while 10 (37.0%) and five (18.5%) underwent sectionectomy and segmentectomy, respectively. The relationship and agreement between PRLV (481.37 +/- 189.47 cm(3)) and ARLV (450.57 +/- 205.19 cm(3)) were then evaluated. The simple regression equation obtained was PRLV = 0.874 x ARLV + 87.75 (R = 0.946; P = 0.000). Meanwhile, ARLV (ICC = 0.943) achieved an excellent agreement with PRLV (P < 0.001); 25 of 27 dots were in the range of 95% confidence interval in Bland-Altman analysis. In the study, these findings validated the consistency between PRLV calculated by MI-3DVS and ARLV guided by fusion IGFI, which proved that IGFI can accurately guide anatomical hepatectomy. Generally, fusion IGFI can provide a valid, feasible and accurate demarcation line, which can confer precision to hepatic resection.
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关键词
3D,anatomical liver resections (ALRs),indocyanine green fluorescence imaging (IGFI)
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