Optimization Of Indocyanine Green Angiography For Colon Perfusion During Laparoscopic Colorectal Surgery

COLORECTAL DISEASE(2021)

引用 21|浏览4
暂无评分
摘要
Aim This study aims to evaluate the extrinsic effects of conditional factors affecting quantitative parameters and to establish the optimization of indocyanine green (ICG) angiography using in vitro experiments and a prospective observational study.Method In vitro experiments were performed to evaluate the correlation between conditional factors such as camera distance, surrounding lighting, fluorescence emission sources and ICG doses. The fluorescence intensity was measured from the ICG-containing test tube in each condition. In the clinical study, ICG angiography was applied to patients with colorectal cancer (n = 164). The quantitative perfusion parameters were the maximal fluorescence intensity (F-MAX), slope, T-1/2MAX and perfusion time ratio (TR). Camera position, distance to colon, fluorescence emission source, surrounding lighting, site of angiography and ICG specific mode were considered as conditional factors and compared with the quantitative parameters to identify the optimal condition of ICG angiography.Results The fluorescence intensity had an inverse correlation with distance, and the transitional zone was shown at a distance of 4-5 cm by slope differential. F-MAX, T-1/2MAX and slope were affected significantly by camera distance, site of angiography, fluorescence emission source and ICG mode as conditional factors. On multivariate analysis, F-MAX was independently associated with spectral ICG mode with red inversion, laser mode and camera distance. Conversely, TR was not related to any conditional factors.Conclusion Since quantitative parameters of ICG angiography are influenced by various conditions, a standardized protocol is required. The application of ICG specific modes with a constant distance of 4-5 cm can provide optimized fluorescence images.
更多
查看译文
关键词
colorectal surgery, fluorescein angiography, indocyanine green, laparoscopy, perfusion imaging
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要