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Fluorescent image-based evaluation of gastric conduit perfusion in a preclinical ischemia model.

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Background This study evaluated near-infrared (NIR) fluorescent images to assess gastric conduit perfusion after an esophagectomy in a porcine model of gastric conduit ischemia. The time necessary to acquire a… Click to show full abstract

Background This study evaluated near-infrared (NIR) fluorescent images to assess gastric conduit perfusion after an esophagectomy in a porcine model of gastric conduit ischemia. The time necessary to acquire a sufficient fluorescent signal to confirm ischemia in the gastric conduit after peripheral or central venous injection of indocyanine green (ICG) was also investigated. Methods A reversible gastric conduit ischemic pig model was established through ligation and release of the right gastroepiploic artery (RGEA, n=10). The esophageal reconstruction was performed to create an esophagogastric anastomosis. After ligation of the RGEA, ICG was injected into an ear vein (n=6) or the inferior vena cava (n=4). Under fluorescent imaging system guidance, the fluorescent signal-to-background ratio (SBR) in the gastric conduit or esophagus was measured during the entire procedure. We estimated the time necessary to acquire fluorescent signals in the gastric conduit using two different injection routes. Results When the RGEA was ligated, the SBR in the esophagus was significantly higher than that in the gastric conduit (P=0.02), and the SBR in the gastric conduit recovered within 180 s after release of the ligation. The time to acquire a fluorescent signal was faster with a central route than with a peripheral route (P=0.04). Conclusions We successfully created an ischemic animal model of the gastric conduit. Using this animal model, we evaluated the sensitivity and applicability of the fluorescent imaging system for observation and identification of ischemic areas during an esophagectomy.

Keywords: fluorescent; conduit; model; conduit perfusion; gastric conduit; ischemia

Journal Title: Journal of thoracic disease
Year Published: 2018

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