Quantification of ICG fluorescence for the evaluation of intestinal perfusion: comparison between two software-based algorithms for quantification

Background: Indocyanine green fluorescence imaging (ICG-FI) can be used to evaluate intestinal perfusion prior to anastomosis. Several software for the quantification of fluorescence have emerged, but these have not previously been compared. The aim of this study was to compare the results from quantitative ICG-FI analysis of relative perfusion in an experimental setting using two different software-based quantification algorithms (FLER and Q-ICG). Methods: Twenty pigs received a laparotomy, and ischemic areas were created in three segments of the small intestine of each pig. For each ischemic area, fluorescence imaging was performed and the fluorescence recordings were quantitatively analyzed using FLER and Q-ICG. The quantitative analysis resulted in a set of perfusion lines for each software for either 30%, 60% or 100% relative perfusion. The perfusion lines were compared by registering the normalized slope for each set of perfusion lines, calculating the relative perfusion percentage in the FLER perfusion line according to Q-ICG, and measuring the length of the ischemic area for each analysis. Results: Fifty-four fluorescence recordings from 18 pigs were included. The ischemic segment for FLER was significantly longer in the 30% perfusion group and significantly shorter in the 100% perfusion group as compared to Q-ICG. The normalized slope for the FLER perfusion lines was significantly higher in the 30% perfusion group and significantly lower in the 100% perfusion group as compared to the Q-ICG perfusion lines. For the perfusion lines defined by FLER as 30%, 60%, and 100%, Q-ICG found 35.2% (p = 0.07), 63.7% (p = 0.31), and 84.1% perfusion (p = 0.003) respectively. Conclusion: The two software demonstrated significant differences in quantitative fluorescence analysis when perfusion was either very high or very low. The clinical relevance of these differences is unclear.