Indocyanine Green Fluorescence Imaging to Predict Graft Survival After Orthotopic Liver Transplantation: A Pilot Study. Issue 10 (29th July 2020) - Dousse, Damien; Vibert, Eric; Nicolas, Quentin; Terasawa, Muga; Cano, Luis; Allard, Marc‐Antoine; Salloum, Chady; Ciacio, Oriana; Pittau, Gabriella; Sa Cunha, Antonio; Cherqui, Daniel; Adam, René; et al.
Abstract : The incidence of primary nonfunction (PNF) after liver transplantation (LT) remains a major concern with the increasing use of marginal grafts. Indocyanine green (ICG) fluorescence is an imaging technique used in hepatobiliary surgery and LT. Because few early predictors are available, we aimed to quantify in real time the fluorescence of grafts during LT to predict 3‐month survival. After graft revascularization, ICG was intravenously injected, and then the fluorescence of the graft was captured with a near infrared camera and postoperatively quantified. A multiparametric modeling of the parenchymal fluorescence intensity (FI) curve was proposed, and a predictive model of graft survival was tested. Between July 2017 and May 2019, 76 LTs were performed, among which 6 recipients underwent retransplantation. No adverse effects of ICG injection were observed. The parameter a 150 (temporal course of FI) was significantly higher in the re‐LT group (0.022 seconds −1 (0.0011‐0.059) versus 0.012 seconds −1 (0.0001‐0.054); P  = 0.01). This parameter was the only independent predictive factor of graft survival at 3 months (OR,  2.4; 95% CI, 1.05‐5.50; P  = 0.04). The best cutoff for the parameter a 150 (0.0155 seconds −1 ) predicted the graft survival at 3 months with a sensitivity (Se) of 83.3% and a specificity (Spe) of 78.6% (area under the curve,  0.82; 95% CI, 0.67‐0.98; P  = 0.01). Quantitative assessment of intraoperative ICG fluorescence on the graft was feasible to predict graft survival at 3 months with a good Se and Spe. Further prospective studies should be undertaken to validate these results over larger cohorts and evaluate the clinical impact of this tool.