Quantitative Assessment of Intraoperative Laser Fluorescence Angiography With Indocyanine Green Predicts Early Graft Function After Kidney Transplantation

Objective: This study was designed to demonstrate the predictive ability of quantitative indocyanine green (ICG) fluorescence angiography for the short-term postoperative outcome, the occurrence of delayed graft function (DGF), and long-term graft survival. Summary Background Data: DGF is a relevant problem after kidney transplantation; sufficient microperfusion of the allograft is crucial for postoperative organ function. Fluorescence angiography with ICG can serve as an intraoperative quality control of microperfusion. Methods: This prospective diagnostic study, conducted in 2 German transplantation centers from November 2015 to October 2018, included 128 consecutive kidney transplantations. Intraoperative assessment of the allograft microperfusion was performed by near-infrared fluorescence angiography with ICG; a software was used for quantitative analysis. The associations between perfusion parameters (eg, ICG Ingress) and donor, recipient, peri-procedural, and postoperative characteristics were evaluated. Results: DGF occurred in 23 (24%) kidney recipients from deceased donors. ICG Ingress ( P = 0.0027), donor age ( P = 0.0452), recipient age ( P = 0.0139), and recipient body mass index ( P = 0.0017) were associated with DGF. ICG Ingress correlated significantly with recipient age (r = −0.27662, P = 0.0016), cold and warm ischemia time (r = −0.25204, P = 0.0082; r = −0.19778, P = 0.0283), operating time (r = −0.32208, P = 0.0002), eGFR on postoperative days 1 (r =+0.22674, P = 0.0104) and 7 (r = +0.33189, P = 0.0001). The cutoff value for ICG Ingress was 106.23 AU with sensitivity of 78.3% and specificity of 80.8% ( P < 0.0001) for the prediction of DGF. Conclusion: Fluorescence angiography with ICG allows intraoperative quantitative assessment of microperfusion during kidney transplantation. The parameter ICG Ingress reflects recipient and procedure characteristics and is able to predict the incidence of DGF. Trial registration: Clinicaltrials.gov: NCT-02775838