Abstract
REAL-TIME MEASUREMENTS OF BIOMARKERS FOR GRAFT ASSESSMENT AND PATIENT MONITORING
Background:
Due to a global shortage of liver grafts, transplant surgeons increasingly resort to transplanting DCD (donated after circulatory death) organs. However, these organs are more susceptible to complications as a result of increased ischemic reperfusion injury. The worst of which is primary non-function, requiring an urgent re-transplantation. To date, there is no reliable metric to estimate the amount of reperfusion injury prior to transplantation. Clinical studies have demonstrated a correlation between flavin mononucleotide (FMN) in the perfusate of hypothermically perfused (HOPE) liver grafts and the risk of post-operative complications, related to mitochondrial damage. These findings indicate that FMN can be used as a biomarker for liver graft quality and motivate the need for robust real-time measurement of FMN.
Methods:
We developed a portable spectrofluorometric device, that can be used directly in the operating room during HOPE, which measures FMN concentration in the perfusate in real-time. Continuous FMN measurements were collected for 26 extended criteria DCD liver grafts prior to being transplanted or discarded.
Results:
Our real-time measurements show that FMN concentration in the perfusate not only indicates severe risk of complications, but also correlates with patient recovery after transplantation. Specifically, post-transplant transaminase expression and coagulation factor synthesis correlated with released FMN. This demonstrates how our technology can be used to assess DCD grafts prior to transplantation, mitigating the risk of non-anastomotic complications and primary non-function. The same approach can be used to also measure other biomarkers non-invasively in perfusate, or even dialysate of dialysis patients.
Conclusion:
Here, we show how liver specific biomarkers that previously were only used in research, could be successfully translated to clinical practice. Further, unprecedented continuous real-time data provides better data sets for research and improved patient diagnosis.