Non-invasive real-time assessment of hepatic macrovesicular steatosis in liver donors: Hypothesis, design and proof-of-concept study

Point-of-care device for the noninvasive assessment of hepatic macrosteatosis in liver donors

BACKGROUND

Quantification of macrosteatosis (MS) in the liver is important given that it has shown to directly correlate with adverse post-liver transplant (LT) outcomes. With advances in medical technology and an implicit understanding of pathology, noninvasive methods of quantitatively assessing MS are in various stages of development. Each of these methods is based on the physical principles of differences between a fat-laden hepatocyte and a normal one.

METHODS

In this regard, after a proof-of-concept study on a prototype for a simple, real-time, handheld device using the principle of diffuse reflectance spectroscopy, this study presents an upgraded point-of-care (POC) device for the noninvasive assessment of hepatic MS in liver donors.

RESULTS

The device was validated on cohort of donor livers and showed a sensitivity (0.0021 V/% fat) and highly correlated (r = 0.9868, P < .0001) with gold-standard liver biopsy. Results showed that this upgraded POC device provides a reliable method for the noninvasive assessment of hepatic MS, which is crucial for selecting suitable donor livers for LT.

CONCLUSION

The device has the potential to be an invaluable apparatus at the hands of the organ-retrieving surgeon. It is noninvasive, portable (handheld), and economic; provides real-time readings of the percentage of MS; and can be efficaciously handled by any member of the organ-retrieving team.

Machine Perfusion for Extended Criteria Donor Livers: What Challenges Remain?

Based on the renaissance of dynamic preservation techniques, extended criteria donor (ECD) livers reclaimed a valuable eligibility in the transplantable organ pool. Being more vulnerable to ischemia, ECD livers carry an increased risk of early allograft dysfunction, primary non-function and biliary complications and, hence, unveiled the limitations of static cold storage (SCS). There is growing evidence that dynamic preservation techniques—dissimilar to SCS—mitigate reperfusion injury by reconditioning organs prior transplantation and therefore represent a useful platform to assess viability. Yet, a debate is ongoing about the advantages and disadvantages of different perfusion strategies and their best possible applications for specific categories of marginal livers, including organs from donors after circulatory death (DCD) and brain death (DBD) with extended criteria, split livers and steatotic grafts. This review critically discusses the current clinical spectrum of livers from ECD donors together with the various challenges and posttransplant outcomes in the context of standard cold storage preservation. Based on this, the potential role of machine perfusion techniques is highlighted next. Finally, future perspectives focusing on how to achieve higher utilization rates of the available donor pool are highlighted.

Diffuse Reflectance Spectroscopy for The Assessment of Steatosis in Liver Phantom and Liver Donors - A Pilot Study

This paper reports the application of a low-cost diagnostic modality for fat analysis in a liver phantom as well as human liver donors. The device works on the principle of diffuse reflectance spectroscopy, which absorbs and/or scatters depending upon the molecules that compose a tissue. Here, we describe the development of liver phantom of varying fat concentration using saturated fat mimicking liver steatosis. Followed by a pilot study in the human liver donor setting. Later, handheld device based on Infrared-LED and Photodetector for real-time time assessment of live donor liver and fat assessment. Clinical Relevance- This device can be used in the development of an accurate and non-invasive for quantification of liver fat in the deceased donor selection process. It has an error margin of 10% in the quantification of fat which is comparable to a standard biopsy technique.

Risk factors and prediction of acute kidney injury after liver transplantation: Logistic regression and artificial neural network approaches

BACKGROUND

Acute kidney injury (AKI) has serious consequences on the prognosis of patients undergoing liver transplantation. Recently, artificial neural network (ANN) was reported to have better predictive ability than the classical logistic regression (LR) for this postoperative outcome.

AIM

To identify the risk factors of AKI after deceased-donor liver transplantation (DDLT) and compare the prediction performance of ANN with that of LR for this complication.

METHODS

Adult patients with no evidence of end-stage kidney dysfunction (KD) who underwent the first DDLT according to model for end-stage liver disease (MELD) score allocation system was evaluated. AKI was defined according to the International Club of Ascites criteria, and potential predictors of postoperative AKI were identified by LR. The prediction performance of both ANN and LR was tested.

RESULTS

The incidence of AKI was 60.6% (n = 88/145) and the following predictors were identified by LR: MELD score > 25 (odds ratio [OR] = 1.999), preoperative kidney dysfunction (OR = 1.279), extended criteria donors (OR = 1.191), intraoperative arterial hypotension (OR = 1.935), intraoperative massive blood transfusion (MBT) (OR = 1.830), and postoperative serum lactate (SL) (OR = 2.001). The area under the receiver-operating characteristic curve was best for ANN (0.81, 95% confidence interval [CI]: 0.75-0.83) than for LR (0.71, 95%CI: 0.67-0.76). The root-mean-square error and mean absolute error in the ANN model were 0.47 and 0.38, respectively.

CONCLUSION

The severity of liver disease, pre-existing kidney dysfunction, marginal grafts, hemodynamic instability, MBT, and SL are predictors of postoperative AKI, and ANN has better prediction performance than LR in this scenario.