Abstract
Facing an ongoing organ shortage in transplant medicine, strategies to increase the use of organs from marginal donors by objective organ assessment are being fostered. In this context, normothermic machine perfusion provides a platform for ex vivo organ evaluation during preservation. Consequently, analytical tools are emerging to determine organ quality. In this study, hyperspectral imaging (HSI) in the wavelength range of 550–995 nm was applied. Classification of 26 kidneys based on HSI was established using KidneyResNet, a convolutional neural network (CNN) based on the ResNet-18 architecture, to predict inulin clearance behavior. HSI preprocessing steps were implemented, including automated region of interest (ROI) selection, before executing the KidneyResNet algorithm. Training parameters and augmentation methods were investigated concerning their influence on the prediction. When classifying individual ROIs, the optimized KidneyResNet model achieved 84% and 62% accuracy in the validation and test set, respectively. With a majority decision on all ROIs of a kidney, the accuracy increased to 96% (validation set) and 100% (test set). These results demonstrate the feasibility of HSI in combination with KidneyResNet for non-invasive prediction of ex vivo kidney function. This knowledge of preoperative renal quality may support the organ acceptance decision.
Highlights
Publisher’s Note: MDPI stays neutralTerminal renal insufficiency is characterized by irreversible deterioration of kidney function
The only therapeutic option at this stage of the disease is renal replacement. This is possible with the help of dialysis procedures, but only a kidney transplant offers long-term improvement in quality of life and life expectancy [1]
The aim of this work is the functional classification of normothermic perfused kidneys based on hyperspectral imaging (HSI) data using convolutional neural network (CNN), by means of residual neural network (ResNet) architecture
Summary
Publisher’s Note: MDPI stays neutralTerminal renal insufficiency is characterized by irreversible deterioration of kidney function. The only therapeutic option at this stage of the disease is renal replacement. This is possible with the help of dialysis procedures, but only a kidney transplant offers long-term improvement in quality of life and life expectancy [1]. Several approaches have been proposed in the past to minimize the discrepancy between organ availability and demand. These include measures to improve the use of suboptimal donor organs by establishing appropriate criteria for accepting organs for transplantation [3,4,5]. The evaluation criteria proposed to date, based e.g., on histological markers or readily available donor characteristics, have limited predictive power for postoperative graft function [6,7]
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