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.

The preservation of kidneys using normothermic machine perfusion (NMP) prior to transplantation has the potential for predictive evaluation of organ quality. Investigations concerning the quantitative assessment of physiological tissue parameters and their dependence on organ function lack in this context. In this study, hyperspectral imaging (HSI) in the wavelength range of 500–995 nm was conducted for the determination of tissue water content (TWC) in kidneys. The quantitative relationship between spectral data and the reference TWC values was established by partial least squares regression (PLSR). Different preprocessing methods were applied to investigate their influence on predicting the TWC of kidneys. In the full wavelength range, the best models for absorbance and reflectance spectra provided R_p² values of 0.968 and 0.963, as well as root-mean-square error of prediction (RMSEP) values of 2.016 and 2.155, respectively. Considering an optimal wavelength range (800–980 nm), the best model based on reflectance spectra (R_p² value of 0.941, RMSEP value of 3.202). Finally, the visualization of TWC distribution in all pixels of kidneys’ HSI image was implemented. The results show the feasibility of HSI for a non-invasively and accurate TWC prediction in kidneys, which could be used in the future to assess the quality of kidneys during the preservation period.

To identify potentially transplantable organs in a pool of marginal kidneys, 33 porcine slaughterhouse kidneys were perfused for 4 h with whole blood. During the normothermic perfusion, plasma, urine, and tissue samples were taken. Several biomarkers for tubule injury, endothelial activation, and inflammatory response were evaluated for a potential correlation with macroscopic appearance, histology, and filtration activity. Generally, biomarker levels increased during perfusion. TLR-4, EDN-1, and NGAL were not associated with any classification. In contrast, a steeper increase in NAG and IL-6 in plasma correlated with a poor macroscopic appearance at 4 h, indicating a higher inflammatory response in the kidneys with worse macroscopy early on, potentially due to more damage at the tubules. Although long-term effects on the graft could not be assessed in this setting, early observation under machine perfusion with whole blood was feasible. It allowed the assessment of kidneys under conditions comparable to reperfusion. This setting could give surgeons further insight into the quality of marginal kidneys and an opportunity to pre-treat them.

Zusammenfassung Normotherme ex-vivo Nierenperfusion ist eine vielversprechende Technik zur Erhaltung und Bewertung der Vitalität und Viabilität von Organen. Die automatisierte Mehrgrößenregelung des Prozesses erhöht die Betriebssicherheit und erleichtert die Bedienung. Für die beteiligte Regelung von arteriellem Sauerstoff- und Kohlendioxidpartialdruck sind in dieser Arbeit zwei Regelungsstrategien anwendungsorientiert umgesetzt und in Simulationen, sowie im echten Prozess validiert worden. Die Ergebnisse wurden im Kontext bekannter Regelungsstrategien diskutiert.

Zusammenfassung Normotherme ex-vivo Nierenperfusion ist eine vielversprechende Technik zur Erhaltung und Bewertung der Vitalität und Viabilität von Organen. In diesem Beitrag wird eine qualitative Prozessanalyse durchgeführt und nierenspezifische Funktionalitäten werden aufgezeigt. Zusätzlich wird eine Methode vorgestellt, die Autoregulation einer isolierten ex-vivo perfundierten Niere automatisiert zu charakterisieren.