Normothermic machine perfusion (NMP) offers a unique opportunity to objectively assess donor organ quality. This study describes the evaluation of inulin clearance as a potential marker for the ex vivo function of porcine kidneys during NMP. The function assessment was performed in both kidneys from slaughterhouse pigs (n = 20) and kidneys from pigs in a laboratory setting (n = 28). The kidneys were exposed to different warm ischemia times (WIT). After a period of static cold storage, the kidneys underwent a 4-hour NMP with autologous whole blood. Inulin clearance, hemodynamic parameters, and urine output were measured. Based on the inulin excretion behavior laboratory pig kidneys were assigned to three classes (functional, limited functional, and nonfunctional), slaughterhouse pig kidneys to two classes (limited functional and nonfunctional), respectively. Contrary to the marginal kidneys of the slaughterhouse pigs, the functional variation of kidneys of the laboratory pigs was associated with the WIT. A correlation between functional kidneys and a WIT less than 25 min was shown. Because none of the slaughterhouse pig kidneys could be assigned to the functional class, only the laboratory pig kidneys were used for examinations with functional markers. Renal blood flow and urine output during NMP correlated significantly (p < 0.01) with ex vivo kidney function. This study demonstrated that inulin is a marker of high quality for the evaluation of suggested kidney function after NMP with whole blood. Furthermore, surrogate markers measured during NMP can be used to describe and predict the physiologic behavior of kidneys before transplantation.

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 Rp2 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 (Rp2 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.

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