Hyperspectral imaging for quantitative assessment of hepatic steatosis in human liver allografts. Issue 8 (5th June 2022) - Wagner, Tristan; Katou, Shadi; Wahl, Philip; Vogt, Franziska; Kneifel, Felicia; Morgul, Haluk; Vogel, Thomas; Houben, Philipp; Becker, Felix; Struecker, Benjamin; Pascher, Andreas; Radunz, Sonia
Abstract: Introduction: In liver transplantation (LT), steatosis is commonly judged to be a risk factor for graft dysfunction, and quantitative assessment of hepatic steatosis remains crucial. Liver biopsy as the gold standard for evaluation of hepatic steatosis has certain drawbacks, that is, invasiveness, and intra‐ and inter‐observer variability. A non‐invasive, quantitative modality could replace liver biopsy and eliminate these disadvantages, but has not yet been evaluated in human LT. Methods: We performed a pilot study to evaluate the feasibility and accuracy of hyperspectral imaging (HSI) in the assessment of hepatic steatosis of human liver allografts for transplantation. Thirteen deceased donor liver allografts were included in the study. The degree of steatosis was assessed by means of conventional liver biopsy as well as HSI, performed at the end of back‐table preparation, during normothermic machine perfusion (NMP), and after reperfusion in the recipient. Results: Organ donors were 51 [30–83] years old, and 61.5% were male. Donor body mass index was 24.2 [16.5–38.0] kg/m 2 . The tissue lipid index (TLI) generated by HSI at the end of back‐table preparation correlated significantly with the histopathologically assessed degree of overall hepatic steatosis (R2 = .9085, P < .0001); this was based on a correlation of TLI and microvesicular steatosis (R2 = .8120; P < .0001). There is also a linear relationship between the histopathologically assessed degree of overall steatosis and TLI during NMP (R2 = .5646; P = .0031) as well as TLI after reperfusion (R2 = .6562; P = .0008). Conclusion: HSI may safely be applied for accurate assessment of hepatic steatosis in human liver grafts. Certainly, TLI needs further assessment and validation in larger sample sizes.