ABSTRACT
Access to lifesaving liver transplantation is limited by a severe organ shortage. One factor contributing to the shortage is the high rate of discard in livers with histologic steatosis. Livers with <30% macrosteatosis are generally considered safe for transplant. However, histologic assessment of steatosis by a pathologist remains subjective and is often limited by image quality. Here, we address this bottleneck by creating an automated digital algorithm for calculating histologic steatosis using only images of liver biopsy histology obtained with a smartphone. Methods: Multiple images of frozen section liver histology slides were captured using a smartphone camera via the optical lens of a simple light microscope. Biopsy samples from 80 patients undergoing liver transplantation were included. An automated digital algorithm was designed to capture and count steatotic droplets in liver tissue while discounting areas of vascular lumen, white space, and processing artifacts. Pathologists of varying experience provided steatosis scores, and results were compared with the algorithm's assessment. Interobserver agreement between pathologists was also assessed. Results: Interobserver agreement between all pathologists was very low but increased with specialist training in liver pathology. A significant linear relationship was found between steatosis estimates of the algorithm compared with expert liver pathologists, though the latter had consistently higher estimates. Conclusions: This study demonstrates proof of the concept that smartphone-captured images can be used in conjunction with a digital algorithm to measure steatosis. Integration of this technology into the transplant workflow may significantly improve organ utilization rates.
ABSTRACT
Liver transplantation is hampered by a severe shortage of donor organs. Normothermic machine perfusion (NMP) of donor livers allows dynamic preservation in addition to viability assessment before transplantation. Little is known about the injury and repair mechanisms induced during NMP. To investigate these mechanisms, we examined gene and protein expression changes in a cohort of discarded human livers, stratified by hepatocellular function, during NMP. Six human livers acquired through donation after circulatory death (DCD) underwent 12 h of NMP. Of the six livers, three met predefined criteria for adequate hepatocellular function. We applied transcriptomic profiling and protein analysis to evaluate temporal changes in gene expression during NMP between functional and nonfunctional livers. Principal component analysis segregated the two groups and distinguished the various perfusion time points. Transcriptomic analysis of biopsies from functional livers indicated robust activation of innate immunity after 3 h of NMP followed by enrichment of prorepair and prosurvival mechanisms. Nonfunctional livers demonstrated delayed and persistent enrichment of markers of innate immunity. Functional livers demonstrated effective induction of autophagy, a cellular repair and homeostasis pathway, in contrast to nonfunctional livers. In conclusion, NMP of discarded DCD human livers results in innate immune-mediated injury, while also activating autophagy, a presumed mechanism for support of cellular repair. More pronounced activation of autophagy was seen in livers that demonstrated adequate hepatocellular function.NEW & NOTEWORTHY We demonstrate that ischemia-reperfusion injury occurs in all livers during NMP, though there are notable differences in gene expression between functional and nonfunctional livers. We further demonstrate that activation of the liver's repair and homeostasis mechanisms through autophagy plays a vital role in the graft's response to injury and may impact liver function. These findings indicate that liver autophagy might be a key therapeutic target for rehabilitating the function of severely injured or untransplantable livers.
