Artificial intelligence-aided steatosis assessment in donor livers according to the Banff consensus recommendations.

OBJECTIVES: Severe macrovesicular steatosis in donor livers is associated with primary graft dysfunction. The Banff Working Group on Liver Allograft Pathology has proposed recommendations for steatosis assessment of donor liver biopsy specimens with a consensus for defining "large droplet fat" (LDF) and a 3-step algorithmic approach. METHODS: We retrieved slides and initial pathology reports from potential liver donor biopsy specimens from 2010 to 2021. Following the Banff approach, we reevaluated LDF steatosis and employed a computer-assisted manual quantification protocol and artificial intelligence (AI) model for analysis. RESULTS: In a total of 113 slides from 88 donors, no to mild (<33%) macrovesicular steatosis was reported in 88.5% (100/113) of slides; 8.8% (10/113) was reported as at least moderate steatosis (≥33%) initially. Subsequent pathology evaluation, following the Banff recommendation, revealed that all slides had LDF below 33%, a finding confirmed through computer-assisted manual quantification and an AI model. Correlation coefficients between pathologist and computer-assisted manual quantification, between computer-assisted manual quantification and the AI model, and between the AI model and pathologist were 0.94, 0.88, and 0.81, respectively (P < .0001 for all). CONCLUSIONS: The 3-step approach proposed by the Banff Working Group on Liver Allograft Pathology may be followed when evaluating steatosis in donor livers. The AI model can provide a rapid and objective assessment of liver steatosis.

Detection of Large-Droplet Macrovesicular Steatosis in Donor Livers Based on Segment-Anything Model.

Liver transplantation is an effective treatment for end-stage liver disease, acute liver failure, and primary hepatic malignancy. However, the limited availability of donor organs remains a challenge. Severe large-droplet fat (LDF) macrovesicular steatosis, characterized by cytoplasmic replacement with large fat vacuoles, can lead to liver transplant complications. Artificial intelligence models, such as segmentation and detection models, are being developed to detect LDF hepatocytes. The Segment-Anything Model, utilizing the DEtection TRansformer architecture, has the ability to segment objects without prior knowledge of size or shape. We investigated the Segment-Anything Model's potential to detect LDF hepatocytes in liver biopsies. Pathologist-annotated specimens were used to evaluate model performance. The model showed high sensitivity but compromised specificity due to similarities with other structures. Filtering algorithms were developed to improve specificity. Integration of the Segment-Anything Model with rule-based algorithms accurately detected LDF hepatocytes. Improved diagnosis and treatment of liver diseases can be achieved through advancements in artificial intelligence algorithms for liver histology analysis.

Heterozygous midnolin knockout attenuates severity of nonalcoholic fatty liver disease in mice fed a Western-style diet high in fat, cholesterol, and fructose.

Although midnolin has been studied for over 20 years, its biological roles in vivo remain largely unknown, especially due to the lack of a functional animal model. Indeed, given our recent discovery that the knockdown of midnolin suppresses liver cancer cell tumorigenicity and that this antitumorigenic effect is associated with modulation of lipid metabolism, we hypothesized that knockout of midnolin in vivo could potentially protect from nonalcoholic fatty liver disease (NAFLD) which has become the most common cause of chronic liver disease in the Western world. Accordingly, in the present study, we have developed and now report on the first functional global midnolin knockout mouse model. Although the overwhelming majority of global homozygous midnolin knockout mice demonstrated embryonic lethality, heterozygous knockout mice were observed to be similar to wild-type mice in their viability and were used to determine the effect of reduced midnolin expression on NAFLD. We found that global heterozygous midnolin knockout attenuated the severity of NAFLD in mice fed a Western-style diet, high in fat, cholesterol, and fructose, and this attenuation in disease was associated with significantly reduced levels of large lipid droplets, hepatic free cholesterol, and serum LDL, with significantly differential gene expression involved in cholesterol/lipid metabolism. Collectively, our results support a role for midnolin in regulating cholesterol/lipid metabolism in the liver. Thus, midnolin may represent a novel therapeutic target for NAFLD. Finally, our observation that midnolin was essential for survival underscores the broad importance of this gene beyond its role in liver biology.NEW & NOTEWORTHY We have developed and now report on the first functional global midnolin knockout mouse model. We found that global heterozygous midnolin knockout attenuated the severity of nonalcoholic fatty liver disease (NAFLD) in mice fed a Western-style diet, high in fat, cholesterol, and fructose, and this attenuation in disease was associated with significantly reduced levels of large lipid droplets, hepatic free cholesterol, and serum LDL, with significantly differential gene expression involved in cholesterol/lipid metabolism.