Overview
Steatotic liver disease, formerly known as fatty liver disease, is common, and it can lead to cirrhosis, liver cancer and the need for a liver transplant. The challenge is that different causes of fatty liver disease can look very similar on a biopsy slide. Alcohol-related injury; metabolic injury, which is often linked to obesity and diabetes; and mixed injury can overlap so much that it is hard to tell them apart and to predict who is at highest risk.
The Artificial Intelligence-Enabled Precision in Liver Pathology Laboratory led by Chady Meroueh, M.D., aims to develop new ways to evaluate liver biopsies using artificial intelligence (AI). The lab builds computer models that measure patterns in routine pathology slides and connect those patterns to clinical lab results, genomics studies and patient outcomes. The lab also studies gene activity inside the tissue using spatial transcriptomics, which help explain why certain injury patterns occur and which biological pathways drive progression.
The lab's goal is to deliver tools that support more-precise diagnoses and prognoses for steatotic liver diseases. These diseases include alcohol-associated liver disease, metabolic dysfunction-associated steatotic liver disease and mixed-etiology disease.
Over time, the lab seeks to:
- More accurately classify liver diseases when causes are mixed or unclear.
- Provide better risk prediction to guide monitoring and treatment decisions.
- Identify links between tissue findings and underlying biology, supporting future noninvasive diagnostics.
- Guide more-personalized care and accelerate discovery of new biomarkers and treatment targets.