Liver Fat Fraction and Machine Learning Improve Steatohepatitis Diagnosis in Liver Transplant Patients.
Authors
Hajek M,Sedivy P,Burian M,Mikova I,Trunecka P,Pajuelo D,Dezortova M
Affiliations (2)
Affiliations (2)
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
- Department of Hepatogastroenterology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
Abstract
Machine learning identifies liver fat fraction (FF) measured by <sup>1</sup>H MR spectroscopy, insulinemia, and elastography as robust, non-invasive biomarkers for diagnosing steatohepatitis in liver transplant patients, validated through decision tree analysis. Compared to the general population (~5.8% prevalence), MASH is significantly more common in liver transplant recipients (~30%-50%). In patients with FF > 5.3%, the positive predictive value for MASH ranged up to 97%, more than twice the value observed in the general population.
Topics
Machine LearningLiver TransplantationLiverFatty LiverJournal Article