PhD Scientific Days 2024

Budapest, 9-10 July 2024

Pharmaceutical Sciences and Health Technologies II.

The Calculation and Evaluation of an Ultrasound-Estimated Fat Fraction in Non-Alcoholic Fatty Liver Disease and Metabolic-Associated Fatty Liver Disease


Zita Zsombor1, Pál Novák Kaposi1, Aladár D. Rónaszéki1, Bettina K. Budai1, Barbara Csongrády1, Róbert Stollmayer1, Ildikó Kalina1, Gabriella Győri1, Viktor Bérczi1, Klára Werling1, Pál Maurovich-Horvat1, Anikó Folhoffer2, Krisztina Hagymási3
1: Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University
2: Department of Internal Medicine and Oncology, Faculty of Medicine, Semmelweis University
3: Department of Surgery, Transplantation and Gastroenterology, Faculty of Medicine, Semmelweis University

Text of the abstract

Introduction: Accurate diagnosis and monitoring of fatty liver disease are crucial for early intervention and prevention of complications. MRI-PDFF is recommended as a reference method after biopsy, but it is expensive, and its availability is limited. Other non-invasive techniques such as Quantitative
ultrasound (QUS) measurements are increasing in popularity for the detection of hepatic steatosis.
Aims: We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. Methods and Results: We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. 5% and <10% vs. 10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. Conclusion: In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose 5% and 10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors. Funding: Z.Z. was partly funded by a Ph.D. scholarship from the New National Excellence Program (ÚNKP–23–3–I–SE–23) of the Ministry of Culture and Innovation of Hungary.