Work

Accuracy of attenuation coefficient measurement (ACM) for hepatic steatosis: comparison with MRI proton density fat fraction (MRI-PDFF) and chemical fat analysis using multimodal liver fat phantoms

Year: 2025

Type: article

Abstract: Background The objective of this study was to evaluate the accuracy and reproducibility of real-time ultrasound steatometry using attenuation coefficient measurement (ACM) in comparison with magnetic resonance imaging proton density fat fraction (MRI-PDFF) and chemical fat analysis. Specifically, we assessed the diagnostic performance and reproducibility of ultrasound-based ACM against MRI-PDFF and laboratory fat quantification using multimodal liver fat phantoms (LFPs) with varying fat-to-water ratios. Methods Sixty LFPs with different fat concentrations were examined in two radiology centers and one chemical laboratory. Each phantom underwent three assessments: MRI-PDFF, ultrasound ACM, and laboratory-based chemical fat quantification. Correlation coefficients, intraclass correlation coefficients (ICC), receiver operating characteristic (ROC) analyses, and Bland–Altman analysis were performed to evaluate the relationships and agreement among the measurement methods. Results Median values of ACM, MRI-PDFF, and laboratory fat content were 2.39 (1.87–2.84), 3.88 (2.46–7.60), and 1.24 (0.51–3.90), respectively. Strong correlations were observed between ACM and laboratory fat quantification ( r = 0.878, p < 0.001) and between MRI-PDFF and laboratory analysis ( r = 0.881, p < 0.001). ACM also correlated strongly with MRI-PDFF ( r = 0.846, p < 0.001). The intraobserver reproducibility of ACM was excellent (ICC = 0.956, p < 0.001). AUROC values were 0.984 for ACM and 0.996 for MRI-PDFF, both indicating high diagnostic sensitivity and specificity. Conclusions ACM demonstrated strong agreement with MRI-PDFF and chemical fat analysis in LFPs, supporting its potential as a reliable, accurate, and cost-effective non-invasive technique for hepatic steatosis quantification.

Source: Frontiers in Medicine

DOI: 10.3389/fmed.2025.1698952

Authors: Maksym Zhaivoronok, Oleh Dynnyk, Nataliya Deresh, Tamara Nosenko, Nazarii Kobyliak

Institutions: Shupyk National Healthcare University of Ukraine, National University of Food Technologies, Bogomolets National Medical University

Language: English

Topic: Liver Disease Diagnosis and Treatment

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801