Document Type

Article

Publication Date

3-3-2026

Department

Department of Materials Science and Engineering; Department of Biomedical Engineering

Abstract

Screening patients with liver fibrosis and identifying those at risk of developing advanced liver fibrosis is of clinical interest. Shear wave elastography (SWE), a promising non-invasive screening tool used to distinguish healthy tissue from diseased tissue, measures tissue shear wave speed (SWS) to describe tissue stiffness and identify liver fibrosis. However, considerable variations in the reported results have been found. We propose that the heterogeneity of the liver tissue background, such as the presence of fatty liver tissue and the preferred local orientation of the scarred fibrotic liver tissues embedded into the liver parenchyma, may contribute to the uncertainty in SWE measurements. Therefore, this study aims to systematically investigate four cofounding factors, the size, volume fraction, and orientation of the fibrotic inclusions, as well as the fatty background, using computer simulations, to describe the multifaceted impact on SWS variability (i.e., SWS standard deviation). The simulations implemented in this preliminary study demonstrated that both fibrosis and fatty background impact the SWS STD and that the SWS STD distributions do not follow a Gaussian distribution. While the SWS STD increased with fibrosis size and volume fraction, the SWS STD decreased as the fatty background increased. The shape of the distribution did not follow a consistent trend across fibrosis inclusion levels, fibrosis sizes, fibrosis orientations, and percent fatty background for either the Mean SWS or the SWS STD. The current study provided evidence that the current clinical guidelines, regarding cut-off values for the different METAVIR Fibrosis stages, overestimate the fibrosis levels in the presence of steatosis.

Publisher's Statement

© The Author(s) 2026. Publisher’s version of record: https://doi.org/10.1007/s13246-026-01712-8

Publication Title

Physical and Engineering Sciences in Medicine

Version

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