Quantifying Fat Zonation in Liver Lobules: An IntegratedMultiscale In-silico Model Combining DisturbedMicroperfusion and Fat Metabolism via aContinuum-Biomechanical Bi-scale, Tri-phasic Approach

Abstract

Metabolic zonation refers to the spatial separation of metabolic functions along thesinusoidal axes of the liver. This phenomenon forms the foundation for adjusting hepaticmetabolism to physiological requirements in health and disease (e.g. metabolicdysfunction-associated steatotic liver disease/ MASLD). Zonated metabolic functions areinfluenced by zonal morphological abnormalities in the liver, such as periportal fibrosisand pericentral steatosis. We aim to analyze the interplay between microperfusion,oxygen gradient, fat metabolism and resulting zonated fat accumulation in a liver lobule.Therefore we developed a continuum-biomechanical, tri-phasic, bi-scale, and multicomponent insilicomodel, which allows to numerically simulate coupled perfusion-function-growth interactionstwo-dimensionally in liver lobules. The developed homogenized model has the following specifications:i) thermodynamically consistent, ii) tri-phase model (tissue, fat, blood), iii) penta-substances(glycogen, glucose, lactate, FFA, oxygen), and iv) bi-scale approach (lobule, cell). Our presentedin-silico model accounts for the mutual coupling between spatial and time-dependent liver perfusion,metabolic pathways and fat accumulation. The model thus allows the prediction of fatdevelopment in the liver lobule, depending on perfusion, oxygen and plasma concentration offree fatty acids (FFA), oxidative processes, the synthesis and the secretion of triglycerides (TGs).The use of a bi-scale approach allows in addition to focus on scale bridging processes. Thus,we will investigate how changes at the cellular scale affect perfusion at the lobular scale andvice versa. This allows to predict the zonation of fat distribution (periportal or pericentral)depending on initial conditions, as well as external and internal boundary value conditions.

Cross-Species Variability in Lobular Geometry and Cytochrome P450 Hepatic Zonation: Insights into CYP1A2, CYP2E1, CYP2D6 and CYP3A4

“…However, the hepatic microarchitecture is surprisingly robust, with significant but rather small differences in the related 2D geometrical parameters. This finding has important implications for computational modeling of the liver, which allows reusing lobular mathematical models of the liver across different species for simulation purposes with minor modifications (Lambers et al, 2023; Ricken et al, 2015).…”