Modeling the Fluid Dynamics in a Human Stomach to Gain Insight of Food Digestion

Abstract

Abstract: During gastric digestion, food is disintegrated by a complex interaction of chemical and mechanical effects. Although the mechanisms of chemical digestion are usually characterized by using in vitro analysis, the difficulty in reproducing the stomach geometry and motility has prevented a good understanding of the local fluid dynamics of gastric contents. The goal of this study was to use computational fluid dynamics (CFD) to develop a 3‐D model of the shape and motility pattern of the stomach wall during digestion, and use it to characterize the fluid dynamics of gastric contents of different viscosities. A geometrical model of an averaged‐sized human stomach was created, and its motility was characterized by a series of antral‐contraction waves of up to 80% relative occlusion. The flow field within the model (predicted using the software Fluent™) strongly depended on the viscosity of gastric contents. By increasing the viscosity, the formation of the 2 flow patterns commonly regarded as the main mechanisms driving digestion (i.e., the retropulsive jet‐like motion and eddy structures) was significantly diminished, while a significant increase of the pressure field was predicted. These results were in good agreement with experimental data previously reported in the literature, and suggest that, contrary to the traditional idea of a rapid and complete homogenization of the meal, gastric contents associated with high viscous meals are poorly mixed. This study illustrates the capability of CFD to provide a unique insight into the fluid dynamics of the gastric contents, and points out its potential to develop a fundamental understanding and modeling of the mechanisms involved in the digestion process. Practical Application: This study illustrates the capability of computational fluid dynamic techniques to provide a unique insight into the dynamics of the gastric contents, pointing out its potential to develop a fundamental understanding and modeling of the human digestion process.