A Workflow for Creating Gastric Computational Models from SPARC Scaffolds

In-silico studies are an ideal medium to model and improve our understanding of the mechanisms underlying gastric motility in health and disease. In this study, a workflow to create computational models of the stomach was developed using SPARC scaffolds. Three anatomically based finite element method (FEM) models of the rat stomach incorporating experimental measurements of muscle layer thickness and fiber orientations across the stomach were developed: (i) 2D (surface) FEM model with no thickness, (ii) 3D (volume) FEM model with a fixed thickness across the longitudinal and circular muscle layers, and (iii) 3D (volume) FEM model with varying thickness across the longitudinal and circular muscle layers. The three FEM models were subsequently used in whole-organ slow wave simulations and the impact of anatomical details on the simulation outcomes was investigated. The 3D FEM model with varying thickness was the most computationally expensive, while the 2D FEM model provided the fastest solution (a 200 s simulation took 8 min vs. 38 h to solve). The spatiotemporal profiles of the slow wave activation and propagation in the three FEM models were in good agreement. The largest temporal difference of 1 s in cellular activation was observed between the 2D FEM model and the varying thickness 3D FEM model in the most distal-stomach regions. These FEM models and developed workflow will be used in in-silico studies to improve our understanding of the structure-function relationship in the stomach and identify the optimal parameters of electrical therapies, an alternative treatment for the motility disorders in the stomach. In addition, the developed workflow can be readily used to generate computational models of other organs using SPARC scaffolds.