# A Workflow for Creating Gastric Computational Models from SPARC Scaffolds
## 1 Introduction  
Digestion in the gastrointestinal (GI) tract is reliant on coordinated contraction and relaxation of the muscles regulated by neurogenic, myogenic, and hormonal mechanisms [1, 2]. Disrupted neuromuscular activity within the gut is associated with functional motility disorders (also known as disorders of the brain-gut interaction) impacting over 40% of the global population [3]. Despite their widespread occurrence and significant burden on healthcare systems, the diagnosis and treatment of functional motility disorders are challenging because the underlying mechanisms of these disorders remain largely unidentified [4, 5]. There is a growing body of research and clinical evidence linking the GI motility disorders with impaired bioelectrical activity known as slow waves [6]. Slow waves aregenerated by interstitial cells of Cajal (ICC) that are interspersed within the layers of gastric muscle and are responsible for regulating muscle contractions [7]. Histopathological and imaging evidence has revealed that significant changes and reduction in ICC are linked with disrupted slow wave activity and motility problems [8]. However, the complex and interacting mechanism of the ICC and smooth muscle cells is imperfectly understood. In-silico models provide greater flexibility and opportunity to investigate bioelectrical activity and the structure-function relationship in the stomach in healthy, disease and interventional states. A number of studies have previously modeled normal and abnormal slow wave activation and propagation from cellular to organ level [9; 10], investigated electromechanical coupling [11; 12], and developed in-silico models of gastric pacing [9]. However, the stomach models used in these studies were largely generated from gross anatomical imaging data simplifying the anatomical properties of the gastric musculature. Gastric smooth muscles are arranged as layered structure such that different layers of smooth muscle cells are commonly aligned along the longitudinal or circumferential axes of the organ, with the circumferential layer typically being the thickest [13; 14]. These structural characteristics play a critical role in determining directions and strengths of contractions and patterns of motility [15]. In addition, the majority of these studies used human stomach models and there is a need for anatomically based stomach models of rodents that are widely used in preclinical studies [16; 17]. An improved understanding of bioelectrical mechanisms in the stomach could also help to develop new and more effective therapies for the gastric motility disorders such as electrical therapies that regulate the activation and propagation of slow waves by using electrical stimuli [6; 18]. Electrical therapies of the stomach have been previously used to treat the loss of peristal activity in postoperative ileus [19], to increase the rate of gastric emptying and control symptoms in gastropareiss [20], and to delay gastric emptying to treat obesity [21; 22]. However, the results have generally been inconsistent and variable. This is mainly because adapting electrical therapies to clinical settings and quantifying the efficacy across a vast range of intervention parameters are challenging due to the complexity of biological regulatory mechanisms of gastric motility [23]. Computational studies can aid in the investigation of electrophysiological and functional responses to electrical therapies and identification of the most effective treatment protocols. Recently, the National Institutes of Health have initiated a comprehensive research program entitled Stimulating Peripheral Activity to Relieve Conditions (SPARC) to transform our understanding of nerve-organ interactions with the intent of advancing bioelectronic medicine towards treatments.