Towards a Digital Twin of the Stomach with application to Digestion and Gastric Reflux

ORAL

Abstract

The stomach is responsible for physically and chemically processing the ingested meal before controlled emptying of the contents into the duodenum through the pyloric sphincter. If the orifice is unable to close due to dysfunction or surgery, contents could flow back from the duodenum into the stomach. The reverse flow could alter the low pH environment of the stomach, erode the mucosal lining, and the regurgitated contents, in some cases, may even reach the esophagus. In this work, an imaging data-based stomach model “StomachSim” is used to study the mechanism of duodenogastric reflux. The effect of variations in food properties and pre-existing motility disorders on the reflux are investigated. The primary driver of reflux was the relaxation of the antrum after a stomach contraction terminated near the pylorus. The region of the stomach walls exposed to the regurgitated contents changed significantly based on the density of stomach contents with respect to the duodenal contents. Concomitant stomach motility disorders led to weaker relaxation of the walls which in turn also affected the amounts of reflux. When the stomach contents were of higher viscosity, the proximal stomach applied increased pressure on the contents to achieve the same emptying rate which reduced the amount of duodenogastric reflux. The work illustrates the utility of in-silico models in identifying and investigating the effect of dietary and motility changes in gastrointestinal disorders.

*The authors acknowledge support from NSF award CBET 2019405 and NIH award 1R21GM139073-01.

Presenters

  • Sharun Kuhar

    • Johns Hopkins University

Authors

  • Sharun Kuhar

    • Johns Hopkins University
  • Jung-Hee Seo

    • Johns Hopkins University
  • Rajat Mittal

    • Johns Hopkins University