A framework for simulating gastric electrical propagation in confocal microscopy derived geometries

Abstract

Interstitial Cells of Cajal (ICC) initiate and actively propagate electrical events in the gastrointestinal tract known as slow-waves. The slow-waves coordinate the contraction of the gastrointestinal tract necessary for breakdown and mixing of ingested food. Degradation of the ICC numbers has been linked to several gastrointestinal motility disorders. However, limitations in imaging techniques and techniques for the quantification of ICC network structure have hindered our understanding of these disorders. We evaluated different machine learning techniques to segment ICC networks imaged using confocal microscopy. The accuracy the segmented networks were then quantified and compared using numerical metrics. Structurally realistic finite element meshes were constructed and used to simulate the propagation of electrical activation over the tissue blocks. The presented framework provides a system to quantify the structure and function of an ICC tissue sample. These methods are also applicable to other biological tissues and networks.