Specific structural traits such as deficient or altered networks of interstitical cells of Cajal (ICC) are often observed in gastroparesis, constipation, chronic intestinal pseudo-obstruction, and Hirschsprung disease based on qualitative histopathological findings, serve as key factors in inferring the health of gastrointestinal (GI) motility function. However, the assessment of ICC at present is limited by the lack of readily available 3D quantitative metrics. Although confocal microscopy can image and quantify the spatial distribution of ICC networks, current techniques to evaluate ICC in histological studies are limited to nuclei counts, or simply by objective visual grading. Although a suite of numerical metrics for the quantitative assessment of the structural features of ICC networks has previously been developed. However, the analysis has been limited to the analysis of ICC structure in 2D images. A 3D framework for quantifying and visualising these ICC networks could provide a valuable tool to elucidate the pathophysiology of GI motility disorders.
In our analysis, 3D visualization techniques namely, 3D structure tensor analysis, 3D Fourier analysis, 3D Graph Network, capable of providing whole-mount gastric antrum tissue imaging representations of proximal and distal regional descriptors based on fluorescence data acquisition have been developed.
Using the murine stomach as a model, the methods outlined in this paper allowed us to analyse and interrogate the gastrointestinal ICC networks structural variations and orientation distribution and better infer and delineate the underlying structural network in unprecedented detail.