ICC network density: Regulation and consequences

Simon J. Gibbons, Jerry Gao, Gianrico Farrugia

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


Interstitial cells of Cajal (ICC) are mesoderm-derived mesenchymal cells found in the smooth muscle layers of the gastrointestinal tract. They contribute to the normal function of the gut by generating rhythmic electrical activity, as intermediaries in neuromuscular signalling, altering the membrane potential of adjacent smooth muscle and responding to mechanical stretch. Depletion of ICC is associated with several gastrointestinal motility disorders including diabetic gastroparesis, slow transit constipation and intestinal pseudo-obstruction. This chapter reviews the information that can be obtained from measuring and characterizing networks of interstitial cells of Cajal in health and disease, the applications of that information in computer modelling and about how mathematical modelling might inform further efforts to characterize and/or reverse ICC network depletion. We describe the appropriate techniques for tissue collection and handling when investigating effects on ICC networks. Methods for identifying, accurately quantifying and mapping ICC are presented together with new analyses that can identify changes to the geometry as well as the density of the ICC networks. Finally we discuss the information that is obtained on the relationship between ICC network changes and alterations to gastrointestinal function and show how computer modelling of virtual ICC networks could be used to predict those relationships.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computational Vision and Biomechanics
PublisherSpringer Netherlands
Number of pages21
StatePublished - 2013

Publication series

NameLecture Notes in Computational Vision and Biomechanics
ISSN (Print)2212-9391
ISSN (Electronic)2212-9413


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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence


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