A stochastic multi-scale model of electrical function in normal and depleted ICC networks

Jerry Gao, Peng Du, Rosalind Archer, Greg O'Grady, Simon J. Gibbons, Gianrico Farrugia, Leo K. Cheng, Andrew J. Pullan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Multi-scale modeling has become a productive strategy for quantifying interstitial cells of Cajal (ICC) network structure-function relationships, but the lack of large-scale ICC network imaging data currently limits modeling progress. The single normal equation simulation (SNESIM) algorithm was utilized to generate realistic virtual images of small real wild-type (WT) and 5-HT$ 2B-receptor knockout (Htr2b$ -/-) mice ICC networks. Two metrics were developed to validate the performance of the algorithm: 1) network density, which is the proportion of ICC in the tissue; and 2) connectivity, which reflects the degree of connectivity of the ICC network. Following validation, the SNESIM algorithm was modified to allow variation in the degree of ICC network depletion. ICC networks from a range of depletion severities were generated, and the electrical activity over these networks was simulated. The virtual ICC networks generated by the original SNESIM algorithm were similar to that of their real counterparts. The electrical activity simulations showed that the maximum current density magnitude increased as the network density increased. In conclusion, the SNESIM algorithm is an effective tool for generating realistic virtual ICC networks. The modified SNESIM algorithm can be used with simulation techniques to quantify the physiological consequences of ICC network depletion at various physical scales.

Original languageEnglish (US)
Article number5979206
Pages (from-to)3451-3455
Number of pages5
JournalIEEE Transactions on Biomedical Engineering
Issue number12 PART 2
StatePublished - Dec 2011


  • Gastroenterology
  • image generation
  • interstitial cells of Cajal (ICC)
  • single normal equation simulation (SNESIM)

ASJC Scopus subject areas

  • Biomedical Engineering


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