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Related Experiment Videos

Multicellular simulation predicts microvascular patterning and in silico tissue assembly.

Shayn M Peirce1, Eric J Van Gieson, Thomas C Skalak

  • 1Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia, USA.

FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology
|February 10, 2004
PubMed
Summary

This study introduces a computational simulation to predict blood vessel network remodeling. The model accurately forecasts how mechanical stresses and growth factors influence vascular patterns, aiding therapeutic revascularization strategies.

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Area of Science:

  • Computational biology
  • Vascular biology
  • Biomedical engineering

Background:

  • Microvascular network remodeling is vital for physiological adaptation and therapeutic revascularization.
  • Cellular behaviors like proliferation, differentiation, and migration are guided by biochemical and biomechanical signals.

Purpose of the Study:

  • To develop a computational simulation integrating epigenetic, molecular, and cellular factors to predict microvascular network patterning.
  • To quantitatively predict vessel network remodeling in response to hemodynamic stresses and angiogenic growth factors.

Main Methods:

  • A cellular automata (CA) computational simulation was developed, incorporating over 50 rules from experimental data.
  • The model simulates thousands of interacting cells, growth factors, and their tissue environment.

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  • The simulation predicts responses to network-wide hemodynamic stress changes and focal delivery of angiogenic growth factors.

    • Main Results:

    • The CA model predicted increased vascular density (370+/-29 mm/mm3) after 14 days of exogenous growth factor treatment, comparable to in vivo results (480+/-41 mm/mm3).
    • A twofold increase in contractile vessel lengths was predicted 5-10 days after a 10% increase in circumferential wall strain, aligning with in vivo observations.
    • The simulation identified a functional patterning module capable of predicting vessel network remodeling.

    Conclusions:

    • The developed CA simulation accurately predicts microvascular network remodeling in response to epigenetic stimuli.
    • This computational model offers a valuable tool for understanding and potentially guiding therapeutic revascularization strategies.