Multiscale mechanistic modelling of heterogeneity in cardiac sub-cellular calcium handling accounting for variable

Michael A Colman1, Yohannes Shiferaw2, David Conesa1

  • 1Department of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, West Yorkshire, UK.

Insights

We developed an efficient computational model for cardiac calcium handling that captures spatial dynamics without explicit modeling. This model simulates normal and abnormal heart rhythms, aiding arrhythmia research and patient-specific treatments.

Area of Science:

  • Cardiology
  • Computational Biology
  • Biophysics

Background:

  • Subcellular calcium handling in cardiac myocytes is crucial for normal and abnormal heart function.
  • The transverse and axial tubular system (t-system) influences calcium-induced calcium-release synchrony and arrhythmogenic behaviors.
  • Existing detailed 3D models are computationally expensive for large-scale tissue simulations.

Purpose of the Study:

  • To develop a computationally efficient model of spatially dependent subcellular calcium handling.
  • To capture a broad range of calcium handling phenomena without explicit spatial modeling.
  • To enable integration into existing cell models for variable t-system density simulations.

Main Methods:

  • Developed a model tracking calcium release unit (CRU) state occupancy.
  • Incorporated activation rates for triggered, spontaneous, and spatially recruited calcium sparks.
  • Designed as an independent module for integration into existing cardiac cell models.

Main Results:

  • The model accurately reproduces normal and abnormal pacing dynamics.
  • Simulated centripetal calcium waves in cells lacking a robust t-system.
  • Captured calcium transient alternans, delayed triggered sparks, and spontaneous calcium release.

Conclusions:

  • The novel model efficiently captures spatial calcium handling features without explicit spatial modeling.
  • Achieves computational efficiency suitable for large-scale tissue simulations.
  • Applicable to mechanistic arrhythmia research and patient-specific modeling.