A computational view of electrophysiological properties under different atrial fibrosis conditions

Juan P. Ugarte, Catalina Tobón, José António Tenreiro Machado

Research output: Contribution to journalArticlepeer-review

Abstract

The excessive proliferation of fibroblasts causes fibrosis, a hallmark of atrial fibrillation (AF), and leads to alterations in the electrical conduction within the heart. However, the underlying electrophysiological mechanisms behind the multifactorial characteristic of AF fibrosis are not fully understood. This work studies the electrophysiological properties of different fibrosis configurations using computational simulations. For this purpose, the intermingling action of the structural and electrical remodeling due to fibroblasts are implemented in an electrophysiological description of the AF fibrosis. The model is built on the base of complex order operators and a fibroblast ionic formulation. Additionally, three fibrosis textures are considered for designing the atrial tissue representations. The resting and depolarization properties are analyzed by means of information theory and multidimensional scaling. The results evinced that the modulation of cardiomyocytes resting potential, exerted by the fibroblasts, is the mechanism giving rise to emergent electrophysiological properties as a result of the synergetic mathematical formulation of the proposed fibrosis model. The metrics assessing such properties unravel distinctive signatures of each fibrosis texture. Additionally, the multidimensional scaling computational tool reveals clusters specifically determined by the resting and depolarization properties, or by their combination. The observed clusters support an electrophysiological interpretation through the underlying fibrosis configuration, in which the diffuse, patchy and compact textures are relevant in determining the emergent patterns.

Original languageEnglish
Pages (from-to)534-550
Number of pages17
JournalApplied Mathematical Modelling
Volume105
DOIs
StatePublished - May 2022

Keywords

  • Cardiac computation
  • Clustering
  • Complex order operators
  • Fibroblasts
  • Fractional calculus
  • Multidimensional scaling

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