Category Archives: Publications

Genetic algorithm based model of action potential

WHAT IS KNOWN?

  1. Computer models use patient specific tissue geometry and cardiac fiber orientation to generate clinically relevant simulations of human cardiac action potentials.
  2. However, none of the models take into account tissue-specific, person-specific, and pathology-specific gene expression profiles which all are known to affect the action potential morphology and propagation dynamics.

WHAT THIS STUDY ADDS?

  1. A novel modification of genetic algorithm which determines personalized parameters of cardiac action potential based on set of human action potentials recorded at different heart rates.
  2. A mRNA based model that can predict action potential waveform at different heart rates with high precision and which makes it possible to map gene expression profile to cardiac function.

LINK TO THE ARTICLE

Smirnov D, Pikunov A, Syunyaev R, Deviatiiarov R, Gusev O, Aras K, Gams A, Koppel A, Efimov IR. Genetic algorithm-based personalized models of human cardiac action potential. PLoS One. 2020;15(5):e0231695. doi: 10.1371/journal.pone.0231695. eCollection 2020. PubMed PMID: 32392258.

Granger Causality-Based Fibrillation Analysis

WHAT IS KNOWN?

  1. Preclinical studies have implicated multiple mechanisms for sustaining myocardial fibrillation
  2. Clinical translation to guide treatment in patients with atrial fibrillation and ventricular fibrillation survival remains challenging due to poor spatial resolution of clinical mapping systems and a lack of suitable analysis tool.

WHAT THIS STUDY ADDS?

  1. Granger causality analysis, originally an econometric tool for quantifying causal relationships between complex-time series, was developed in rat ventricular fibrillation and validated in human ventricular fibrillation and atrial fibrillation as a novel fibrillation mapping tool.
  2. Grange causality-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map rotational drivers using low spatial resolution sequentially acquired data.

LINK TO ARTICLE

Handa BS, Li X, Aras KK, Qureshi NA, Mann I, Chowdhury RA, Whinnett ZI, Linton NWF, Lim PB, Kanagaratnam P, Efimov IR, Peters NS, Ng FS. Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers. Circ Arrhythm Electrophysiol. 2020 Mar;13(3):e008237. doi: 10.1161/CIRCEP.119.008237. Epub 2020 Feb 16. PubMed PMID: 32064900; PubMed Central PMCID: PMC7069398.