Contents

📒 Trayanova 2012

Computational cardiology: how computer simulations could be used to develop new therapies and advance existing ones1

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Introduction

  • iterative interaction between experimentation and simulation
  • the heart is the most highly advanced example of a virtual organ, capable of integrating data at multiple scales, from genes to the whole organ.

Subject-specific biophysically-detailed modelling of the heart for optimization and advancement of therapies for arrhythmias and pump dysfunction

  • Imaging: ex vivo structural and diffusion tensor (DT) magnetic resonance imaging (MRI) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482619/bin/eus27701.jpg

  • Computational modelling of the electrophysiology of the human atria is also becoming an important component in the evaluation and advancement of therapeutic strategies

    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482619/bin/eus27702.jpg
    patient-specific model with the fibrosis regions

  • biophysically detailed electromechanical models of the heart

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482619/bin/eus27703.jpg

  • maximal haemodynamic benefit occurred when the LV pacing site was located near the base and mid-ventricle, which was within the region of longest electromechanical delay

Biophysically-detailed computational modelling of the heart as a testbed for new molecular therapies

  • A major avenue of scientific inquiry in computational cardiology relates the binding/unbinding of drugs to molecular target(s) to the instigation, termination or prevention of cardiac arrhythmias
  • Markov models with state specific drug binding/unbinding have been used to test hypotheses regarding the mechanisms of drug effects on macroscopic currents https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482619/bin/eus27704.jpg

Biophysically detailed computational modelling of novel defibrillation therapies

  • biophysically detailed multi-scale models of defibrillation have made major contributions to understanding how defibrillation shocks used in clinical practice interact with cardiac tissue.
  • development of new methodologies for low-voltage termination of lethal arrhythmias or for applying defibrillation in novel, less damaging ways
  • kilohertz-range alternating current (AC) fields have been known to instantaneous and reversibly block electrical conduction in nerve tissue => similarly produce reversible block of cardiac impulse propagation and lead to successful defibrillation

Biophysically detailed computational modelling of the heart in risk stratification for arrhythmias

  • who would benefit from Implantable Cardioverter-Defibrillator (ICD) therapy
  • results of clinical trials to correlate surface EGG indices to lethal cardiac arrhythmias are often contradictory => EP simulations come into play
  • a steep action potential duration (APD) restitution (>1) at rapid heart rates67 produces alternans in APD that underlie T-wave alternans and the genesis of fibrillation
  • detecting instabilities in the QT interval in clinical ECGs can predict VT onset

Inverse problem in electrocardiography: computational modelling of the heart as a diagnostic tool

  • The application of inverse electrocardiography in humans has been led by the Rudy lab
  • electrocardiographic imaging (ECGI) method computes epicardial extracellular potential distributions

Concluding remarks

  • Modern cardiac research has increasingly recognized that appropriate models and simulation can help interpret an array of experimental data and dissect important mechanisms and relationships.

Reference


  1. Trayanova NA, O’Hara T, Bayer JD, et al. Computational cardiology: how computer simulations could be used to develop new therapies and advance existing ones. Europace. 2012;14 Suppl 5(Suppl 5):v82-v89. PMC3482619 ↩︎