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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
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Ventricular anatomical complexity and sex differences impact predictions from electrophysiological computational
Pablo Gonzalez-Martin1, Federica Sacco2,3, Constantine Butakoff1
1ELEM Biotech S.L., Barcelona, Spain.
Plos One
|February 13, 2023
Summary
Sex hormones and heart anatomy significantly impact cardiac electrophysiology and ventricular tachycardia (VT) inducibility. Detailed anatomical models reveal differences in QRS and T-waves, influencing VT prediction.
Area of Science:
- Computational Biology
- Cardiovascular Physiology
- Medical Imaging
Background:
- Cardiac electrophysiology simulations often simplify heart anatomy, potentially overlooking crucial details.
- Sex hormones and intricate anatomical features like trabeculations can influence heart electrical activity.
Purpose of the Study:
- To investigate the influence of sex hormones and anatomical details (trabeculations) on human heart electrophysiology.
- To analyze sex- and anatomy-dependent effects on ventricular tachycardia (VT) inducibility using computational models.
Main Methods:
- Utilized high-resolution MRI to create detailed and smoothed biventricular geometries (male and female).
- Performed finite element model (FEM) simulations with sex-specific O'Hara-Rudy myocyte models.
- Compared electrophysiological responses between detailed vs. smoothed and male vs. female anatomies, including a scarred heart model.
Main Results:
- Female hearts showed anatomy-dependent QT-interval prolongation compared to males.
- Detailed geometries exhibited QRS fractionation and increased T-wave magnitude versus smoothed geometries.
- Male geometries showed geometry-dependent differences in VT inducibility and reentry channel prediction; female VT induction was less consistent.
Conclusions:
- Anatomical complexity and sex hormones are critical factors in cardiac electrophysiology and VT risk.
- Simplified 'smooth' endocardial models may lead to inaccurate predictions of reentry channels in VT inducibility studies.
- In-silico models must incorporate detailed cardiac anatomy for accurate electrophysiological predictions.
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