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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
Reconstructing subsurface electrical wave orientation from cardiac epi-fluorescence recordings: Monte Carlo versus
Christopher J Hyatt1, Christian W Zemlin, Rebecca M Smith
1Department of Pharmacology, SUNY Upstate Medical University, 750 E Adams St, Syracuse, NY 13210, USA.
Optics Express
|September 6, 2008
Summary
Monte Carlo models provide more accurate optical action potential predictions in cardiac tissue than diffusion models. This research improves optical imaging of heart electrical activity by comparing computational models with experimental data.
Area of Science:
- Cardiac electrophysiology
- Biophotonics
- Computational modeling
Background:
- Voltage-sensitive dyes enable optical imaging of cardiac electrical activity.
- Photon diffusion and electrical excitation models predict optical action potential shapes.
- Accuracy of diffusion models for thin tissues is uncertain.
Purpose of the Study:
- Compare diffusion and Monte Carlo (MC) models for optical imaging of cardiac electrical activity.
- Investigate the impact of tissue thickness on optical signal prediction.
- Validate computational models against experimental data from guinea pig hearts.
Main Methods:
- Developed and compared photon diffusion and Monte Carlo (MC) models.
- Simulated optical imaging of electrical activity in cardiac tissue.
- Acquired experimental data from intact guinea pig hearts for comparison.
Main Results:
- MC models predict a deeper contributing subsurface volume, leading to longer optical upstroke durations.
- MC model results show better agreement with experimental optical upstroke durations.
- Optical upstroke morphology correlates with subsurface wave orientation, independent of the model used.
Conclusions:
- Monte Carlo models offer improved accuracy for optical action potential prediction in cardiac tissue compared to diffusion models.
- Tissue thickness and subsurface electrical wave orientation are critical factors in optical imaging accuracy.
- This study enhances the understanding and predictive capability of optical imaging techniques in cardiac electrophysiology.
