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. 2010 May;7(5):692-8.
doi: 10.1016/j.hrthm.2010.01.030. Epub 2010 Feb 1.

Finite element modeling of subcutaneous implantable defibrillator electrodes in an adult torso

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Finite element modeling of subcutaneous implantable defibrillator electrodes in an adult torso

Matthew Jolley et al. Heart Rhythm. 2010 May.

Abstract

Background: Total subcutaneous implantable subcutaneous defibrillators are in development, but optimal electrode configurations are not known.

Objective: We used image-based finite element models (FEM) to predict the myocardial electric field generated during defibrillation shocks (pseudo-DFT) in a wide variety of reported and innovative subcutaneous electrode positions to determine factors affecting optimal lead positions for subcutaneous implantable cardioverter-defibrillators (S-ICD).

Methods: An image-based FEM of an adult man was used to predict pseudo-DFTs across a wide range of technically feasible S-ICD electrode placements. Generator location, lead location, length, geometry and orientation, and spatial relation of electrodes to ventricular mass were systematically varied. Best electrode configurations were determined, and spatial factors contributing to low pseudo-DFTs were identified using regression and general linear models.

Results: A total of 122 single-electrode/array configurations and 28 dual-electrode configurations were simulated. Pseudo-DFTs for single-electrode orientations ranged from 0.60 to 16.0 (mean 2.65 +/- 2.48) times that predicted for the base case, an anterior-posterior configuration recently tested clinically. A total of 32 of 150 tested configurations (21%) had pseudo-DFT ratios </=1, indicating the possibility of multiple novel, efficient, and clinically relevant orientations. Favorable alignment of lead-generator vector with ventricular myocardium and increased lead length were the most important factors correlated with pseudo-DFT, accounting for 70% of the predicted variation (R(2) = 0.70, each factor P < .05) in a combined general linear model in which parameter estimates were calculated for each factor.

Conclusion: Further exploration of novel and efficient electrode configurations may be of value in the development of the S-ICD technologies and implant procedure. FEM modeling suggests that the choice of configurations that maximize shock vector alignment with the center of myocardial mass and use of longer leads is more likely to result in lower DFT.

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Conflict of interest statement

Conflict of interest statement

Matthew Jolley: No conflicts to report

Jeroen Stinstra: No conflicts to report

Jess Tate No conflicts to report

Steve Pieper: No conflicts to report

Rob MacLeod: No conflicts to report

Larry Chu: No conflicts to report

Paul Wang: No conflicts to report

John K. Triedman: Honorarium, Boston Scientific CRM

Figures

Figure 1
Figure 1
Imaging and Computational Pipeline: A. Rendering of original CT in SCIRun. B. Electrode placement in SCIRun C. Visualization of isopotential surfaces (upper scale-Volts) and voltage gradients on cardiac surface (lower scale-V/cm) D. Example of graph of percentage of ventricular myocardium vs. voltage gradient for 500 volt potential difference.
Figure 2
Figure 2
Left-sided ICD can positions corresponding to named parameters, with number of configurations tested in both left- and right-sided versions of each position.
Figure 3
Figure 3
Starting orientation for Grace et al (left) and Lieberman et al (right) in modeling environment based on the literature. All modeled orientations were normalized to the predicted DFT for the orientation on the right (Lieberman).
Figure 4
Figure 4
Diagram of distances measured for each electrode and generator configuration. Metric A: Alignment of thoracic field with myocardium, measured as distance of center of mass of heart from line between generator and lead; Metric B. Minimum distance between generator and lead; Metric C: Minimum distance between generator and surface of heart; Metric D: Minimum distance between lead and surface of heart
Figure 5
Figure 5
Predicted effects of two major parameters on predicted DFT based on general linear model. Left panel: effect of increase in Metric A (worsening of alignment of shock vector with ventricular myocardial center of mass) to increase predicted DFT. Right panel: effect of increase in electrode length to decrease predicted DFT by smaller increment.
Figure 6
Figure 6
Top panels: Examples of two-electrode configurations, with predicted DFT ratios. Bottom panels: Examples of electrode array configurations, with predicted DFT ratios.

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