Elsevier

Medical Image Analysis

Volume 57, October 2019, Pages 197-213
Medical Image Analysis

A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data

https://doi.org/10.1016/j.media.2019.06.017Get rights and content
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open access

Highlights

  • Electrical properties of cardiac tissue can be defined with rule-based methods.

  • Non-invasive clinical data can be used to parameterize rule-based models.

  • Rule-based methods to simulate cardiac electrophysiology are fast and cheap.

  • Fast endocardial conduction models realistically simulate heart electrophysiology.

Abstract

Background

Cardiac Resynchronization Therapy (CRT) is one of the few effective treatments for heart failure patients with ventricular dyssynchrony. The pacing location of the left ventricle is indicated as a determinant of CRT outcome.

Objective

Patient specific computational models allow the activation pattern following CRT implant to be predicted and this may be used to optimize CRT lead placement.

Methods

In this study, the effects of heterogeneous cardiac substrate (scar, fast endocardial conduction, slow septal conduction, functional block) on accurately predicting the electrical activation of the LV epicardium were tested to determine the minimal detail required to create a rule based model of cardiac electrophysiology. Non-invasive clinical data (CT or CMR images and 12 lead ECG) from eighteen patients from two centers were used to investigate the models.

Results

Validation with invasive electro-anatomical mapping data identified that computer models with fast endocardial conduction were able to predict the electrical activation with a mean distance errors of 9.2 ± 0.5 mm (CMR data) or (CT data) 7.5 ± 0.7 mm.

Conclusion

This study identified a simple rule-based fast endocardial conduction model, built using non-invasive clinical data that can be used to rapidly and robustly predict the electrical activation of the heart. Pre-procedural prediction of the latest electrically activating region to identify the optimal LV pacing site could potentially be a useful clinical planning tool for CRT procedures.

Keywords

Cardiac resynchronization therapy
Electrophysiology
Computational models
Patient-specific simulations

Abbreviations

CRT
cardiac resynchronization therapy
LBBB
left bundle branch block
LV
left ventricle
RV
right ventricle
EAM
electroanatomical mapping
CE CMR
contrast enhanced cardiac magnetic resonance
LAT
local activation time
CS
coronary sinus
DT MRI
diffusion tensor magnetic resonance imaging

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