Key result
Bi-ventricular pacing simulations on a patient-specific model showed that optimal electrode locations for CRT differ depending on whether a uniform or dissimilar local conductivity profile is used.
Why the study?
Up to 30% of CHF patients do not respond to CRT, partly due to inadequate pacing lead positioning, making patient stratification and CRT optimization challenging.
Does the choice of myocardial conductivity parameter identification approach (uniform vs. dissimilar local conductivity) affect the predicted optimal zones for bi-ventricular pacing in a personalized heart model?
Does the choice of myocardial conductivity parameter identification approach (uniform vs. dissimilar local conductivity) affect the predicted optimal zones for bi-ventricular pacing in a personalized heart model?
Accurate prediction of optimal electrode location for CRT requires personalized models that account for structural and functional parameters of myocardial tissue, such as local conductivity.
Caution in uniform-conductivity CRT models; leaves open whether heterogeneity improves human lead placement.
Up to 30% of chronic heart failure (CHF) patients undergoing cardiac resynchronization therapy (CRT) do not respond to the treatment. Low CRT response can be associated with inadequate pacing lead positioning in ventricles not accounting for individual structural abnormalities in myocardium. Therefore, patient stratification for CRT, operation planning and optimization of CRT device settings remain a challenge. Personalized heart computer models based on clinical data may be useful for the prediction of the optimal zones for bi-ventricular pacing. Accurate model personalization is computationally expensive and time-consuming task depending on the criteria for parameter identification problem and numerical approach to solve the task. The aim of the study is to compare results of bi-ventricular pacing simulations on a patient specific model of the heart geometry with different parameter sets for myocardial conductivity based on different parameter identification approaches. We used CT images of a patient heart with annotated zone of the post-infarction scar for building a detailed anatomical model of the ventricles. For identification of myocardial conductivity parameters in the model, we used data from clinical surface ECG recordings from 191 electrodes on the torso. Two different approaches for solving identification problem were examined (uniform conductivity versus dissimilar local conductivity) and model simulations of the ventricular activation and ECG were compared under varied combinations of myocardial segments for bi-ventricular stimulation. We showed that the location of ventricular segments providing for optimal response to pacing in terms of a shortest total activation time, QRS complex duration, and low electrical dissynchrony indices may differ depending on the myocardial conductivity profile. Our results suggest that the structural and functional parameters of myocardial tissue are essential for accurate prediction of the optimal electrode location that could be used in the clinical practice for pre-operational CRT planning.
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Bazhutina et al. (2021) studied Chronic heart failure (n=1). Patient-specific heart computer model with dissimilar local conductivity vs. Model with uniform conductivity was evaluated on Optimal response to pacing (shortest total activation time, QRS complex duration, and low electrical dissynchrony indices). Bi-ventricular pacing simulations on a patient-specific model showed that optimal electrode locations for CRT differ depending on whether a uniform or dissimilar local conductivity profile is used.
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