A novel computational method can rapidly personalize biophysical ionic models from standard catheter measurements to predict spiral wave stability and identify potential ablation targets in atrial fibrillation.
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May inform personalized AF ablation strategies; hypothesis-generating from animal data, clinical validation required.
Identifying the atrial tissue that is capable of supporting sustained re-entrant spiral wave activation patterns offers a potential ablation target for atrial arrhythmias. Current strategies for identifying this substrate require the patient to be in atrial fibrillation and require a large specialized catheter or an inverse ECG vest. We propose a novel method to personalize biophysical ionic models from standard multi-electrode catheter measurements and to predict spiral wave stability using computer simulations of a tissue region.
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Corrado et al. (2016) studied this question.
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