The age of computational cardiology and future of long-term ablation target prediction for ventricular tachycardia

Moinuddin, Arsalan ORCID: https://orcid.org/0000-0002-4242-1714, Ali, Syed Yusuf, Goel, Ashish, Sethi, Yashendra, Patel, Neil, Kaka, Nirja, Satapathy, Prakasini, Sah, Ranjit, Barboza, Joshuan J and Suhail, Mohammed K (2023) The age of computational cardiology and future of long-term ablation target prediction for ventricular tachycardia. Frontiers in Cardiovascular Medicine, 10. Art 1233991. doi:10.3389/fcvm.2023.1233991

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Abstract

Ventricular arrhythmias, particularly ventricular tachycardia, are ubiquitously linked to 300,000 deaths annually. However, the current interventional procedure-the cardiac ablation-predict only short-term responses to treatment as the heart constantly remodels itself post-arrhythmia. To assist in the design of computational methods which focuses on long-term arrhythmia prediction, this review postulates three interdependent prospectives. The main objective is to propose computational methods for predicting long-term heart response to interventions in ventricular tachycardia Following a general discussion on the importance of devising simulations predicting long-term heart response to interventions, each of the following is discussed: (i) application of "metabolic sink theory" to elucidate the "re-entry" mechanism of ventricular tachycardia; (ii) application of "growth laws" to explain "mechanical load" translation in ventricular tachycardia; (iii) derivation of partial differential equations (PDE) to establish a pipeline to predict long-term clinical outcomes in ventricular tachycardia.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Ventricular tachycardia; Catheter ablation; Computational cardiology; Metabolic sink theory; Precision medicine
Subjects:	R Medicine > R Medicine (General)
Divisions:	Schools and Research Institutes > School of Education, Health and Sciences
Depositing User:	Susan Turner
Date Deposited:	18 Oct 2023 11:49
Last Modified:	30 Mar 2026 16:00
URI:	https://eprints.glos.ac.uk/id/eprint/13324

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