2021
DOI: 10.1063/5.0058050
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Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications

Abstract: Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From … Show more

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Cited by 28 publications
(13 citation statements)
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“…However, a priori sensitivity analysis of varying tissue thickness indicated that overall results do not change since temperature decreases rapidly with tissue depth and significant heating only occurs in the vicinity of the electrode. Because of clinical applications, however, a patient-specific image-based realistic geometry will be mandatory for maximizing model reliability and further improving its predictability ( Sung et al, 2021 ).…”
Section: Discussionmentioning
confidence: 99%
“…However, a priori sensitivity analysis of varying tissue thickness indicated that overall results do not change since temperature decreases rapidly with tissue depth and significant heating only occurs in the vicinity of the electrode. Because of clinical applications, however, a patient-specific image-based realistic geometry will be mandatory for maximizing model reliability and further improving its predictability ( Sung et al, 2021 ).…”
Section: Discussionmentioning
confidence: 99%
“…These 3D computational models entail a biophysical approach from the cell-scale to the organ-scale and are specific to each patient's disease and resultant remodeling. Perhaps uniquely among risk stratification methodologies, virtual hearts evaluate how triggers from different locations will interact with the substrate to initiate VA, potentially providing mechanistic insights into how and VAs can develop in the patient heart ( 63 ). This approach was initially demonstrated in patients with ICM and ICDs; wherein virtual hearts were superior to clinical risk factors in predicting VA ( 64 ).…”
Section: Cardiac Magnetic Resonance Imagingmentioning
confidence: 99%
“…Considerable efforts have been made in the last decade to produce digital twins for clinical applications and cardiac modelling has been among the fastest growing fields. Leaving aside the wealth of literature dealing with individual parts of the heart, recent examples include the computational investigation of electromechanical features [1][2][3] , the influence of cardiac contraction on the electrocardiogram (ECG) 4 and of the heart rate variability 5 ; recent review papers 6,7 give a detailed account of whole-heart electromechanical models.…”
Section: Introductionmentioning
confidence: 99%