Personalized Digital Twins in Scar‐Dependent Ventricular Tachycardia: Mechanistic Insight, Clinical Translation, and the Limits of Computational Precision

Scar‐dependent ventricular tachycardia (VT) remains challenging to treat, with reported recurrence rates of 30%–50% within 2 years after catheter ablation. Conventional substrate mapping relies on electrogram‐based surrogates of arrhythmogenic tissue and may incompletely characterize intramural conduction pathways and substrate changes following ablation. Personalized cardiac digital twins integrate cardiac imaging with biophysical electrophysiological models to simulate virtual programmed stimulation at multiple sites and identify candidate re‐entrant pathways. This narrative review examines their biological and biophysical foundations, computational construction, validation, emerging clinical evidence, and barriers to clinical translation. Current workflows combine contrast‐enhanced cardiac imaging, image‐derived ventricular geometry, assigned tissue properties, and reaction–diffusion or reduced‐order electrophysiological formulations. Preclinical and clinical studies support the feasibility of reconstructing scar‐related conduction pathways and evaluating candidate ablation targets. In a prospective validation cohort, model‐derived predictions showed 81.3% sensitivity and 98.8% negative predictive value, but a positive predictive value of 21.7% for the study‐defined critical‐site classification. In the 10‐patient TWIN‐VT pilot, 6 of 7 patients with tested inducible VT became noninducible after the ablation of twin‐predicted targets alone; all 10 were noninducible at procedural completion, including 2 who were noninducible at baseline. These findings support early clinical feasibility but do not establish comparative efficacy or durable arrhythmia control. Important translational barriers include imaging and registration uncertainty, population‐derived electrophysiological parameters, simplified tissue and lesion representations, and limited validation across scar etiologies. Clinical translation will require independent multicenter validation, transparent reporting, risk‐informed model credibility assessment, and prospective comparative trials evaluating procedural and longer‐term clinical outcomes. Until such evidence is available, cardiac digital twins should remain investigational decision‐support tools that complement invasive electrophysiological assessment and clinical judgment. Trial Registration ClinicalTrials.gov identifier: NCT03536052