The Hodgkin-Huxley-Katz Prize Lecture: Heart digital twins: A new paradigm in arrhythmia medicine.

Digital twins offer a way to translate rich patient data into individualized models that can be interrogated rather than merely described. In cardiac electrophysiology this approach has advanced to the point where the geometry, fibrosis, adiposity, inflammation and genotype of an individual heart can be incorporated into biophysically grounded simulations. This review accompanies The Physiological Society's annual Hodgkin-Huxley-Katz Award Lecture, presented to Dr. Natalia Trayanova in recognition of her contributions to computational cardiology and its clinical translation. It surveys the body of work developed by Dr. Trayanova and her group at Johns Hopkins University, charting the arc from the application of patient-specific heart digital twins to reveal substrate determinants of arrhythmogenesis to their translation to sudden cardiac death risk prediction and guidance of catheter ablation for ventricular tachycardia and atrial fibrillation (AF). Across ventricular disease these studies showed that scar architecture, border-zone conduction slowing, repolarization gradients, adipose infiltration and genotype-specific remodelling can govern the emergence and stability of re-entrant circuits. In the atria digital twins clarified how fibrosis distribution and driver anchoring shape AF dynamics. Taken together this body of work demonstrates that heart digital twins satisfy the operative medical criterion of informing clinical decisions that realize value, including non-invasive sudden cardiac death risk stratification, pre-procedural ventricular tachycardia (VT) ablation target prediction in a prospective Food and Drug Administration Investigational Device Exemption (FDA-IDE) clinical trial and personalized AF ablation planning. The major challenge ahead is to convert these validated but still computationally intensive technologies into scalable, continuously updated tools that can be deployed routinely in clinical care.