Anatomical-electrical coupling of cardiac axes: Definitions and population variability for advancing personalised ECG...

Electrocardiogram (ECG) recordings are affected by the heart's three-dimensional orientation within the thorax, i.e., the anatomical axis. Various cardiac conditions can cause the anatomical axis to shift and/or alter the pattern of electrical activation, leading to changes in the electrical axis. Nevertheless, there remains a lack of a formal, population-level study of the interplay between the cardiac anatomical and electrical axes and the factors that affect them. In this context, this study aimed to: (1) propose standardised definitions for the cardiac anatomical and electrical axes, (2) characterise their population-wide interplay in healthy conditions, (3) evaluate the impact of hypertension on their distribution and (4) identify associations with phenotypical and disease characteristics. Using cardiac magnetic resonance images and 12-lead ECGs from ~39,000 UK Biobank participants, patient-specific, paired biventricular geometries and vectorcardiograms were constructed. Five anatomical and four electrical axis definitions were computed, with the optimal pair of definitions selected based on their mutual alignment in 3D space within 28,000 healthy subjects. Accordingly, the anatomical axis was defined as the vector from the apex to the spatial centre of the four valves, and the electrical axis as the direction of the maximum QRS dipole. Mean angular separation in 3D, [Formula: see text], was 145.0° ± 16.8° in the healthy cohort. The electrical axes exhibited a much larger variability, and strong evidence of anatomical-electrical coupling was identified. Increasing BMI notably affected the anatomical axis, rotating the heart more horizontally-a pattern mirrored by the electrical axis. Both axes were also significantly influenced by sex and, to a lesser extent, age. The axes were then studied in the sub-cohort of ~3,500 UK BioBank participants with primary hypertension, where a similar rotational pattern as that with increasing BMI was revealed. Finally, phenome-wide association studies in the 39,000 participants reveal associations between the axes angular metrics and phenotypes signalling an increased afterload, and an association to hypertension among other clinical conditions. These findings underscore the complex anatomical-electrical interplay and highlight the potential of cardiac axes biomarkers for an improved clinical ECG interpretation and disease characterisation.