Prediction of sudden cardiac death (SCD) in the inherited cardiac conditions (ICC) remains challenging owing to complexities in the geno-phenotypic relationship and the limitations of current risk stratification techniques. This was demonstrated in a retrospective study we undertook in our cohort of patients with Brugada Syndrome and Hypertrophic Cardiomyopathy, highlighting the need to improve upon current risk stratification in these conditions.
Whilst models of arrhythmogenesis predict that non-uniform recovery of excitation promotes ventricular fibrillation, this can be difficult to evaluate in patients using conventional cardiac investigative tools that have limited spatial resolution. As autonomic tone has also been implicated in modulating arrhythmic risk in these conditions, we hypothesized that high-resolution characterisation of the electrophysiological substrate during physiological stress can identify at risk individuals.
To address the hypothesis, we evaluated the ability of electrocardiographical imaging (ECGi) to detect dynamic changes in whole heart depolarization and repolarization patterns following pharmacological and physiological stressors in patients with inherited cardiac conditions. ECGi is a non-invasive tool that utilises body surface potentials from a 252 electrode vest. The system applies inverse solution mathematics to reconstruct >1200 unipolar electrograms to provide detailed information on depolarization and repolarization patterns on a digitised epicardial heart surface.
By measuring the activation recovery interval, we demonstrated that patients with an ICC and previous aborted SCD events had a significantly greater increase in global dispersion of repolarization following exercise than those without previous aborted SCD events. We also observed the development of regional conduction slowing on ECGi 3D activation maps that occurred more frequently in individuals with previous SCD events than those without and that these conduction and repolarisation abnormalities returned to baseline following a further period of recovery. These dynamic changes suggest a role for autonomic stimulation in augmenting the arrhythmogenic substrate and identifying those at higher risk for SCD.

We subsequently developed the Ventricular Conduction Stability (V-CoS) test as a method to automatically and objectively quantify and localise the development of spatial heterogeneities in conduction following exertion. On testing this new method in a cohort of ICC patients, we found that there was a small degree of inter-operator, beat-to-beat and test re-test variability, making it a suitable and reliable method with which to assess the development of non-uniform recovery of excitation.
Lastly, we applied the V-CoS test to a cohort of patients with different types of ICC which included Brugada Syndrome, Hypertrophic Cardiomyopathy and idiopathic Ventricular Fibrillation. Using this technique, we observed that exertion produced lower V-CoS scores, or greater amounts of spatial heterogeneity, in SCD survivors compared to those without previous life threatening arrhythmic events regardless of the underlying pathology. The data suggest the clinical applicability of this tool as a potential risk stratifier for different types of ICC.
In conclusion, we provide evidence that the arrhythmogenic substrate of the ICCs appears to be augmented by exercise and can be characterised non-invasively with high resolution electrocardiographical imaging.