Three-dimensional standard electrocardiogram: A first approach based on precordial leads

Traditional electrocardiography (ECG) is limited to two-dimensional (2D) representations, which restricts its ability to capture the full complexity of cardiac electrical activity. We propose a novel three-dimensional (3D) ECG methodology directly derived from standard 2D recordings, providing enhanced spatial insights without requiring additional hardware modifications. Additionally, we introduce a new formulation, which we term "almost-curvature", to optimize the detection of variations in acute ischemic states, which is one of the leading causes of mortality and exhibits sensitivity issues in diagnosis using traditional ECG methods.

To introduce the methodology for developing 3D ECG and evaluate its diagnostic utility in detecting morphological changes associated with acute myocardial ischemia through perimeter, curvature, and almost-curvature metrics.

We developed a methodology based on spherical-to-Cartesian coordinate transformations applied to standard ECG data from the PhysioNet database. For validation, we utilized datasets from patients with induced myocardial ischemia. We extracted perimeter, curvature, and almost-curvature metrics from both 3D and 2D ECG and compared them across different ischemic states. From method implementation to clinical validation, we used clustering analyses and statistical tests such as Anderson-Darling, Kolmogorov-Smirnov, Mantel, Shapiro-Wilk, Wilcoxon, and the Permutation test.

Statistical analysis revealed a correlation between the plane presenting standard deflections in the 3D ECG and the plane displaying the novel loops generated by our methodology. The almost-curvature metric demonstrated an enhanced capacity to detect variations between ischemic states, surpassing the diagnostic performance of traditional curvature metrics. While 2D analyses showed a reduction in curvature and perimeter during ischemia progression, 3D ECG analysis revealed an increase in these metrics, underscoring its ability to capture morphological changes that may be overlooked by conventional methods.

3D ECG analysis shows potential to enhance the detection of ischemic alterations, offering a more detailed spatial representation of cardiac electrical activity compared to traditional methods. By leveraging spherical-to-Cartesian transformations, our methodology integrates temporal and voltage dynamics into a unified framework, potentially revealing subtle morphological changes associated with ischemia. Although the methodology remains in its early developmental stage and requires further refinement, its promising diagnostic utility suggests it could significantly enhance cardiac diagnostics. Further studies are essential to validate its clinical applicability and address current limitations.