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Automated interpretation of the 12-lead ECG has remained an underpinning interest in decades of research that has seen a diversity of computing applications in cardiology.
The application of computers in cardiology began in the 1960s with early research focusing on the conversion of analogue ECG signals (voltages) to digital samples. Alongside this, software techniques that automated the extraction of wave measurements and provided basic diagnostic statements, began to emerge. In the years since then there have been many significant milestones which include the widespread commercialisation of 12-lead ECG interpretation software, associated clinical utility and the development of the related regulatory frameworks to promote standardised development.
In the past few years, the research community has seen a significant rejuvenation in the development of ECG interpretation programs. This is evident in the research literature where a large number of studies have emerged tackling a variety of automated ECG interpretation problems. This is largely due to two factors. Specifically, the technical advances, both software and hardware, that have facilitated the broad adoption of modern artificial intelligence (AI) techniques, and, the increasing availability of large datasets that support modern AI approaches.
In this article we provide a very high-level overview of the operation of and approach to the development of early 12-lead ECG interpretation programs and we contrast this to the approaches that are now seen in emerging AI approaches. Our overview is mainly focused on highlighting differences in how input data are handled prior to generation of the diagnostic statement.
Background: The 12-lead ECG is spatially limited in diagnosing cardiac abnormalities. Additional leads (right sided and posterior leads) are inconvenient in a clinical setting, however, they can be derived. In this paper we report on the development of coefficients to allow derivation of right sided and posterior leads.
Method: Analysis was performed using body surface potential maps (BSPM) recorded from 910 patients in two centres. Recordings were made up of healthy controls (n=314), peak balloon inflation during elective percutaneous coronary angioplasty (n=88), myocardial infarction (n=271) and left-ventricular hypertrophy (n=237). All recordings were expanded to the 352-node Dalhousie torso. Coefficients to allow derivation of right sided and posterior leads were generated by linear regression. Further coefficients from a previously reported study were used for performance comparisons.
Results: Correlation coefficients between recorded and derived leads were significantly improved using the new coefficients (p<0.05) in leads V7-V12.
Conclusion: We have developed coefficients that allow the derivation of 10 additional leads from the 12-lead ECG.
Background: We have previously reported on the potential of patch-based ECG leads to observe changes typical during ischaemia. In this study we aim to assess the utility of patch-based leads in the detection of these changes.
Method: Body surface potential maps (BSPM) from subjects (n=45) undergoing elective percutaneous coronary angioplasty (PTCA) were used. The short spaced lead (SSL), that was previously identified as having the greatest ST-segment change between baseline and peak balloon inflation (PBI), was selected as the basis for a patch based lead system. A feature set of J-point amplitudes for all bipolar leads available within the same 100 mm region were included (n=6). Current 12-lead ECG criteria were applied to 12-lead ECGs for the same subjects to benchmark performance.
Results: The previously identified single SSL achieved sensitivity and specificity of 87% and 71% respectively using a Naive Bayes classifier. Adding other combinations of leads to this did not improve performance significantly. The 12-lead ECG performance was 62/93% (sensitivity/specificity).
Conclusion: This study suggests that short spaced leads can be sensitive to ischaemic ECG changes. However, due to the short distance between leads, they lack the specificity of the 12-lead ECG.