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Accurate diagnosis of apical hypertrophic cardiomyopathy using explainable advanced electrocardiogram analysis
Rebecca K Hughes1,2, George D Thornton1,2, James W Malcolmson2,3
1Institute of Cardiovascular Science, University College London, Gower Street, London, UK.
Insights
Explainable advanced ECG (A-ECG) accurately diagnoses apical hypertrophic cardiomyopathy (ApHCM), even with subtle hypertrophy. This electrical analysis offers value beyond traditional imaging for ApHCM diagnosis.
Area of Science:
- Cardiology
- Medical Diagnostics
- Artificial Intelligence in Medicine
Background:
- Standard electrocardiograms (ECG) have limitations in diagnosing apical hypertrophic cardiomyopathy (ApHCM).
- ECG is crucial for initial cardiac assessment, often preceding advanced imaging.
- Subtle or relative hypertrophy in ApHCM can be challenging to detect with conventional ECG.
Purpose of the Study:
- To evaluate the diagnostic accuracy of explainable advanced ECG (A-ECG) for ApHCM.
- To determine if A-ECG can identify ApHCM when typical ECG features are absent.
- To assess the incremental value of A-ECG compared to cardiac imaging.
Main Methods:
- Analysis of standard resting 12-lead ECGs from patients with ApHCM and various comparator groups.
- Application of multivariable logistic regression and linear discriminant analysis for A-ECG measures.
- Comparison of A-ECG diagnostic performance against established benchmarks.
Main Results:
- A-ECG analysis demonstrated high diagnostic accuracy for ApHCM (AUC 0.982-0.989).
- Four key A-ECG measures effectively discriminated ApHCM from other cardiac conditions.
- Accurate diagnosis was achieved even in cases with relative hypertrophy.
Conclusions:
- Explainable A-ECG offers excellent diagnostic accuracy for ApHCM.
- A-ECG provides value beyond cardiac imaging, particularly in subtle hypertrophy cases.
- Integrating electrical (A-ECG) and anatomical (imaging) data may enhance future ApHCM strategies.
Aims:
Typical electrocardiogram (ECG) features of apical hypertrophic cardiomyopathy (ApHCM) include tall R waves and deep or giant T-wave inversion in the precordial leads, but these features are not always present. The ECG is used as the gatekeeper to cardiac imaging for diagnosis. We tested whether explainable advanced ECG (A-ECG) could accurately diagnose ApHCM.
Methods And Results:
Advanced ECG analysis was performed on standard resting 12-lead ECGs in patients with ApHCM [n = 75 overt, n = 32 relative (<15 mm hypertrophy); a subgroup of which underwent cardiovascular magnetic resonance (n = 92)], and comparator subjects (n = 2449), including healthy volunteers (n = 1672), patients with coronary artery disease (n = 372), left ventricular electrical remodelling (n = 108), ischaemic (n = 114) or non-ischaemic cardiomyopathy (n = 57), and asymmetrical septal hypertrophy HCM (n = 126). Multivariable logistic regression identified four A-ECG measures that together discriminated ApHCM from other diseases with high accuracy [area under the receiver operating characteristic (AUC) curve (bootstrapped 95% confidence interval) 0.982 (0.965-0.993)]. Linear discriminant analysis also diagnosed ApHCM with high accuracy [AUC 0.989 (0.986-0.991)].
Conclusion:
Explainable A-ECG has excellent diagnostic accuracy for ApHCM, even when the hypertrophy is relative, with A-ECG analysis providing incremental diagnostic value over imaging alone. The electrical (ECG) and anatomical (wall thickness) disease features do not completely align, suggesting that future diagnostic and management strategies may incorporate both features.
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