Evaluation of new vectorcardiography algorithms for identifying left ventricular hypertrophy and impaired systolic function
Janek Salatzki, Arne Kristian Schwarz, Sarah Wolfsteller, Nicolas Hein, Erika Poyo Medina, Norbert Frey, Henning Steen, Florian André, Alexander Passow, Univeritätsklinikum Heidelberg, Journal of Electrocardiology, Volume 97, July–August 2026, 154272.
See more than a standard ECG: Cardisiography—AI-based 3D vector cardiography—makes structural changes to the heart visible at an early stage. In a recent study conducted at Heidelberg University Hospital, the technology demonstrated high accuracy in detecting left ventricular hypertrophy and impaired cardiac function—quickly, non-invasively, and directly at the point of care.
Highlights
- VCG detects impaired systolic function and LVH with high diagnostic accuracy.
- A repolarization time-difference ratio identifies reduced ejection fraction with 83% accuracy.
- T-wave azimuth and magnitude are key markers of LVH on VCG.
- VCG enables rapid, interpretable non-invasive cardiac assessment.
Heart failure with reduced ejection fraction (HFrEF) and left ventricular hypertrophy (LVH) are among the most prevalent and prognostically significant forms of cardiac structural remodeling. Despite their clinical importance, both conditions are frequently underdiagnosed or detected at a relatively late stage in routine practice. This study provides a methodologically robust proof-of-concept for the diagnostic utility of artificial intelligence (AI)-assisted vectorcardiography in the detection of structural heart disease. From a clinical perspective, several aspects warrant particular attention:
- Methodological strengths: No specialist operator required, no ionizing radiation exposure, and no contrast agent administration. Data acquisition is completed within approximately four minutes, followed by fully automated analysis. This approach offers considerable scalability for implementation in primary care practices, emergency departments, and resource-constrained healthcare settings.
- Addressing an important diagnostic gap: Early identification of LVH and impaired left ventricular systolic function, particularly during asymptomatic stages, remains challenging with conventional ECG-based screening. AI-enabled VCG may represent a practical and clinically deployable bridge technology for earlier detection of structural cardiac disease.
- Immediate PDF report including individualized risk score
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