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Biotechnology - Radiology and Medical Imaging


Beat-to-Beat Vectorcardiographic Analysis of Ventricular Depolarization and Repolarization in Myocardial Infarction
Published: Wednesday, November 14, 2012
Author: Muhammad A. Hasan et al.

by Muhammad A. Hasan, Derek Abbott, Mathias Baumert

Objectives

Increased beat-to-beat variability in the QT interval has been associated with heart disease and mortality. The purpose of this study was to investigate the beat-to-beat spatial and temporal variations of ventricular depolarization and repolarization in vectorcardiogram (VCG) for characterising myocardial infarction (MI) patients.

Methods

Standard 12-lead ECGs of 84 MI patients (22 f, 63±12 yrs; 62 m, 56±10 yrs) and 69 healthy subjects (17 f, 42±18 yrs; 52 m, 40±13 yrs) were investigated. To extract the beat-to-beat QT intervals, a template-matching algorithm and the singular value decomposition method have been applied to synthesise the ECG data to VCG. Spatial and temporal variations in the QRS complex and T-wave loops were studied by investigating several descriptors (point-to-point distance variability, mean loop length, T-wave morphology dispersion, percentage of loop area, total cosine R-to-T).

Results

Point-to-point distance variability of QRS and T-loops (0.13±0.04 vs. 0.10±0.04, p< 0.0001 and 0.16±0.07 vs. 0.13±0.06, p< 0.05) were significantly larger in the MI group than in the control group. The average T-wave morphology dispersion was significantly higher in the MI group than in the control group (62°±8° vs. 38°±16°, p< 0.0001). Further, its beat-to-beat variability appeared significantly lower in the MI group than in the control group (12°±5° vs. 15°±6°, p< 0.005). Moreover, the average percentage of the T-loop area was found significantly lower in the MI group than the controls (46±17 vs. 55±15, p< 0.001). Finally, the average and beat-to-beat variability of total cosine R-to-T were not found statistically significant between both groups.

Conclusions

Beat-to-beat assessment of VCG parameters may have diagnostic attributes that might help in identifying MI patients.

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