Diego di Bernardo

Origin on the electrocardiogram of U-waves and abnormal U-wave inversion

AIMSnSoon after the initial development of electrocardiography, U-waves were discovered in many normal subjects following the T-wave repolarisation waveform on the electrocardiogram. Various explanations have been offered for their origin, but none is universally accepted. We used our model of left ventricular repolarisation to explore the most common hypotheses for the genesis of U-waves.nnnMETHODSnRecently, we have shown that a computer model of left ventricular repolarisation was able to explain the formation of the characteristic shape of the T-wave, and we have now used this model to explore the most common hypotheses for the genesis of U-waves. The repolarisation phase of the action potentials in the model exhibited an after-potential. We investigated separately the effect on the 12-lead electrocardiogram of three different features of the model: the amplitude of the after-potential; dispersion of repolarisation in the left ventricle ranging from 20 to 100 ms; the timing of the after-potential, relative to the end of the principal action potential component, ranging from -100 to 100 ms.nnnRESULTSnWe show that delaying repolarisation in different regions of the heart cannot explain the U-wave, but show that the presence of after-potentials on the cardiac action potential do explain the U-wave polarity and other characteristic U-wave features. We also show that abnormal after-potential timing corresponds with abnormal U-wave inversion.nnnCONCLUSIONnOur model provides a realistic and simple solution to the problem of U-wave genesis.

Effect of changes in heart rate and in action potential duration on the electrocardiogram T wave shape

The mechanisms responsible for changes in T wave symmetry and amplitude with changes in heart rate and action potential duration were investigated. A computer model of normal left ventricular repolarization was used to simulate the T waves on the surface 12-lead ECG. The effect of heart rate changes was studied by varying the ratio between dispersion of repolarization (Disp) and action potential repolarization duration (APRD). With constant dispersion. as heart rate increases, APRD decreases and the ratio Disp/APRD increases. T waves were simulated while varying the Disp/APRD ratio from 3.6% to 100%. The T wave symmetry ratio measured from the areas either side of the peak (SRarea), the symmetry ratio from the times either side of the peak (SRtime) and the T wave amplitude (Tamplitude) were calculated from each simulated ECG. SRarea decreased from 1.42 to 0.77, SRtime from 1.75 to 1.04 and the Tamplitude increased from 0. 19 mV to 2.30 mV. The stability of results with variation in model characteristics was also investigated, by moving the heart +/- 20 mm on all three axes, rotating the heart axes by +/- 10 and by modifying all constants defining the action potential by +/- 5% and +/- 10%. T wave amplitude was sensitive to changes in heart position, as the heart was moved towards the body surface. However, T wave shape changed very little with heart position or rotation, with the SD of SRarea varying by less than 0.05 over an SRarea range of 0.65 for different values of Disp/APRD ratio. We have shown from our model that cardiac T waves increase in amplitude, and become more symmetric with their peaks becoming central as APRD shortens with increasing heart rate, agreeing with clinical observations. These results help to explain the T wave shape changes which occur when heart rate increases.

Quantification of T wave shape changes following exercise.

LANGLEY, P., et al.: Quantification of T Wave Shape Changes Following Exercise. T wave shape is increasingly used to provide insights into cardiac repolarization and, although shape is known to change as heart rate changes, there are no published quantitative clinical data. The aim of this study was to quantify these changes. Heart rate (HR), T wave amplitude, and two measures of T wave symmetry (SRarea—ratio of areas about the peak, SRtime—ratio of centrality of peak), were quantified over a period of 360 seconds following exercise in 20 healthy human subjects. As HR decreased, in all subjects the T wave became more asymmetrical (SRarea 20/20, SRtime 20/20, P < 0.0001). Resting reference HR and symmetry ratios were (mean ± SD), HR 63 ± 10 beat/min, SRarea 1.68 ± 0.25, and SRtime 2.13 ± 0.39. Fifty seconds postexercise, HR was significantly higher than reference at 92 ± 11 beat/min (P < 0.0001), and symmetry ratios were significantly less at SRarea 1.04 ± 0.15, SRtime 1.24 ± 0.36 (P < 0.0001). Significant differences in HR and both symmetry ratios remained at 300 seconds postexercise. Amplitude increases had returned to their reference values at 300 seconds. T wave shape was significantly more symmetrical at higher HRs. These findings confirm qualitative reports of shape changes.

Computer Model for Study of Cardiac Repolarization

Computer Model for Cardiac Repolarization. Introduction: We propose a new and simple method to model repolarization in the left ventricle and the corresponding T waves on the surface ECG.

Medical physics: Explaining the T-wave shape in the ECG

The heartbeat is recorded on an electro- cardiogram (ECG) as a characteristic trace determined by changes in the electrical activity of the heart muscle. The T wave is a component of this waveform that is associated with the repolarization phase of the action potentials. It is asymmetrical in healthy subjects, but tends to become symmetrical with heart disease. The reason for the T-wave shape is not clear. Here we show that T waves become more symmetrical as a result of an increase in the dispersion of the regional repolarization of cardiac muscle.

Dispersion of QT intervals: A measure of dispersion of repolarization or simply a projection effect?

QT interval dispersion may provide little information about repolarization dispersion. Some clinical measurements demonstrate an association between high QT interval dispersion and high morbidity and mortality, but what is being measured is not clear. This study was designed to help resolve this dilemma. We compared the association between different clinical measures of QT interval dispersion and the ECG lead amplitudes derived from a heart vector model of repolarization with no repolarization dispersion whatsoever. We compared our clinical QT interval dispersion data obtained from 25 subjects without cardiac disease with similar data from published studies, and correlated these QT dispersion results with the distribution of lead amplitudes derived from the projection of the heart vector onto the body surface during repolarization. Published results were available for mean relative QT intervals and mean differences from the maximum QT interval. The leads were derived from Uijen and Dower lead vector data. Using the Uijen lead vector data, the correlation between measurements of dispersion and derived lead amplitudes ranged from 0.78 to 0.99 for limb leads, and using the Dower values ranged from 0.81 to 0.94 for the precordial leads. These results show a clear association between the measured QT interval dispersion and the variation in ECG lead amplitudes derived from a simple heart vector model of repolarization with no regional information. Therefore, measured QT dispersion is related mostly to a projection effect and is not a true measure of repolarization dispersion. Our existing interpretation of QT dispersion must be reexamined, and other measurements that provide true repolarization dispersion data investigated.

Effect of Lead Exclusion for the Manual Measurement of QT Dispersion

LANGLEY, P., et al.: Effect of Lead Exclusion for the Manual Measurement of QT Dispersion. To investigate the effect of different lead exclusion criteria for the manual measurement of QT dispersion (QTd). Simultaneous 12‐lead ECGs from three groups of 25 subjects were studied; healthy normal subjects, subjects with a myocardial infarction, and subjects with arrhythmias. Leads were excluded with (1) small absolute T wave amplitudes, (2) small relative T wave amplitudes, and (3) small and/or large relative QT measurements. QTd was calculated as the QT range and assessed for its ability to differentiate between the normal and pathological groups. With exclusion of no leads or low absolute amplitude T waves (< 50 μV) significant differences were observed only between normal and myocardial infarct groups (P < 0.05). Significant differences between normal and both pathological groups were observed when excluding the lead with the smallest amplitude T wave or shortest QT (P < 0.05), or when two leads of either type were excluded (P < 0.005). There was good agreement between leads excluded by amplitude or QT (P < 0.01). Lead exclusion for QTd is important. Exclusion of the two smallest amplitude or two shortest QT leads from each subject produced the greatest differences between the normal and pathological groups.

Modelling cardiac repolarisation for the study of the T wave: effect of repolarisation sequence

Abstract The electrocardiogram is of major importance in the diagnosis of heart disease. Cardiac repolarisation is the result of the return to a resting state of myocardial cells, and is detected on the surface 12-lead ECG as the T wave. The exact mechanisms responsible for the T wave shape are not completely understood. In this work, using our computer model of left ventricular repolarisation, we investigated the effect of different action potential duration gradients on the T wave in order to understand which are the most important in determining T wave shape. Three different repolarisation sequences (no base to apex epicardial gradient, no posterior to septal wall gradient and no epicardial gradient) were simulated and the T waves on the 12-lead ECG were computed and compared with those resulting from a normal repolarisation sequence. Results show that T wave shape is little affected by the specific repolarisation sequence, although its polarity in the 12 leads is dependent upon it. We found that including only the epicardium to endocardium gradient, the most common T wave polarity pattern across the 12 leads was generated, while eliminating the posterior to septal wall gradient produced abnormal T wave inversion in leads V4 and V5. This suggests that the epicardium to endocardium gradient is the most important for producing the T wave shape. These results are in agreement with experimental evidence.

Explaining the T-wave shape in the ECG: Medical physics

The heartbeat is recorded on an electro- cardiogram (ECG) as a characteristic trace determined by changes in the electrical activity of the heart muscle. The T wave is a component of this waveform that is associated with the repolarization phase of the action potentials. It is asymmetrical in healthy subjects, but tends to become symmetrical with heart disease. The reason for the T-wave shape is not clear. Here we show that T waves become more symmetrical as a result of an increase in the dispersion of the regional repolarization of cardiac muscle.