Development of Automated 12-Lead QT Dispersion Algorithm for Sudden Cardiac Death

Abstract

A single global QT interval measurement from the 12 lead ECG has been the standard measure, but recently there has been a great interest in the distribution of the QT intervals, at a given instant of time, across the 12 lead Electrocardiogram (ECG) leads. This parameter is called as QT dispersion (QTd). The QTd is emerging as an important new clinic tool as it has proposed as a marker of the risk of sudden cardiac death after Myocardium Infarction (MI). However, the measured QTd values vary among different studies around the world in term of the mean and the standard deviation. This research is aimed to develop an automatic algorithm to compute QTd for patients in Malaysia. DSP techniques were applied to 12 lead ECG signals to develop algorithm to facilitate offline automatic QT interval analysis. The results are statistically represented in terms of the mean and standard deviation, SD (mean ± SD). A threshold determined from Gaussian probability distribution function (pdf) is used to evaluate the significance difference of QTd between the non-MI patients and MI patients. The characteristic function is used to justify the discrimination of QTd between the non-MI and MI patients. A total number of 432 ECG recordings (36 patients X 12 leads per patient) were analyzed. It is found that the mean value of QTd for non-MI and MI group is 37.28 ± 11.13ms (p<0.05) and 66.17 ± 13.95ms (p<0.05) respectively. The QTd for non-MI and MI have the sensitivity of 88.89%. The threshold found is 50ms. Thus, QTd index is a clinically useful diagnostic adjunct in discriminating between non-MI patients and patients with MI. In conclusion, the QTd values are significantly higher in patients with MI compared to non-MI patients.