Statistical Methods of ECG Signal Processing in Diagnostics of Coronary Artery Disease

Objective: Coronary artery disease results in higher morbidity, mortality, and medical costs than any other illness in the developed world. The improvement of coronary artery disease non-invasive detection is still actual problem. The aim of this study was to increase the quality of non-invasive diagnostics of coronary artery disease with statistical technology of ECG signal processing for quantitative assessment the degree of myocardial ischemia and the coronary artery lesion. Methods and Results: The four minutes 12-channel electrocardiogram was used for the statistical technology of ECG signal processing to gain 200 PQRST complexes. It allowed calculating L criterion from relation of standard deviation to average value of 200 T-wave times and G-criterion the from relation of standard deviation to average value of 200 T-wave amplitudes in all 12 channels. The L and G criteria were compared by relation the maximum value in one channel to minimum value in another channel to get the second order L and G criteria. 139 patients with suspected coronary artery disease underwent elective coronary angiography and were examined by G and L criteria. Among patients with coronary angiography the values of second order L-criterion had a strong positive correlation with the value of coronary artery lesion (correlation factor r = +0.894). The values of G-criterion quantitatively reflect the severity of clinical presentation and confirm the functional classes. Conclusions: The offered statistical technology of quantitative assessment of electrocardiographic curve parameters allows indirectly assessing the coronary blood flow and the degree of ischemic process regardless the presence of risk factors and clinical presentation. The localization of maximum ischemic process according the appropriate leads can help in selection of stent implantation priority.