An arrayed-range-gate data acquisition for spatial distribution analysis of myocardial tissue vibration from stenosis in coronary Doppler vibrometry

Coronary Doppler vibrometry (CDV) is a non-invasive diagnosis to detect vibrations from stenosis in coronary artery using ultrasound. Although recent CDV shows considerable sensitivity and specificity in diagnosing coronary artery disease, there still remains a serious problem that normal subjects can also have high-frequency components in vibration. We developed new data acquisition and analysis algorithms that focus on the spatial distribution of high-frequency vibration in myocardial tissue. Our purpose is to observe the location-dependent variation of vibration in myocardial tissue. We recruited total 33 subjects in a hospital clinical study; four are known as patients who have coronary artery stenosis (over 50 % occlusion in coronary angiography) and the other 29 subjects are normal. We use 12 range gates in a view of echocardiography. Six range gates are located near stenosis (left anterior descending (LAD)) and the other six are located at normal tissue (or right coronary artery (RCA)). We define the segment vibration index (SVI) as the proportion of high-frequency component intensity (400 Hz ~ 800 Hz) to total intensity (100 Hz ~ 800Hz) in early diastole period. In addition, we define the myocardial tissue vibration distribution index (MVDI) as the ratio of the standard deviation of SVI in stenosis (or LAD) segments to that of SVI in normal (or RCA) segments. Thus, it is expected that myocardial tissue vibrations caused by stenosis can give a spatial distribution of vibration intensity, i.e., a large MDVI. Our proposed MDVI algorithm effectively classifies normal subjects and patients with sensitivity of 75% and specificity of 83%. This result shows that the patients with coronary artery disease tend to have higher MDVI value than normal subjects.