Estimation of Arterial Stiffness by Time–Frequency Analysis of Pulse Wave

2018

In our studies on ultrasonic elasticity assessment, minute change in the thickness of the arterial wall was measured by the phased-tracking method. However, most images in carotid artery examinations contain multiple-reflection noise, making it difficult to evaluate arterial wall elasticity precisely. In the present study, a modified phased-tracking method using the pulse inversion method was examined to reduce the influence of the multiple-reflection noise. Moreover, aliasing in the harmonic components was corrected by the fundamental components. The conventional and proposed methods were applied to a pulsated tube phantom mimicking the arterial wall. For the conventional method, the elasticity was 298 kPa without multiple-reflection noise and 353 kPa with multiple-reflection noise on the posterior wall. That of the proposed method was 302 kPa without multiple-reflection noise and 297 kPa with multiple-reflection noise on the posterior wall. Therefore, the proposed method was very robust against multiple-reflection noise.

Section: Introductionmentioning

confidence: 99%

Accuracy improvement in measurement of arterial wall elasticity by applying pulse inversion to phased-tracking method

Miyachi

Arakawa²,

2018

“…The pulse wave generated with the heart beat propagates toward the periphery of the arterial wall and is reflected at vascular bifurcations and peripheral vessels. 60) Nevertheless, PWV is calculated on the assumption that the pulse wave has only an incident component. Therefore, local lesions on the order of several millimeters to tens of millimeters may not be evaluated correctly.…”

Section: Introductionmentioning

confidence: 99%

Local pulse wave velocity estimated from small vibrations measured ultrasonically at multiple points on the arterial wall

Ito

Arakawa

2018

Pulse wave velocity (PWV) is used as a diagnostic criterion for arteriosclerosis, a major cause of heart disease and cerebrovascular disease. However, there are several problems with conventional PWV measurement techniques. One is that a pulse wave is assumed to only have an incident component propagating at a constant speed from the heart to the femoral artery, and another is that PWV is only determined from a characteristic time such as the rise time of the blood pressure waveform. In this study, we noninvasively measured the velocity waveform of small vibrations at multiple points on the carotid arterial wall using ultrasound. Local PWV was determined by analyzing the phase component of the velocity waveform by the least squares method. This method allowed measurement of the time change of the PWV at approximately the arrival time of the pulse wave, which discriminates the period when the reflected component is not contaminated.

“…The PWV method has been developed to measure the elasticity of the arterial wall. [13][14][15] Propagation of the pressure wave along the arterial tree is evaluated in this noninvasive diagnostic method. Although it is useful for evaluation of global elasticity such as from the heart to the femoral artery, regional elasticity cannot be evaluated.…”

Section: Introductionmentioning

confidence: 99%

Automated detection of arterial wall boundaries based on correlation between adjacent receive scan lines for elasticity imaging

Miyachi

Hasegawa

2015

In our series of studies on the ultrasonic assessment of the regional elasticity of the arterial wall, the change in the thickness of the arterial wall caused by the heartbeat was measured by the ultrasonic phased-tracking method. In the measurement of elasticity, the boundaries of the anterior and posterior walls must be assigned in advance. Currently the boundaries are manually determined by the operator, which is time-consuming and results in observer variability. In this paper, we propose an automated method for the detection of arterial wall boundaries using multiscale dynamic programming, in which the cost function includes the correlation term between ultrasonic echoes in adjacent receive scan lines. The correlation term enables boundary detection that is more robust than conventional methods against noises. The effectiveness of the proposed method was validated using a phantom and applied to the in vivo measurements of carotid arteries. The root mean square error between the results obtained by the proposed method and the manual assignment of the boundaries was significantly improved.