Effects of parameters on the accuracy and precision of ultrasound-based local pulse wave velocity measurement: a simulation study.

Quantification of arterial stiffness, such as pulse wave velocity (PWV), is increasingly used in the risk assessment of cardiovascular disease. Pulse wave imaging (PWI) is an emerging ultrasound-based technique to noninvasively measure the local PWV instead of the global PWV, as in conventional methods. In PWI, several key parameters, including the frame rate of ultrasound imaging, motion estimation rate (MER), number of scan lines, image width, PWV value, and sonographic signal-to-noise ratio (SNRs), play an important but still unclear role in the accuracy and precision of PWV measurement. In this study, computer simulations were performed to investigate the fundamental effects of these parameters on the PWV measurement. The pulse waveform was estimated by speckle tracking on ultrasound RF signals acquired at a frame rate of 2083 Hz from a location on the common carotid artery of a healthy subject. By applying different time delays on the estimated waveform based on specific PWI parameters, the pulse waveforms at others locations were simulated. Ultrasound RF signals of the artery during the pulse wave propagation were generated from a 2-D convolutional image formation model. The PWI technique was applied to estimate the PWV at different values of frame rate, MER, number of scan lines, image width, PWV, and SNRs. The performance of the PWV estimation was evaluated by measuring the relative error, coefficient of variation (CV) and coefficient of determination (R(2)). The results showed that PWVs could be correctly measured when the frame rate was higher than a certain value (i.e., minimum frame rate), below which the estimated error increased rapidly. The minimum frame rate required for PWV estimation was found to increase with the value of PWV. An optimal MER was found (i.e., about 200 Hz) and allowed better performance of PWV measurement. The CV of PWV estimation decreased and R(2) increased with number of scan lines and image width, indicating that the performance of the PWV estimation could be improved with a larger number of scan lines and image width. For a given sufficiently high frame rate, a higher PWV value was found to deteriorate the PWV estimation, as indicated by an increasing CV and decreasing R(2). The simulation results were in good agreement with the theoretical analysis. Finally, high-quality PWV estimation could be obtained as long as the SNRs was higher than about 30 dB. The quantitative effects of the key parameters obtained from this study might provide important guidelines for parameter optimization in ultrasound-based local PWV measurement in vivo.