Key result
Proposed blood flow ultrasound simulation method matches human aortic signals with ~13% error.
A proposed linear time variant model successfully simulates blood flow ultrasound radio frequency signals with a 13.02% error compared to real human aortic data.
Does not support clinical adoption of simulated signals; leaves open further validation in prospective studies.
This study aims to propose a computer simulation method for generating blood flow ultrasound signals. It mainly focuses on the simulation of radio frequency (RF) of moving objects in vessels, because RF signals contain more information than Doppler signal simulation. This method simulates RF signal on the basis of the acoustic field calculations. Furthermore, the resulting signal also includes Doppler Effect. The Doppler Effect is introduced while assuming the system is linear time variant (LTV). That is, when a scatterer moves, its spatial impulse response changes by time. Therefore, we could consider the desired Doppler Effect in the signals. Different velocity of a cardiac cycle is applied to the model and their corresponding frequency shifts are calculated by applying fast Fourier transform. The results of study show correct frequency shifts in the simulated signal. We further compared our simulated signal with a RF signal recorded from human aorta by a longitudinal scan. According to the results, the normalized root mean square error in one cardiac cycle between velocity profile of the simulated and experimental signals is 13.02% and that verifies the similarity of our proposed method to the real data.
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Khodabakhshi et al. (2011) studied this question. Computer simulation method for generating blood flow ultrasound signals vs. Experimental RF signal recorded from human aorta was evaluated on Normalized root mean square error in one cardiac cycle between velocity profile of the simulated and experimental signals. A proposed computer simulation method for generating blood flow ultrasound signals demonstrated a normalized root mean square error of 13.02% compared to experimental signals from a human aorta.
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