Abstract
The Doppler ultrasound technique is used to detect vascular stenosis as a non-invasive procedure. To look for characteristics of Doppler ultrasound signals that are susceptible to stenosis, an accurate model of the Doppler ultrasound signal is required. This study models Doppler ultrasound waves from blood flow through stenotic arteries of varying degrees. In this model, it was expected that random scattering points will move based on their velocity. The Doppler influence was also included by modifying the form of the scattered signal at any time. Modeling the blood flow pattern through arteries helped identify the scattering point’s velocity profile and Doppler spectrum. The Tu and Devil model was used to consider a cosine stenosis shape because it is sufficiently similar to the natural shape of stenosis in the arteries. According to the Womersley model, the input flow to the stenotic zone was the same as the pulsatile blood flow in the vessel. As a result, the flow amplitude and Reynolds number changes will be near to reality. The fluid was deemed as non-Newtonian in the form of the power law to provide a more precise approximation to blood. When the calculated velocity profile was compared to the applied input value, the error rate was 6% for both normal and stenotic (70%) situations, validating the model’s accuracy in mimicking Doppler signals. This new computer model can be used to evaluate spectral analysis methods on simulated Doppler signals with clinically important underlying flow patterns.
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Mohsen Mehrabi, Nafise Salek, Sara Vosoughi, and Hassan Ranjbar. The first draft of the manuscript was written by Mohsen Mehrabi and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Mehrabi, M., Salek, N., Vosoughi, S. et al. Modeling doppler ultrasound blood flow signals in vessels with various stenosis degrees. J Eng Math 138, 7 (2023). https://doi.org/10.1007/s10665-022-10250-7
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DOI: https://doi.org/10.1007/s10665-022-10250-7