Title |
Simulation of ultrasound RF signals backscattered from a 3D nodel of pulsating artery surrounded by tissue / |
Authors |
Makūnaitė, Monika ; Jurkonis, Rytis ; Lukoševičius, Arūnas ; Baranauskas, Mindaugas |
DOI |
10.3390/diagnostics12020232 |
Full Text |
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Is Part of |
Diagnostics.. Basel : MDPI. 2022, vol. 12, iss. 2, art. no. 232, p. 1-21.. ISSN 2075-4418 |
Keywords [eng] |
carotid artery ; field II ; motion simulation ; scatterers ; ultrasound |
Abstract [eng] |
Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous tissue micro-motions currently being studied for tissue elastography. Methods based on artery motion detection are not applied in clinical practice these days, because they must be carefully investigated in silico and in vitro before wide usage in vivo. The purpose of this paper is to propose a dynamic 3D artery model capable of reproducing the biomechanical behavior of human blood vessels surrounded by elastic tissue for endogenous deformation elastography developments and feasibility studies. The framework is based on a 3D model of a pulsating artery surrounded by tissue and simulation of linear scanning by Field II software to generate realistic dynamic RF signals and B-mode ultrasound image sequential data. The model is defined by a spatial distribution of motions, having patient-specific slopes of radial and longitudinal motion components of the artery wall and surrounding tissues. It allows for simulating the quantified mechanical micro-motions in the volume of the model. Acceptable simulation errors calculated between modeled motion patterns and those estimated from simulated RF signals and B-scan images show that this approach is suitable for the development and validation of elastography algorithms based on motion detection. |
Published |
Basel : MDPI |
Type |
Journal article |
Language |
English |
Publication date |
2022 |
CC license |
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