This paper shows the results of a preliminary study on the performance of new methods based on ultrasonic images parametrization, to estimate the arterial wall movements used for the evaluation of arterial stiffness, considered to be a predictor of cardiovascular events. The well-known technique of motion tracking in ultrasound image sequences was applied on cine loops scanned from subjects with different risks of suffering from cardiovascular disease (CVD). The motion of arterial walls was traced using displacement signals: Diameter, intima-media thickness (IMT) and longitudinal intima-media (IM) complex movement. The new methods used for the parametrization of the displacement signals were the average value (AV), effective or root mean square (RMS) value, and peak-to-peak motion amplitude estimate. A total of 79 subjects were analyzed in the study with 30 considered at low risk and 49 included in a preventive program for monitoring high CVD risk subjects. The results show a statistically significant difference between healthy volunteers and at-risk patients according to the AV of IMT, RMS values of longitudinal and radial motions and peak-to-peak amplitude of radial motion.
The purpose of this paper is a quantification of displacement parameters used in the imaging of brain tissue endogenous motion using ultrasonic radiofrequency (RF) signals. In a preclinical study, an ultrasonic diagnostic system with RF output was equipped with dedicated signal processing software and subject head–ultrasonic transducer stabilization. This allowed the use of RF scanning frames for the calculation of micrometer-range displacements, excluding sonographer-induced motions. Analysis of quantitative displacement estimates in dynamical phantom experiments showed that displacements of 55 µm down to 2 µm were quantified as confident according to Pearson correlation between signal fragments (minimum p ≤ 0.001). The same algorithm and scanning hardware were used in experiments and clinical imaging which allows translating phantom results to Alzheimer’s disease patients and healthy elderly subjects as examples. The confident quantitative displacement waveforms of six in vivo heart-cycle episodes ranged from 8 µm up to 263 µm (Pearson correlation p ≤ 0.01). Displacement time sequences showed promising possibilities to evaluate the morphology of endogenous displacement signals at each point of the scanning plane, while displacement maps—regional distribution of displacement parameters—were essential for tissue characterization.
Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is the quantitative evaluation of RF signal simulation uncertainties in resolution and contrast reproduction with the model of a phased array transducer. The method is based on three types of standard physical phantoms. Digital 3D models of those phantoms are composed of point scatterers representing the weak backscattering of the background material and stronger backscattering from inclusions. The simulation results of echoscopy with sector scanning transducer by Field II software are compared with the RF output of the Ultrasonix scanner after scanning standard phantoms with 2.5 MHz phased array. The quantitative comparison of axial, lateral, and elevation resolutions have shown uncertainties from 9 to 22% correspondingly. The echoscopy simulation with two densities of scatterers is compared with contrast phantom imaging on the backscattered RF signals and B-scan reconstructed image, showing that the main sources of uncertainties limiting the echoscopy RF signal simulation adequacy are an insufficient knowledge of the scanner and phantom’s parameters. The attempt made for the quantitative evaluation of simulation uncertainties shows both problems and the potential of echoscopy simulation in imaging technology developments. The analysis presented could be interesting for researchers developing quantitative ultrasound imaging and elastography technologies looking for simulated raw RF signals comparable to those obtained from real ultrasonic scanning.
Non‐invasive ultrasound (US) imaging enables the assessment of the properties of superficial blood vessels. Various modes can be used for vascular characteristics analysis, ranging from radiofrequency (RF) data, Doppler‐ and standard B/M‐mode imaging, to more recent ultra‐high frequency and ultrafast techniques. The aim of the present work was to provide an overview of the current state‐of‐the‐art non‐invasive US technologies and corresponding vascular ageing characteristics from a technological perspective. Following an introduction about the basic concepts of the US technique, the characteristics considered in this review are clustered into: 1) vessel wall structure; 2) dynamic elastic properties, and 3) reactive vessel properties. The overview shows that ultrasound is a versatile, non‐invasive, and safe imaging technique that can be adopted for obtaining information about function, structure, and reactivity in superficial arteries. The most suitable setting for a specific application must be selected according to spatial and temporal resolution requirements. The usefulness of standardization in the validation process and performance metric adoption emerges. Computer‐based techniques should always be preferred to manual measures, as long as the algorithms and learning procedures are transparent and well described, and the performance leads to better results. Identification of a minimal clinically important difference is a crucial point for drawing conclusions regarding robustness of the techniques and for the translation into practice of any biomarker.
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.
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