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.
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