14 research outputs found

    Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material

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    A key step toward implementing quantitative ultrasound techniques in a clinical setting is demonstrating that parameters such as the ultrasonic backscatter coefficient (BSC) can be accurately estimated independent of the clinical imaging system used. In previous studies, agreement in BSC estimates for well characterized phantoms was demonstrated across different laboratory systems. The goal of this study was to compare the BSC estimates of a tissue mimicking sample measured using four clinical scanners, each providing RF echo data in the 1-15 MHz frequency range. The sample was previously described and characterized with single-element transducer systems. Using a reference phantom for analysis, excellent quantitative agreement was observed across the four array-based imaging systems for BSC estimates. Additionally, the estimates from data acquired with the clinical systems agreed with theoretical predictions and with estimates from laboratory measurements using single-element transducers

    Viscoelastic Characterization of in vivo Human Dermis Using High-Frequency Ultrasonic Crawling Wave Elastography

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    8 pags., 5 figs., 1 tab.High-frequency (center frequency of 18MHz) ultrasound was combined with crawling wave elastography to characterize skin viscoelastic properties in two anatomical sites (i.e., thigh and forearm) in humans in the range of 200-400 Hz. The Voigt model was used to obtain shear elasticity and shear viscosity estimates. The forearm's mean shear elasticity and shear viscosity were 6 kPa and 5.5 Pa.s, respectively, exhibiting significantly higher values than in the thigh (3.4 kPa and 3.2 Pa.s, respectively, p < 0.05). These results suggest that skin viscoelastic properties can be estimated in vivo using high-frequency crawling wave elastography and show translation potential for future application in the clinical screening of skin disorders.This work was supported by InnovatePeru/FINCYT Grant PIAP-3-P-872-14Peer reviewe
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