Ultrasound in medicine & biology · 2024
Estimation of In Vivo Human Carotid Artery Elasticity Using Arterial Dispersion Ultrasound Vibrometry.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Roy Tuhin, Lee Hyoung-Ki, Capron Charles B, Lopez-Jimenez Francisco, Hesley Gina K, Greenleaf James F, Urban Matthew W, Guddati Murthy N
Аннотация
OBJECTIVE: Arterial stiffening serves as an early indicator for a variety of cardiovascular diseases. Arterial Dispersion Ultrasound Vibrometry (ADUV) is a method that leverages acoustic radiation force to stimulate arterial wall motion, assess wave propagation characteristics, and subsequently calculate the arterial shear modulus. Previously, we introduced an inversion technique based on a guided cylindrical wave model, which proved effective in rubber tube phantom experiments. In this study, we broaden the scope of our investigation from phantom experiments to in vivo examination of common carotid arteries in human subjects, identify the challenges, and provide solutions, leading to a systematic protocol for ADUV application and robust estimation of the elastic modulus of common carotid arteries.
METHODS: We achieve this by analyzing ADUV data from 59 subjects categorized as (a) confirmed atherosclerotic cardiovascular disease (n = 27), (b) with cardiovascular risk factors (n = 20), and (c) healthy (n = 12). A crucial aspect of this work is the development of metrics to differentiate high-quality ADUV data from unusable data.
RESULTS AND CONCLUSIONS: With the proposed metrics, in our cohort, we observed 82% of diameter data and 78% of motion data as usable data. Future work will involve applying this protocol to a larger cohort with subsequent statistical analysis to assess and validate the resulting biomarkers.
METHODS: We achieve this by analyzing ADUV data from 59 subjects categorized as (a) confirmed atherosclerotic cardiovascular disease (n = 27), (b) with cardiovascular risk factors (n = 20), and (c) healthy (n = 12). A crucial aspect of this work is the development of metrics to differentiate high-quality ADUV data from unusable data.
RESULTS AND CONCLUSIONS: With the proposed metrics, in our cohort, we observed 82% of diameter data and 78% of motion data as usable data. Future work will involve applying this protocol to a larger cohort with subsequent statistical analysis to assess and validate the resulting biomarkers.