The influence of acoustic impedance mismatch on poststenotic pulsed-doppler ultrasound measurements in a coronary artery model

Abstract

AP. The influence of acoustic impedance mismatch on poststenotic pulsed-Doppler ultrasound measurements in a coronary artery model. Ultrasound Med Biol. 1996;22:623-634 and 12%, and then under stenosed conditions for the 0% and 7% mismatch cases.. For the zero mism.tch case, the Doppler spectra could be readily interpreted in terms of fluid mechankal phenomena. When mismatch was present, the spectra rrom Poiseuille Dow exhibited multiple peaks which could not be directly related to the ve10clty prome. Also, the spectra from stenosed flow with a mismatch of 7% were similar to those from tbe zero mismatch case but did not exhibit the specific flow-related reatuns as clearly. These results indicate that the Impedance mismatch alters the acoustic environment inskle tbe model and that this causes artifact In the Doppler spectra.

Feasibility of Encord Artificial Intelligence Annotation of Arterial Duplex Ultrasound Images

“…In terms of overall clinical application, the field of ultrasound (US) has presented substantial opportunities for the integration of AI. Inherent subjective characteristics of US can be improved with the integration of AI, including grayscale imaging quality, which is adversely affected by operator acquisition [ 9 ], and noise in relationship to other structures [ 10 ]. The clinical need for segmentation in US has been substantially advanced by AI technology, such as in breast cancer detection [ 15 , 16 ], thyroid nodule classification [ 17 , 18 ], and hepatic tissue vasculature identification in liver US [ 19 ].…”

“…Despite these advantages, US image quality can be adversely affected by operator acquisition and noise, such as bone shadowing [ 9 ]. DUS velocity measurements for stenosis are often distorted by echogenic mismatch of the blood and vessel wall [ 10 ]. To measure the vessel wall and the true lumen for an accurate percent of stenosis, manual segmentation has been applied, although it is not routinely performed due to the large amount of time, effort, and individual variability these measurements incur [ 11 ].…”

Ultrasound-based carotid stenosis measurement and risk stratification in diabetic cohort: a deep learning paradigm

“…However, Doppler US is dependent on velocity of blood flow which is variable. Doppler is used to measure stenosis based on pulse wave velocity (PWV) which in turn is dependent upon arterial wall stiffness (30)(31)(32)(33). Further, Doppler spectrum gets distorted by the acoustic impedance mismatch between the fluid and the vessel walls (34) leading to low-resolution images and loss of information during color display.…”