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Coanda Effect in a Human Body
Published in Noor A. Ahmed, Coanda Effect, 2019
An echocardiogram is generally used in the diagnosis, management, and follow-up of patients who are suspected to suffer from heart diseases. An imaging technique known as color Doppler echocardiography creates two-dimensional or three-dimensional color images of the intracardiac blood flow patterns, particularly in valvular heart disease, using pulsed-wave or continuous-wave Doppler ultrasound. From such echo Doppler and color flow mapping, the visual images and quantitative information about the size and shape of the heart, as well as the location of the damaged tissues can be determined. In addition, several functional parameters of the heart, such as its pumping capacity, blood flow volume, ejection fraction, and heart relaxation can also be quantified. The information is then used to assess any abnormalities in blood flow between the left and right sides of the heart and the clinical severity of both mitral and aortic regurgitation.
Mechanical Effects of Cardiovascular Drugs and Devices
Published in Michel R. Labrosse, Cardiovascular Mechanics, 2018
All heart valve replacements are Class III devices and require extensive testing for regulatory approval.33 The goal of valve replacements is to improve cardiac function by maximizing forward flow and reducing regurgitant flow. Clinically, valve function is assessed with Doppler echocardiography to measure flow velocity during the cardiac cycle. Effective orifice area, EOA, is a global index that estimates the equivalent area for valvular flow from the continuity equation. The EOA is measured using the continuity equation: () EOA=ALVOT∗VTILVOT/VTI
Artificial intelligence: improving the efficiency of cardiovascular imaging
Published in Expert Review of Medical Devices, 2020
Andrew Lin, Márton Kolossváry, Ivana Išgum, Pál Maurovich-Horvat, Piotr J Slomka, Damini Dey
AI has been increasingly applied to the automated quantification of 2D and 3D echocardiograms. Early software used traditional ML to automatically perform rapid and accurate calculation of LV ejection fraction based on 2D LV volumes [47]. ML and DL algorithms have since been utilized to quantify a variety of other 2D parameters such as LV hypertrophy [48], wall motion abnormalities [49], myocardial velocity [50], and longitudinal strain [51]. Doppler echocardiography, which measures blood flow, provides a velocity-time image for assessment of valvular function. A ML framework using hierarchical clustering has provided automated Doppler measurements of mitral inflow and aortic and tricuspid regurgitation [52]. Further, a support vector machine was able to accurately quantify the severity of mitral regurgitation based on textural features on 2D images [53].