This application is aimed at greatly improving the state-of-the-art in Doppler ultrasound imaging. A novel methodology will be developed based on implementation of a cross-correlation technique to obtain velocity field data directly from digital ultrasound images. The method will eliminate the flop ambiguities caused by angular dependency that are inherent in the currently available two-dimensional (2-D) Doppler ultrasonograph methods. The angular dependency of the ultrasound methods often has adverse effect in detecting important intracardiac flow features such as intraventricular cortical structures. Angular dependency also results in distortion of the flop convergence contour in transvalvular flows, particularly when valvular regurgitation and stenotic features are studied. Optical DPIV was pioneered in this group and has been used frequently for in vitro pulsatile flow studies. It represents a novel and very reliable method for whole-field flow mapping, and has become a common technique for flow diagnosis in which digitally recorded video images are analyzed computationally, removing all the photographic and opto-mechanical processing steps. The images can be recorded at time intervals as small as 1 microsecond. Usually, a laser light sheet provides cross-sectional illumination. By sequential imaging of the particle seeded flow, one can obtain shifted images of particle field. Various pattern-matching techniques, such as cross-correlation, can be used to quantify this particle shift and obtain the velocity field information. A pilot study has shown that a combination of ultrasound speckle images and the cross-correlation technique can be successfully used to obtain a calibrated velocity vector field. The investigators will conduct in vitro experiments to optimize the processing of ultrasound digital speckle images by the cross-correlation technique available for optical DPIV. Following this phase, they will implement the same cross-correlation technique to process selected clinical images of intraventricular and transvalvular flows in humans. The entire biomedical research community, particularly those who utilize ultrasonography for clinical diagnosis and flow imaging, will benefit from this new methodology in quantitative flow imaging.
