MODEL BASED IMAGE PROCESSING IN DOPPLER ECHOCARDIOGRAPHY

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DESCRIPTION (Adapted from Applicant's Abstract): The applicants have developed and tested, on various manufacturers' echocardiography equipment, a model-based image processing (MBIP) method for the analysis of diastolic transmitral Doppler flow velocity images. The method can extract quantitative physiologic information from transmitral Doppler echocardiographic images that previously could not be obtained or could only be determined by cardiac catheterization. The proposed research follows two main, interconnected themes: I) refinement of the MBIP method and, II) in-vivo verification. Specifically, the following MBIP steps will be refined: 1) machine independent Doppler image acquisition via video frame-grabbing, 2) extraction of the maximum velocity contour, and 3) fit solution of LV filling model to the contour using digital processing, estimation theory and error minimization. The in-vivo component will test the hypothesis that physiologically relevant, non-invasive quantitation of DF can be achieved by this MBIP method. MBIP advantages, in comparison to available methods of Doppler analysis include: 1) echo machine independent, numerically determined, rather than hand-traced/hand-digitized Doppler velocity contours, 2) causal, rather than correlative modeling, 3) unique-valued model parameters determined by numerical (automated) means directly from Doppler images, 4) noninvasive determination of DF parameters previously requiring catheterization. The proposed research will identify physiologic DF parameters obtained by transmitral Doppler echocardiography, and verify them, by simultaneous left and right heart catheterization in subjects meeting inclusionary criteria. The Specific Aims are to: 1) refine and extend the MBIP method for cardiac diastolic Doppler analysis, 2) validate the relation between MBIP-derived and invasively-derived indices of DF by analysis of simultaneous diastolic Doppler and high-fidelity hemodynamic data and MBIP based predictions, 3) verify the physiologic analogues of MBIP parameters as clinically relevant Doppler-derived indexes of DF.