EVALUATION OF MODEL-BASED PROCESSING ALGORITHMS FOR AVERAGED TRANSMITRAL SPECTRAL DOPPLER IMAGES

In an effort to characterize more fully diastolic function using Doppl er echocardiography, we have previously developed an automated method of model-based image processing for spectral Doppler images of transmi tral blood how. In this method, maximum velocity envelopes (MVEs) extr acted from individual Doppler images are aligned and averaged over sev eral cardiac cycles. The averaged waveform is fit by the solution of a kinematic model of diastolic filling. The results are estimates of th e model parameters. As expected, the mean and standard deviation of th e model parameter estimates depend on many factors such as noise, the number of cardiac cycles averaged, beat-to-beat variation, waveform sh ape, observation time and the processing methods used, among others. A comprehensive evaluation of these effects has not been performed to d ate. A simulation was developed to evaluate the performance of three a utomated processing methods and to measure the influence of noise, bea t-to-beat variation and observation time on the model parameter estima tes. The simulation's design and a description and analysis of the thr ee automated processing methods are presented. Of the three methods ev aluated, using the inflection point in the acceleration portion of the velocity contour as the first data point to be fit was found to be th e most robust method for processing averaged E-wave MVE waveforms. Usi ng this method under nominal conditions, the average bias was measured to be < 3% for each of the model parameters. As expected, the biases and standard deviations of the estimates increased as a result of incr eased noise levels, increased beat-to-beat variation and decreased obs ervation time. Another important finding was that the effects of noise , beat-to-beat variation and waveform observation time on the paramete r estimates are dependent on the location in model parameter space. (C ) 1998 World Federation for Ultrasound in Medicine & Biology.