Quantitative analysis of Doppler flow spectra in the lower limb arteries

A computer processing method was developed to analyze lower limb Doppler signals, extract diagnostic features from Doppler spectrograms, and classify the severity of the arterial disease. A pattern recognition method (Bayes model) was used to discriminate between nonhemodynamically significant (<50% diameter reduction) and hemodynamically significant (<50% diameter reduction) stenoses. The features investigated were based on spectral broadening and on the power of the spectrogram in various frequency bands. The performance of the pattern recognition method was compared to that of conventional biplane contrast angiograms read by experienced angioradiologists. Results showed a percentage of correct classification of 85%. Sensitivity was 77%, and specificity was 90%