Computer based pattern recognition of carotid artery Doppler signals for disease classification: prospective validation.

A computer based pattern recognition method has been developed to classify the percent diameter reduction in nonoccluded internal carotid arteries. Using a combined B-mode/pulsed Doppler unit, the system utilizes spectral waveforms obtained from the low common and proximal internal carotid artery locations. The ECG-R wave is used as a time reference to synchronize the averaging of Doppler spectra from 20 heart cycles. An averaged waveform is generated and represents the spectral data from which features are extracted for analysis. A stepwise selection algorithm identifies a feature subset for partitioning the entire range of disease into two states, less than and greater than a decision point. Three such partitions are made, leading to the following categories: Normal, 1-20, 21-50 and 51-99% dia. reduction. A classifier was trained, tested prospectively against unknown data and the results compared to angiography. Of the 170 vessels tested, 141 (82%) were classified in the same category by angiography and the computer system. Agreement for each category was 93% (27/29) for the normals, 81.5% (44/54) for the 1-20% lesions, 78% (29/37) for the 21-50% lesions and 82% (41/50) for the 51-99% lesions. The computer method and angiography differed by more than one category in only one of the 170 tests. The level of agreement corrected for chance (Kappa +/- SE(K] was 0.769 +/- 0.039. Future efforts will be directed toward dividing classification of disease further (especially in the 51-99% category), developing a dedicated microprocessor for on-line analysis of the signals and using the system for prospective epidemiological studies of various populations.

Flow velocity patterns in the carotid bifurcations of young, presumed normal subjects.

Spectral analysis of pulsed Doppler velocity waveforms has been found useful as a diagnostic technique in the assessment of carotid artery disease. While spectral broadening of the velocity waveform obtained at center stream sites is usually associated with arterial disease, the present study describes spectral patterns resulting from disturbed blood flow in the proximal branches of the carotid bifurcation in young, presumed normal human subjects. In those studied, spectral patterns in the bifurcation region exhibit characteristics similar to those occurring in zones of flow separation in model studies under conditions of steady flow. It is important to distinguish the spectral patterns due to arterial disease from those occurring in the normal bifurcation. This paper describes the types of flow disturbances noted in presumed normal arteries and points out the need to understand the flow velocity patterns that may be found at specific anatomical sites across the carotid bifurcation.

Computer based classification of carotid arterial disease: a prospective assessment.

A minicomputer based pattern recognition method has been used to prospectively classify the category of disease involvement of 105 carotid arteries. The system utilized spectral patterns obtained from a combined B-mode/pulsed Doppler unit. All decisions are based upon comparison of an unknown, averaged waveform with a series of vessels with known severity of disease. The variability in the computer decision as compared to arteriography is discussed.

Computer based pattern recognition of carotid arterial disease using pulsed Doppler ultrasound.

A minicomputer based system has been developed for studying carotid artery blood flow data obtained for a combined B-mode, pulsed Doppler ultrasound scanner. The goals of this work are to devise and improve techniques for estimating the extent of atherosclerosis at the carotid artery bifurcation. Features are automatically extracted from spectrum analyzed Doppler blood flow data. Five statistical pattern recognition algorithms are compared, with cross validation being used to improve the estimate of classification accuracy. A data collection protocol has been devised in which four sites are studied along each carotid arterial system. Classification of unknowns is done using a hierarchy of three decisions.

Spectral analysis of Doppler velocity patterns in normals and patients with carotid artery stenosis.

A computerized pattern recognition program was utilized to assess the predictive ability of various parameters obtained from the spectra of ultrasonic pulsed Doppler signals from the carotid arteries. The most accurate features selected by linear regression analysis were the natural log (ln) of the ratio of the mean velocity in the internal carotid artery compared to that in the common carotid artery, and the ln of the maximum velocity, the ln of the maximum frequency, and the square of the fractional broadening term, all of which were measured at peak systole in the internal carotid artery. Using the combination of the velocity ratio and the fractional broadening term, the average difference in the estimated percentage stenosis, as compared to that obtained by arteriography, was 12.8%.

Flow disturbances following carotid endarterectomy.

Noninvasive flow dynamics in 69 carotid arteries following endarterectomy were studied. By using three parameters which measure either changes in velocity or disturbed flow, 49 per cent of the arteries demonstrated flow abnormalities consistent with a 50 per cent, or greater, reduction in diameter in at least two of the three measured parameters. Of the 31 arteries which underwent more than one postoperative study, progression of the flow abnormality was suggested by changes in the velocity ratio in 20 arteries, maximum velocity in 15 arteries and the fractional broadening term in 25 arteries.