Optimization of Doppler velocity echocardiographic measurements using an automatic contour detection method.
Intra- and inter-observer variability in Doppler velocity echocardiographic measurements (DVEM) is a significant issue. Indeed, imprecisions of DVEM can lead to diagnostic errors, particularly in the quantification of the severity of heart valve dysfunction. To minimize the variability and rapidity of DVEM, we have developed an automatic method of Doppler velocity wave contour detection, based on active contour models. To validate our new method, results obtained with this method were compared to those obtained manually by an experienced echocardiographer on Doppler echocardiographic images of left ventricular outflow tract and transvalvular flow velocity signals recorded in 30 patients, 15 with aortic stenosis and 15 with mitral stenosis. We focused on three essential variables that are measured routinely by Doppler echocardiography in the clinical setting: the maximum velocity, the mean velocity and the velocity-time integral. Comparison between the two methods has shown a very good agreement (linear correlation coefficient R(2) = 0.99 between the automatically and the manually extracted variables). Moreover, the computation time was really short, about 5s. This new method applied to DVEM could, therefore, provide a useful tool to eliminate the intra- and inter-observer variabilities associated with DVEM and thereby to improve the diagnosis of cardiovascular disease. This automatic method could also allow the echocardiographer to realize these measurements within a much shorter period of time compared to standard manual tracing method. From a practical point of view, the model developed can be easily implanted in a standard echocardiographic system.
Gaillard
E
E
Laboratory of Biomedical Engineering, Montreal Clinical Research Institute (IRCM), University of Montreal, Montreal, Canada. emmanuel.gaillard@irc.qc.ca
Kadem
L
L
Pibarot
P
P
Durand
L-G
LG
D001011:Aorta / Q000503:physiopathology; D001024:Aortic Valve Stenosis / Q000175:diagnosis / Q000503:physiopathology*; D001331:Automation; D001698:Biomedical Engineering / Q000379:methods; D001783:Blood Flow Velocity; D004452:Echocardiography / Q000295:instrumentation / Q000379:methods*; D018618:Echocardiography, Doppler, Color / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D008943:Mitral Valve / Q000503:physiopathology; D008946:Mitral Valve Stenosis / Q000175:diagnosis / Q000503:physiopathology*; D015233:Models, Statistical; D015588:Observer Variation; D015203:Reproducibility of Results; D013997:Time Factors