CAN TRANSMITRAL DOPPLER E-WAVES DIFFERENTIATE HYPERTENSIVE HEARTS FROM NORMAL

Citation
Sj. Kovacs et al., CAN TRANSMITRAL DOPPLER E-WAVES DIFFERENTIATE HYPERTENSIVE HEARTS FROM NORMAL, Hypertension, 30(4), 1997, pp. 788-795
Citations number
48
Categorie Soggetti
Peripheal Vascular Diseas
Journal title
ISSN journal
0194911X
Volume
30
Issue
4
Year of publication
1997
Pages
788 - 795
Database
ISI
SICI code
0194-911X(1997)30:4<788:CTDEDH>2.0.ZU;2-J
Abstract
Physiological models of transmitral flow predict E-wave contour altera tion in response to variation of model parameters (stiffness, relaxati on, mass) reflecting the physiology of hypertension. Accordingly, anal ysis of only the E-wave (rather than the E-to-A ratio) should be able to differentiate between hypertensive subjects and control subjects. C onventional versus model-based image processing methods have never bee n compared in their ability to differentiate E-waves of hypertensive s ubjects with respect to age-matched control subjects. Digitally acquir ed transmitral Doppler flow images were analyzed by an automated model -based image processing method. Model-derived indexes were compared wi th conventional E-wave indexes in 22 subjects: 11 with hypertension an d echocardiographically verified ventricular hypertrophy and 11 age-ma tched nonhypertensive control subjects. Conventional E-wave indexes in cluded peak E, integral E, and acceleration and deceleration times. Mo del-based image processing-derived indexes included acceleration ard d eceleration times, potential energy index, and damping and kinematic c onstants. Inter-group comparison yielded lower probability values for model-based compared with conventional indexes. In the subjects studie d, Doppler E-wave images analyzed by this automated method (which elim inates the need for hand-digitizing contours or the manual placement o f cursors) demonstrate diastolic function alteration secondary to hype rtension made discernible by model-based indexes. The method uses the entire E-wave contour, quantitatively differentiates between hypertens ive subjects and control subjects, and has potential for automated non invasive diastolic function evaluation in large patient populations, s uch as hypertension and other transmitral flow velocity-altering patho physiological states.