Can transmitral Doppler E-waves differentiate hypertensive hearts from normal?

Sándor J. Kovács, Jose Rosado, Abigail L. Manson McGuire, Andrew F. Hall

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Physiological models of transmittal flow predict E-wave contour alteration in response to variation of model parameters (stiffness, relaxation, mass) reflecting the physiology of hypertension. Accordingly, analysis of only the E-wave (rather than the E-to-A ratio) should be able to differentiate between hypertensive subjects and control subjects. Conventional versus model-based image processing methods have never been compared in their ability to differentiate E-waves of hypertensive subjects with respect to age-matched control subjects. Digitally acquired transmittal Doppler flow images were analyzed by an automated model-based image processing method. Model-derived indexes were compared with conventional E- wave indexes in 22 subjects: 11 with hypertension and echocardiographically verified ventricular hypertrophy and 11 age-matched nonhypertensive control subjects. Conventional E-wave indexes included peak E, ∫E, and acceleration and deceleration times. Model-based image processing-derived indexes included acceleration and deceleration times, potential energy index, and damping and kinematic constants. Inter-group comparison yielded lower probability values for model-based compared with conventional indexes. In the subjects studied, Doppler E-wave images analyzed by this automated method (which eliminates the need for hand-digitizing contours or the manual placement of cursors) demonstrate diastolic function alteration secondary to hypertension made discernible by model-based indexes. The method uses the entire E-wave contour, quantitatively differentiates between hypertensive subjects and control subjects, and has potential for automated noninvasive diastolic function evaluation in large patient populations, such as hypertension and other transmittal flow velocity-altering pathophysiological states.

Original languageEnglish
Pages (from-to)788-795
Number of pages8
JournalHypertension
Volume30
Issue number4
DOIs
StatePublished - Oct 1997
Externally publishedYes

Keywords

  • Diastole
  • Hypertension, model-based image processing
  • Models, physiological
  • Ultrasonics

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