S J Kovács1, R Setser, A F Hall. 1. Cardiovascular Biophysics Laboratory, Barnes-Jewish Hospital at Washington University Medical Center, St Louis, MO 63110, USA.
Abstract
BACKGROUND: Model-based image processing (MBIP) of Doppler E-waves eliminates the need for digitizing waveforms by hand or determining the contour 'by eye'. Little et al. (Circulation 1995, 92:1933-1939) used pressure-volume measurements for dogs to verify the physiologic-model-derived prediction that the left ventricular chamber stiffness, KLV1 can be determined from the deceleration time tdec, when that portion of the E-wave contour is fit by a cosine function. MBIP of clinical Doppler E-wave images to determine chamber stiffness KLV has not been performed. OBJECTIVE: We sought to determine KLV by MBIP of clinical Doppler E-wave images and elucidate the physiologic meaning of the harmonic oscillator filling model's parameter k. METHODS AND RESULTS: The unique mathematical relationship between the kinematic, harmonic oscillator model of filling and KLV predicts that the oscillator's spring constant k be linearly proportional to the chamber stiffness KLV. To verify this, digitally acquired, clinical Doppler transmitral flow velocity images from 21 subjects were analyzed. The parameter k and the stiffness KLV were computed independently for each subject and compared. In accordance with prediction, a linear relationship between k and the stiffness KLV, namely k = 1.16 [A/(rho L)]KLV+41, r = 0.96, was observed. CONCLUSIONS: The oscillator parameter k is linearly proportional to the left ventricular chamber stiffness KLV. The MBIP approach allows automated computation of k and KLV, provides a robust, automated, observer independent method of Doppler transmitral flow velocity analysis, and eliminates the need for visual determination of the contour or measurement of its attributes by eye. It provides a stimulus for further validation of the relationships among K, KLV, and catheterization-based diastolic chamber properties in humans and their correlations with selected diastolic function-altering syndromes.
BACKGROUND: Model-based image processing (MBIP) of Doppler E-waves eliminates the need for digitizing waveforms by hand or determining the contour 'by eye'. Little et al. (Circulation 1995, 92:1933-1939) used pressure-volume measurements for dogs to verify the physiologic-model-derived prediction that the left ventricular chamber stiffness, KLV1 can be determined from the deceleration time tdec, when that portion of the E-wave contour is fit by a cosine function. MBIP of clinical Doppler E-wave images to determine chamber stiffness KLV has not been performed. OBJECTIVE: We sought to determine KLV by MBIP of clinical Doppler E-wave images and elucidate the physiologic meaning of the harmonic oscillator filling model's parameter k. METHODS AND RESULTS: The unique mathematical relationship between the kinematic, harmonic oscillator model of filling and KLV predicts that the oscillator's spring constant k be linearly proportional to the chamber stiffness KLV. To verify this, digitally acquired, clinical Doppler transmitral flow velocity images from 21 subjects were analyzed. The parameter k and the stiffness KLV were computed independently for each subject and compared. In accordance with prediction, a linear relationship between k and the stiffness KLV, namely k = 1.16 [A/(rho L)]KLV+41, r = 0.96, was observed. CONCLUSIONS: The oscillator parameter k is linearly proportional to the left ventricular chamber stiffness KLV. The MBIP approach allows automated computation of k and KLV, provides a robust, automated, observer independent method of Doppler transmitral flow velocity analysis, and eliminates the need for visual determination of the contour or measurement of its attributes by eye. It provides a stimulus for further validation of the relationships among K, KLV, and catheterization-based diastolic chamber properties in humans and their correlations with selected diastolic function-altering syndromes.
Authors: Wei Zhang; Charles S Chung; Matt M Riordan; Yue Wu; Leonid Shmuylovich; Sándor J Kovács Journal: Ultrasound Med Biol Date: 2007-05-03 Impact factor: 2.998