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S J Kovács

Publications and source records attributed to S J Kovács.

At least 19 recordsLinked to original sources
PubMed2001

The relation of the peak Doppler E-wave to peak mitral annulus velocity ratio to diastolic function.

Previous observations (Garcia et al. 1998; Sohn et al. 1997; Nagueh et al. 1997) indicate that mitral annulus velocity may be viewed as a "load-independent" index of filling and that wedge pressure is linearly related to the transmitral flow velocity (V(E)) to mitral annulus velocity (V(MA)) ratio (V(E)/V(MA)) measured at maximum velocity. In healthy subjects, the mean value observed for [V(E)](max)/[V(MA)](max) was 1:0.23 approximately 4. No prior physiologic or physical explanation for the basis of, or for the magnitude of, the ratio has been proposed. We propose a physiologic, model-based, quantitative explanation for these observations and test our simplified model's prediction in an invasive (n = 30) and noninvasive (n = 34) test groups of subjects. The simplified geometric model is based on the known constant volume (within a few percentage points) attribute of the four-chambered heart. Accordingly, left-atrial and left-ventricular volumes reciprocate so that their sum is constant throughout the cardiac cycle. The model predicts that: 1. the ratio (V(E)/V(MA)) is a constant approximately 3 in healthy hearts; and 2. V(E)/V(MA) should be linearly proportional to left ventricular end-diastolic pressure (LVEDP). Model prediction was tested using V(E) and V(MA) echocardiographic data from 34 subjects (noninvasive group), and simultaneous echocardiographic and high-fidelity hemodynamic (LVEDP) data in 30 subjects (invasive group). Excellent agreement was observed between model prediction and observed data. For the noninvasive (healthy) group, [V(E)](max)/[V(MA)](max) = 4.20 +/- 1.11. For the invasive group, [V(E)](max)/[V(MA)](max) was observed to be linearly related to LVEDP, [V(E)](max)/[V(MA)](max) = 0.19 (LVEDP) + 1.54, r = 0.92. Hence, [V(E)](max)/[V(MA)](max) is a legitimate flow-derived index of diastolic function because it is a derivable consequence of the heart's constant-volume pump attribute.

Blood Flow Velocity↗
PubMed2001

Echocardiographic characterization of fundamental mechanisms of abnormal diastolic filling in diabetic rats with a parameterized diastolic filling formalism.

Abnormalities of diastolic function (DF) precede systolic dysfunction in diabetic cardiomyopathy. Transmitral Doppler flow analysis is the primary method for noninvasively assessing DF. We used model-based Doppler E-wave analysis to evaluate diastolic function differences between normal and diabetic rat hearts. Control rats and those with diabetes underwent echocardiography with analysis by traditional Doppler indexes and by the parameterized diastolic filling (PDF) formalism, generating 3 parameters, x0, c, and k, that uniquely characterize each E-wave. Significant intergroup differences in the E/A ratios (P <.01), isovolumic relaxation times (P <.01), and the modeling parameter c (P <.05) were found. There were no significant differences in shortening fraction, deceleration time, myocardial collagen content, or the parameters x0 and k between diabetic and control rats. These results indicate that differences in diastolic function may be noninvasively quantified and that diabetic hearts may exhibit defects in uncoupling of the contractile apparatus without concomitant increases in chamber stiffness.

Animals↗
PubMed2001

Phase plane analysis of left ventricular hemodynamics.

We sought to extract additional physiological information from the time-dependent left ventricular (LV) pressure contour and thereby gain new insights into ventricular function. We used phase plane analysis to characterize high-fidelity pressure data in selected subjects undergoing elective cardiac catheterization. The standard hemodynamic indexes of LV systolic and diastolic function derived from the time-dependent LV pressure contour could be easily obtained using the phase plane method. Additional novel attributes of the phase plane pressure loop, such as phase plane pressure loop area, graphical representation of the isovolumic relaxation time constant, and quantitative measures of beat-to-beat systolic-diastolic coupling were characterized. The asymmetry between the pressures at which maximum isovolumic pressure rise and pressure fall occur, as well as their load dependence, were also easily quantitated. These results indicate that the phase plane method provides a novel window for physiological discovery and has theoretical and applied advantages in quantitative ventricular function characterization.

Algorithms↗
PubMed2001

Chamber properties from transmitral flow: prediction of average and passive left ventricular diastolic stiffness.

A chamber stiffness (K(LV))-transmitral flow (E-wave) deceleration time relation has been invasively validated in dogs with the use of average stiffness [(DeltaP/DeltaV)(avg)]. K(LV) is equivalent to k(E), the (E-wave) stiffness of the parameterized diastolic filling model. Prediction and validation of 1) (DeltaP/DeltaV)(avg) in terms of k(E), 2) early rapid-filling stiffness [(DeltaP/DeltaV)(E)] in terms of k(E), and 3) passive (postdiastasis) chamber stiffness [(DeltaP/DeltaV)(PD)] from A waves in terms of the stiffness parameter for the Doppler A wave (k(A)) have not been achieved. Simultaneous micromanometric left ventricular (LV) pressure (LVP) and transmitral flow from 131 subjects were analyzed. (DeltaP)(avg) and (DeltaV)(avg) utilized the minimum LVP-LV end-diastolic pressure interval. (DeltaP/DeltaV)(E) utilized DeltaP and DeltaV from minimum LVP to E-wave termination. (DeltaP/DeltaV)(PD) utilized atrial systolic DeltaP and DeltaV. E- and A-wave analysis generated k(E) and k(A). For all subjects, noninvasive-invasive relations yielded the following equations: k(E) = 1,401. (DeltaP/DeltaV)(avg) + 59.2 (r = 0.84) and k(E) = 229.0. (DeltaP/DeltaV)(E) + 112 (r = 0.80). For subjects with diastasis (n = 113), k(A) = 1,640. (DeltaP/DeltaV)(PD) - 8.40 (r = 0.89). As predicted, k(A) showed excellent correlation with (DeltaP/DeltaV)(PD); k(E) correlated highly with (DeltaP/DeltaV)(avg). In vivo validation of average, early, and passive chamber stiffness facilitates quantitative, noninvasive diastolic function assessment from transmitral flow.

Adult↗
PubMed2000

Modeling of diastole.

Modeling methods have been employed to further characterize the physical and physiologic processes of filling and diastolic function. They have led to more detailed understanding of the effect of alteration of physiologic parameters on the Doppler E-wave contour as well as pulmonary vein flow. Depending on the modeling approach, different aspects of the filling process have been considered from AV gradient and net compliance to atrial appendage function to the mechanical suction pump attribute of the heart. The models have been applied for further characterization of diastolic function and elucidation of novel basic physiologic relations. We trust that readers recognize that this article could not serve as a comprehensive and global review of the state-of-the-art in physiologic modeling, but rather as a selective overview, with emphasis on the main modeling principles and options currently in use. Modeling of systems physiology, especially as it relates to the function of the four-chamber heart, remains a fertile area of investigation. Future progress is likely to have profound influence on (noninvasive) diagnosis and quantitation of the effect of therapy and lead to continued discovery of "new" (macroscopic, cellular, and molecular biologic) physiology.

Animals↗
PubMed2000

Unsolved problems in diastole.

It is now recognized that a sizable portion of patients who exhibit symptoms of congestive heart failure have relatively well-preserved systolic function, but have significantly elevated LV filling pressures. This syndrome, termed "diastolic heart failure," is associated with various conditions such as aging, anatomic abnormalities, hypertension, ischemic disease, tachycardia, and atrial fibrillation. Advances in the proper medical and surgical management of these patients will depend on the continued delineation of the basic physiologic mechanisms that account for normal and pathologic cardiac diastolic function. This goal can only be achieved by the integration of information acquired from basic science investigations conducted in vitro and in vivo, mathematic modeling simulation studies, and prospective, community-based investigations that characterize the incidence, prevalence, and natural history of the disease. In addition, randomized clinical trials will be needed to determine the optimal treatment strategies for this group of patients--strategy choices undoubtably complicated by a disease whose treatment is influenced to a large extent by its origin. The future therapies evaluated in these randomized clinical trials will most likely range from medical therapies that target either the heart directly or the peripheral vascular system, to surgical interventions such as direct myocardial revascularization, to gene therapy. Finally, it is worth mentioning one more unresolved issue that is of general practical concern not only to the physiologist studying diastolic function, but also to the clinician: whether or not it is even feasible to develop a single, sensitive, specific, clinically relevant index of diastolic function that is free from the contaminating influences of rate, contractility, and load. As observed by Glantz 20 years ago, developing indexes with the hope that one might fully delineate the left ventricle's diastolic properties, rather than concentrating on discovering the physiologic significance of such indexes, is probably counterproductive. More recently, in a related article, Slinker implied that an operational definition of any aspect of cardiac function must allow for the measurement of that function over an adequate range of essential variables. Therefore, as previously mentioned, the physiologist studying cardiac function has the daunting task of trying to understand, in a precise way, how the processes and mechanisms of the various phases of the cardiac cycle couple together to produce either a normal or abnormal functioning heart. It seems clear that because of the complex weave of factors that control overall cardiac diastolic function, the derivation of any single index that adequately describes LV diastolic function in vivo may not be possible.

Diastole↗
PubMed1999

Prognostic value of diastolic filling parameters derived using a novel image processing technique in patients > or = 70 years of age with congestive heart failure.

Conventional echocardiographic characterization of diastolic function requires manual analysis of Doppler E-and A-wave amplitudes, deceleration times, isovolumic relaxation times, and pulmonary venous flow patterns. Mathematic modeling of the suction pump activity of the heart permits characterization of diastolic function through model-based image processing, which relies solely on transmitral Doppler images. This automated method uniquely specifies the entire E-wave contour using 3 parameters (x(o), k, and c) that determine E-wave amplitude, width, and rate of decay. Moreover, the index beta = c2 - 4k, reflecting the balance between chamber viscosity and stiffness/recoil, represents a novel parameter for characterizing diastolic function. We analyzed Doppler E waves from 39 patients (mean age 79 years, 61% women, mean ejection fraction 47%) using the model-based image processing technique. A value of beta <-900 was selected as indicative of severe diastolic dysfunction. Of 17 subjects with beta <-900, 8 (47%) were no longer alive at 1 year. Of 22 subjects with beta >-900, all were alive (p = 0.001). The index beta, dichotomized at <-900, had a predictive accuracy of 0.769 (30 of 39), a negative predictive value of 1.0 (22 of 22 alive), and a positive predictive value of 0.471 (8 of 17 deceased) for 1-year vital status. Of 14 subjects with deceleration time < or =160 ms, 5 (36%) were deceased at 1 year, whereas for deceleration time >160 ms, 22 of 25 patients were alive (p = NS). Of 16 subjects with ejection fraction <45%, 6 (38%) were deceased at 1 year. Of 23 subjects with ejection fraction >45%, 21 were alive at 1 year (p = 0.074). On multivariate analysis, beta dichotomized at -900 was the strongest independent predictor of 1-year mortality. We conclude that evaluation of diastolic function using model-based image processing provides valuable prognostic information in elderly patients with heart failure.

Aged↗
PubMed1999

Blood pool agent strongly improves 3D magnetic resonance coronary angiography using an inversion pre-pulse.

The ability of a blood pool contrast agent to enhance MR coronary angiography was defined. The proximal coronary vessels of pigs were imaged before and after administration of Gd-DTPA bound covalently to bovine serum albumin (0.2 mmol/ kg). The contrast agent resulted in a reduction of the blood T1 value to 33+/-5 msec, as determined in vivo with a Look-Locker technique. Both 2D and 3D imaging techniques were performed. An inversion pulse suppressed the signal of nonblood tissue postcontrast. After contrast agent administration, in the 3D data set the signal-to-noise ratio (SNR) of blood and contrast-to-noise ratio (CNR) of blood to myocardium were improved by factors of 2.0+/-0.2 and 15+/-8, respectively (P < 0.05). Postcontrast, the 3D acquisition was superior to the 2D technique in terms of spatial resolution, SNR of blood, and CNR of blood to myocardium. The high contrast of the 3D data set allowed for direct and rapid display of coronary arteries using a "closest vessel projection."

Animals↗
PubMed1998

Evaluation of model-based processing algorithms for averaged transmitral spectral Doppler images.

In an effort to characterize more fully diastolic function using Doppler echocardiography, we have previously developed an automated method of model-based image processing for spectral Doppler images of transmitral blood flow. In this method, maximum velocity envelopes (MVEs) extracted from individual Doppler images are aligned and averaged over several cardiac cycles. The averaged waveform is fit by the solution of a kinematic model of diastolic filling. The results are estimates of the model parameters. As expected, the mean and standard deviation of the model parameter estimates depend on many factors such as noise, the number of cardiac cycles averaged, beat-to-beat variation, waveform shape, observation time and the processing methods used, among others. A comprehensive evaluation of these effects has not been performed to date. A simulation was developed to evaluate the performance of three automated processing methods and to measure the influence of noise, beat-to-beat variation and observation time on the model parameter estimates. The simulation's design and a description and analysis of the three automated processing methods are presented. Of the three methods evaluated, using the inflection point in the acceleration portion of the velocity contour as the first data point to be fit was found to be the most robust method for processing averaged E-wave MVE waveforms. Using this method under nominal conditions, the average bias was measured to be < 3% for each of the model parameters. As expected, the biases and standard deviations of the estimates increased as a result of increased noise levels, increased beat-to-beat variation and decreased observation time. Another important finding was that the effects of noise, beat-to-beat variation and waveform observation time on the parameter estimates are dependent on the location in model parameter space.

Algorithms↗
PubMed1998

Beat averaging alternatives for transmitral Doppler flow velocity images.

To characterize diastolic function from transmitral Doppler data, the image's maximum velocity envelope (MVE) is fit by a model for flow velocity. To reduce the physiologic beat-to-beat variability of best-fit determined model parameters, averaging of multiple cardiac cycles is indicated. To assess variability mathematically, we modeled physiologic noise as a random (normally-distributed) process and evaluated three methods of averaging (1, averaging model parameters from single images; 2, averaging images; and 3, averaging MVEs) using clinical datasets (50 continuous beats from 5 subjects). Method 2 generates a positive bias because low-velocity beats will not contribute to the composite MVE. The difference between Methods 3 and 1 is less than 2.0 E-5 (m/s)2 for uncorrelated model parameters. Input having 10% beat-to-beat variation yields a bias of <4% for model parameter mean. Hence, Method 1 was, in general, more robust than Method 3.

Blood Flow Velocity↗
PubMed1997

Echo machine-imposed limit on transmitral spectral Doppler velocity-profile analysis.

We have previously developed a kinematic model of ventricular filling. Its application to in vivo transmitral Doppler velocity profiles provides a quantitative characterization of filling. However, the model parameters computed by solving the "inverse problem" may depend on ultrasound machine type and setting (e.g., gain, baseline filter, dynamic range). To determine machine-based effects on the computed model parameters, we performed a flow phantom study using Acuson and HP echocardiography machines at various settings. We compared maximum velocity envelopes (MVEs), as well as the model fit to these MVEs, for 3 simulated waveforms imaged by both machines. For all 3 waveforms, the machines generated comparable MVEs, fit by the model within a mean-square difference of 5E-5 (m/s)2. The associated variations in model parameters for the 3 waveforms were not uniform. Two waveforms showed slight variation between machines, with model parameters varying by less than 6%. The shortest duration waveform showed model parameter variations of 10-15%. Analysis of the parameter space for this waveform showed a constant mean-square error contour that was larger than that for the other two, causing similar small variations in measured MVEs to result in larger differences in the parameter estimates for this waveform. Because this method completely eliminates inter- and intraobserver variability, we conclude that, within the limits established, the slight contour variations due to machine type and setting should not affect this method's applicability in clinical Doppler-flow analysis.

Blood Flow Velocity↗
PubMed1997

Relationship of the fourth heart sound to atrial systolic transmitral flow deceleration.

The fourth heart sound (S4) is thought to be due to cardiohemic vibrations, powered by deceleration of transmitral blood flow, that occur when atrial systole leads to a disproportionately high rise in ventricular end-diastolic pressure (relative to diastasis), associated with an enhanced atrial systolic blood filling volume or a stiff ventricular wall. To characterize S4 production, we modeled the cardiohemic system as a forced, damped nonlinear harmonic oscillator. The forcing term used a closed-form expression for the Doppler A-wave contour. We simultaneously recorded transthoracic phonocardiograms and Doppler A waves in subjects with and without audible S4 and compared model predictions for S4 amplitude, frequency, and power spectrum with those of the recorded S4. Excellent agreement was observed between the model-predicted amplitude, duration, timing, and power spectrum and those of the phonocardiographic S4. We conclude that, with a normal mitral valve, there should always be an oscillation of the cardiohemic system during A-wave deceleration. However, oscillations may not have high enough amplitude, frequency, or coupling to the chest wall to be clinically audible as an S4.

Atrial Function↗
PubMed1997

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

Physiological models of transmitral 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 transmitral 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. Intergroup 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 transmitral flow velocity-altering pathophysiological states.

Aged↗
PubMed1995

Anatomically and physiologically based reference level for measurement of intracardiac pressures.

BACKGROUND: Many reference levels have been proposed for the measurement of intracardiac pressures, but none have met with universal acceptance. In the first part of our study, we evaluated 10 cardiologists' understanding of how hydrostatic pressure influences intracardiac pressures as measured with fluid-filled catheters. In the second part, we proposed and validated a new zero level (H): the uppermost blood level in the left ventricular (LV) chamber relative to the anterior chest wall for a patient in the supine position. A comparison was made of LV minimum diastolic pressure measured by reference to H versus measurements made with the zero level at midchest. METHODS AND RESULTS: Using two-dimensional echocardiography, we determined H in the LVs of seven normal patients (five male, two female; age, 49 +/- 9 years) undergoing routine cardiac catheterization. H was determined from a left parasternal short-axis view and calculated as the average distance between end diastole and end systole of the endocardium of the uppermost segment of the LV anterior wall below the fourth or fifth intercostal space of the left sternal border on the anterior surface of the chest wall, with the patient in the supine position. A micromanometer/fluid-filled lumen catheter was then positioned in the LV, and we compared the micromanometer LV minimum pressure (LVPmin) obtained when the reference fluid-filled transducer was aligned at midchest with the LVPmin obtained when the reference fluid-filled transducer was aligned at H. LVPmin referenced to a midchest fluid-filled external transducer was measured as 5.1 +/- 1.6 mm Hg (range, 2.4 to 7.2 mm Hg) versus -0.6 +/- 0.6 mm Hg (range, -1.6 to 0.4 mm Hg) when referenced to H (P < .001). A significant linear relation was found to exist between patient anterior-posterior chest diameter and the magnitude of hydrostatic pressure influences related to pressure referenced at midchest (r = .88; P < .01). CONCLUSIONS: External fluid-filled transducers should be used with the goal of removing hydrostatic pressure and other influences so that the presence of subatmospheric pressure during diastole in any of the cardiac chambers is accurately measured. To achieve this goal, intracardiac pressure should be referenced to an external fluid-filled transducer aligned with the uppermost blood level in the chamber in which pressure is to be measured. The current practice of referencing the zero level of LV diastolic pressure to an external fluid-filled transducer positioned at the midchest level results in systematic overestimation due to hydrostatic effects and produces physiologically significant error in the measurement of diastolic intracardiac pressure.

Cardiac Catheterization↗
PubMed1995

Relationship of the third heart sound to transmitral flow velocity deceleration.

BACKGROUND: The third heart sound (S3) occurs shortly after the early (E-wave) peak of the transmitral diastolic Doppler velocity profile (DVP). It is thought to be due to cardiohemic vibrations powered by rapid deceleration of transmitral blood flow. Although the presence, timing, and clinical correlates of the S3 have been extensively characterized, derivation and validation of a causal, mathematical relation between transmitral flow velocity and the S3 are lacking. METHODS AND RESULTS: To characterize the kinematics and physiological mechanisms of S3 production, we modeled the cardiohemic system as a forced, damped, nonlinear harmonic oscillator. The forcing term used a closed-form mathematical expression for the deceleration portion of the DVP. We tested the hypothesis that our model's predictions for amplitude, timing, and frequency of S3 accurately predict the transthoracic phonocardiogram, using the simultaneously recorded transmitral Doppler E wave as input, in three subject groups: those with audible pathological S3, those with audible physiological S3, and those with inaudible S3. CONCLUSIONS: We found excellent agreement between model prediction and the observed data for all three subject groups. We conclude that, in the presence of a normal mitral valve, the kinematics of filling requires that all hearts have oscillations of the cardiohemic system during E-wave deceleration. However, the oscillations may not have high enough amplitude or frequency to be heard as an S3 unless there is sufficiently rapid fluid deceleration (of the Doppler E-wave contour) with sufficient cardiohemic coupling.

Blood Flow Velocity↗
PubMed1995

Comparison of diastolic filling models and their fit to transmitral Doppler contours.

Anatomic/physiologic and kinematic mathematical models of diastolic filling which employ (lumped) parameters of diastolic function have been used to predict or characterize transmitral flow. The ability to determine model parameters from clinical transmitral flow, the Doppler velocity profile (DVP), is equivalent to solving the "inverse problem" of diastole. Systematic model-to-model and model-to-data comparison has never been carried out, in part due to the requirement that DVPs be digitized by hand. We developed, tested and verified a computerized method of DVP acquisition and reproduction, and carried out numerical determination of model-to-model and model-to-data goodness-of-fit. The transmitral flow velocity of two anatomic/physiologic models and one kinematic model were compared. Each model's ability to fit computer-acquired and reproduced transmitral DVPs was assessed. Results indicate that transmitral flow velocities generated by the three models are 'graphically indistinguishable and are able to fit the E-wave of clinical DVPs with comparable mean-square errors. Nonunique invertibility of the anatomic/physiologic models was verified, i.e., multiple sets of model parameters could be found that fit a single DVP with comparable mean-square error. The kinematic formulation permitted automated, unique, model-parameter determination, solving the "inverse problem" for the Doppler E-wave. We conclude that automated, quantitative characterization of clinical Doppler E-wave contours using this method is feasible. The relation of kinematic parameters to physiologic variables is a subject of current investigation.

Algorithms↗