(Circulation. 1995;92:1473-1478.)
© 1995 American Heart Association, Inc.
Articles |
From the Cardiac Catheterization Laboratory, Hospital of the University of Pennsylvania; the Department of Medicine, University of Pennsylvania School of Medicine; and the Cardiovascular Studies Unit, Department of Bioengineering, University of Pennsylvania, Philadelphia.
Correspondence to Warren K. Laskey, MD, Cardiac Catheterization Laboratory, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104.
| Abstract |
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Methods and Results We developed an analog model of the systemic arterial circulation in the presence of a stenotic aortic valve. The model clearly describes the dependence of stenosis severity (described by coefficients A and B) on the resistive and capacitive properties of the arterial system. We used high-fidelity pressure recordings obtained at the time of diagnostic cardiac catheterizations and found that a highly significant relation between the measured mean transvalvular gradient and that predicted by the model was demonstrated both at rest (r2=.90) and with exercise (r2=.80). Furthermore, the relative constancy of stenosis coefficients A and B was validated.
Conclusions Transvalvular hemodynamics in patients with aortic valve stenosis are dependent on the properties of the arterial system. The current model describes such behavior, correctly predicts the transvalvular gradient from model parameters, and may be useful in the assessment of stenosis severity under various clinical and physiological conditions.
Key Words: aorta stenosis valves hemodynamics
| Introduction |
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The purpose of the present study was to (1) develop a model of the systemic arterial circulation in the presence of a stenosed aortic valve and (2) analyze the effect of systemic arterial hemodynamics on measures of stenosis severity.
| Methods |
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![]() | (1) |
![]() | (2) |
![]() | (3) |
Manipulation
of Equations 1 through 3![]()
![]()
permits
the development of
a relation among coefficients A and B, the transvalvular
pressure gradient, and the characteristics of the arterial
bed, while eliminating flow. Thus, substituting
![]() | (4) |
![]() | (5) |
![]() | (6) |
then
![]() | (7) |
and
![]() | (8) |
Substitution
of Equations 7 and 8 in Equation 5
finally
yields
![]() | (9) |
![]() |
![]() |
Equation
9
indicates the dependence of stenosis severity
on systemic arterial resistance (R) and compliance
(C)arterial properties that effectively characterize
systemic arterial hemodynamics. Note also
that the flow term Q(t) has been eliminated.
To derive coefficients A
and B, several simplifications and assumptions
were made: (1) The relation expressed in Equation 9
was
examined at the
instant to, wherein the transvalvular
gradient (Pv-PAo) was maximum, that is,
when the first derivative of the pressure gradient with respect to time
was zero. (2) The aortic characteristic impedance is substantially less
than the peripheral vascular resistance. With these
simplifications, Equation 9
then reduces to the simpler
expression
shown in Equation 10
.
![]() | (10) |
![]() |
Note
that in Equation 10
, the variables
PAo, its derivative, and the gradient are
instantaneous measures at time to. This latter expression,
however, represents one equation with two unknowns: the
coefficients A and B. Therefore, to solve for coefficients A and B,
Equation 10
was evaluated at two different
physiological states (rest and exercise), with the
assumption that A and B remain constant from rest to exercise.
Model Validation and Validation of Assumptions
As indicated
above, several simplifying assumptions were made to
allow for the derivation of stenosis coefficients A and B. With
respect to the first simplifying assumption, that is, that conditions
that exist at the time of peak gradient are met throughout the systolic
ejection period, substitution of A and B into Equation 9
at all
points
in time should yield results not significantly different from zero. It
will be recalled that Equations 4 through
10![]()
![]()
![]()
![]()
![]()
![]()
express the instantaneous
relation between variables. Ideally, then, the model should be
validated using instantaneous measures of pressure and flow.
Catheter-tip manometry of instantaneous pressure and flow across a
stenotic aortic valve is technically demanding and highly
position dependent within the region distal to the valve.9
Given the uncertainty of the instantaneous flow measurement and the
goal of developing a clinically useful approach, we chose to examine as
a first approximation the mean relation between variables. Thus, if
A and B remain constant under rest and exercise conditions, then a
close relation between the predicted mean transvalvular
gradient (from Equation 3
) and the measured mean
transvalvular gradient should be demonstrable.
Clinical Study Protocol
Fifteen patients (mean age,
59±7 years) were referred for
diagnostic cardiac catheterization in the
setting of clinically significant aortic valve stenosis. All
patients were demonstrated to have normal left ventricular
size and systolic function, angiographically normal coronary
arteries, and no significant aortic regurgitation.
The study protocol consisted of micromanometric left ventricular and ascending aortic pressure determinations.9 Cardiac output was obtained using the thermodilution technique. Patients were studied under supine resting conditions as well as during 3 to 5 minutes of supine bicycle exercise. Data were reordered on FM tape and subjected to off-line analysis.
All subjects gave written consent for participation in the research protocol in accordance with guidelines established by the University of Pennsylvania Committee on Studies Involving Human Beings.
Data Analysis
Total arterial compliance (C) was derived as
described previously.10 Note that, as seen in Equations 9
and 10, with aortic valve closure Q=0 and
CdPAo/dt+PAo/R=0. Thus,
PAo(t)=Pe-t/RC. Systemic vascular
resistance
(R) was derived as the relation between the mean aortic pressure and
cardiac output. Aortic valve resistance was also derived after the
method of Ford et al.11 The aortic valve area was derived
according to the method of Gorlin and Gorlin.1
Twenty to 30 consecutive analog beats were taken from FM tape and subjected to digital conversion at 4-ms intervals. Data were stored and signal-averaged as previously described.12
Statistical Analysis
Within-patient comparisons were
accomplished with the paired
t test. The relation between selected variables was
estimated using a least-squares linear regression technique.
Statistical significance was defined as P<.05.
| Results |
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Table 2
summarizes aortic valve
hemodynamics in the study population. A significant
increase in the Gorlin-derived aortic valve area was noted on exercise
(mean change, 10±3%), along with a significant decrease in the
Ford-calculated valve resistance (mean change, 21±7%). By definition,
the stenosis coefficients A and B remained constant from rest
to exercise.
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Fig 2
demonstrates close agreement between the
Gorlin-derived aortic valve area and stenosis coefficient A
under resting conditions; however, less agreement is seen under
exercise conditions. Fig 3
also demonstrates close
agreement between Ford aortic valve resistance and stenosis
coefficient A under resting conditions; somewhat more scatter is noted
with exercise. It is of note that the decrease in aortic valve
resistance was strongly dependent on the resting level of valve
resistance (r2=.74,
P<.001).
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The validation of the model under mean conditions is seen in Fig
4
, which demonstrates a significant relation between the
predicted mean transvalvular gradient and the measured mean
transvalvular gradient. The former was obtained by
integration of both sides of Equation 3
and substitution of the
derived
values for A and B. Note that the integral of the left side of Equation
3
over the ejection period divided by the ejection period
yields the
mean transvalvular gradient, while the integral of Qdt over
the ejection period divided by the ejection period yields mean
transvalvular flow. In accord with our original hypothesis,
the constancy of coefficients A and B under resting and exercise
conditions would necessitate the observed close relation between
predicted and observed gradients.
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The validation of the model under instantaneous conditions is seen in
Fig 5
. The summation of the terms in Equation 9
for all
146 digitized time points throughout the ejection period (other than
the moment of peak gradient) is shown for two randomly chosen beats in
a single patient. It can be seen that the overall sum is not
significantly different from zero (95% confidence interval, -11,+3)
and supports the assumption that the values for coefficients A and B
are relatively invariant over time.
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| Discussion |
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Traditional assessment of the severity of a stenotic aortic valve describes the relation between transvalvular pressure and flow. These measurements are usually obtained under resting conditions during diagnostic cardiac catheterization and have provided for reliable and prognostically useful indices in the management of such patients. However, the acquisition of hemodynamic data under varying physiological states in patients with aortic valve stenosis has, using these traditional methods, resulted in variable results for the calculated aortic valve area. Prior studies have reported consistent and significant increases in calculated aortic valve area with exercise.2 3 4 Explanations for this finding have varied from increased physical displacement of the stenotic aortic valve under conditions of increased transvalvular flow13 to limitations of the theoretical underpinning for valve area calculation.14 Several recent studies of the assessment of aortic valve stenosis under exercise conditions have emphasized the strong dependence of all derived indices of stenosis severity on transvalvular flow.15 16
Since both transvalvular flow and the pressure gradient (as
demonstrated herein) are dependent on the characteristics of the
systemic arterial circulation, a model providing a more
flow-independent approach would be useful. As seen in Equation
9
, the
absence of the flow term Q(t) allows for such an approach. We have also
demonstrated that the pressure gradient is a function of
stenosis severity (A,B), aortic pressure, arterial
compliance, and peripheral resistance. In the Gorlin model
of valvular hemodynamics, the relation between
the pressure gradient and flow is given by the quadratic relation
P=K1Q2. The approach used by Ford et al
describes a linear relation between the pressure gradient and flow:
P=K2Q. Our approach represents the summation of
both the Gorlin and Ford expressions (Fig 6
). In this
respect, all three models would predict similar pressure gradients at
low values of Q. However, at higher values of Q, the pressure gradient
is underestimated with both the Gorlin and Ford approaches. This
underestimate of the pressure gradient would in the Gorlin model lead
to the observed increase in calculated area and in the Ford model a
decrease in valve resistance.
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The current model describes the influence of the (analog) components of
the peripheral arterial circulation on
"upstream" events at the aortic valve. The model not only
provides for evaluation of the severity of aortic valve
stenosis under resting and exercise conditions but also may be
used in the assessment of stenosis severity in other clinical
settings. One such setting is the low cardiac output state. Under these
circumstances, the Gorlin-derived aortic valve area may be
problematic and potentially misleading.17 We
have seen how, under high flow conditions, the Gorlin model would
result in an underestimate of the pressure gradient. While all three
models provide comparable estimates of the pressure gradient at lower
flows, further consideration of our model under low flow conditions
provides insight into this challenging clinical
presentation. A common accompaniment of the low flow state
is an elevated systemic vascular resistance. Rearranging the terms of
Equation 10
reveals that the gradient is, at common levels of
arterial pressure and compliance, inversely proportional to
the systemic vascular resistance. Thus, the model predicts a lower
gradient under these low flowelevated resistance conditions for
similar valvular stenoses (A,B). Patients 14 and 15 in
our series were characterized by depressed cardiac outputs at rest and
elevated systemic vascular resistance. Both were characterized by
similar high values for stenosis coefficients A and B, although
the patient with a higher systemic vascular resistance had a lower
transvalvular gradient. Unfortunately, in this small group
we could find no instances of lower values for coefficients A and B in
the setting of low cardiac output, perhaps reflecting the biased nature
of this sample in which only symptomatic patients with
clinically severe valvular stenosis were chosen for
study. Assessment of stenosis severity in the setting of severe
arterial hypertension is another situation commonly
encountered.18 Under such conditions, marked alterations
in peripheral vascular resistance and total
arterial compliance must be accounted for because the
pressure gradient will vary directly with the compliance but inversely
with the resistance.
The current model also indicates the importance of kinetic terms in the
evaluation of stenosis severity. That is, the fraction of the
overall pressure gradient due to the term BQ2 ranged from
15% to 35% of the total pressure drop (the sum of
AQ+BQ2). The kinetic terms clearly assume greater
importance under high flow conditions such as encountered during
exercise and therefore must not be discounted in the evaluation of
stenosis severity. In fact, without the inclusion of the
kinetic term, the relation between predicted and observed gradients was
substantially inferior to that depicted in Fig 3
(r=.20).
There are several limitations to the present study that must be acknowledged. In the current study, we develop a model based on the three-element Windkessel. Although this Windkessel model has been useful in the understanding of the behavior of the systemic arterial circulation, its limitations are acknowledged.19 However, given the ability to take into account such features of in vivo behavior as wave travel and wave reflection,20 the approximations made using the current approach allow for reliable model behavior.
A critical assumption was the constancy of stenosis
coefficients A and B during rest and exercise. That A and B were
essentially invariant is seen in the significant relation between
predicted and observed transvalvular gradients. That is, if
A and B were significantly different on exercise and these values were
entered into Equation 3
(which describes the predicted
behavior), a
poorer correlation with the observed gradient would have been
obtained.
One simplifying assumption was the relation between the
transvalvular pressure gradient and flow (Equation 3
).
Although this relation is modeled under steady (nonpulsatile)
conditions, application of the model to pulsatile
hemodynamics has been validated.7 8 As
indicated previously, we chose, as a first approximation, to examine
the relation in mean terms, given the uncertainty of catheter-tip
measures of instantaneous flow velocity in the proximal ascending aorta
and the need to develop a clinically useful method. Despite these
limitations, both resting and exercise gradients could be reliably
predicted by use of this model.
Another simplifying assumption relates to the solution of Equation
9
at
the moment of the peak transvalvular gradient when the time
derivative is zero. We chose this point to simplify our calculations.
To establish the validity of Equation 9
at each instant in time
over
the ejection interval, we computed the exact solution for every
digitized time point. Significant overall deviation from zero (less
than 10% of all calculated values) was not seen in any instance in
randomly chosen beats from all patients studied.
Summary
The present study reports the development and
preliminary
validation of a model describing the relation between stenotic
aortic valve hemodynamics and systemic
arterial hemodynamics. The need for
additional validation, particularly with respect to instantaneous
measures of pressure and flow under carefully controlled experimental
conditions, is recognized. The current approximate approach to
understanding the relation between systemic arterial
properties and valvular hemodynamics provides
an alternative flow-independent method of assessing stenosis
severity.
| Acknowledgments |
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Received February 27, 1995; accepted April 1, 1995.
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