Noninvasive methods for determining pulmonary vascular function in children with pulmonary arterial hypertension: application of a mechanical oscillator model

Abstract

Objective: Noninvasive diagnostics for pulmonary arterial hypertension (PAH) have traditionally sought to predict main pulmonary artery pressure from qualitative or direct quantitative measures of the flow velocity pattern obtained from spectral Doppler ultrasound examination of the main pulmonary artery. A more detailed quantification of flow velocity patterns in the systemic circuit has been obtained by parameterizing the flow trace with a simple dynamic system model. Here, we investigate such a model's utility as a noninvasive predictor of total right heart afterload and right heart function.

Design: Flow velocity and pressure was measured within the main pulmonary artery during right heart catheterization of patients with normal hemodynamics (19 subjects, 20 conditions) and those with PAH undergoing reactivity evaluation (34 patients, 69 conditions). Our model parameters were obtained by least-squares fitting the model velocity to the measured flow velocity.

Results: Five parameter means displayed significant (P < .05) differences between normotensive and hypertensive groups. The model stiffness parameter correlated to actual pulmonary vascular resistance (r = 0.4924), pulmonary vascular stiffness (r = 0.6811), pulmonary flow (r = 0.6963), and stroke work (r = 0.7017), while the model initial displacement parameter had good correlation to stiffness (r = 0.6943) and flow (r = 0.6958).

Conclusions: As predictors of total right heart afterload (resistance and stiffness) and right ventricle work, the model parameters of stiffness and initial displacement offer more comprehensive measures of the disease state than previous noninvasive methods and may be useful in routine diagnostic monitoring of patients with PAH.

Figure 1

(A) Classical mechanical oscillator with components of mass (m), stiffness (k), and damping (c). The mass displaces only along the x-axis. (B) For our model, we postulate correspondence between the mass component and the fluid bolus traveling through the main pulmonary artery (MPA), between the spring (stiffness) and the driving force provided by the right ventricle (and the proximal arteries after systole), between the damper and the fluid viscous drag in the peripheral vessels, and between the displacement (x) and the flow through the MPA. RV, right ventricle.

Figure 2

Graphical user interface for semiautomatic impedance computation. At center transient PW Doppler data with an overlain computed velocity trace (red); at center bottom, the corresponding ECG signal (blue).

Figure 3

Multiple sets of experimental data (+) and average classical mechanical oscillator model fit obtained from multiple optimizations (line).

Figure 4

Univariate correlations between normalized classical mechanical oscillator model stiffness (k/BSA) and hemodynamically measured variables (A, B, pulmonary vascular resistance and stiffness—PVR and PVS, respectively; C, pulmonary flow—Q_p; D, stroke work—SW).

Figure 5

Univariate correlations between normalized classical mechanical oscillator model initial displacement (x₀ · BSA) and hemodynamically measured variables (A, pulmonary vascular stiffness—PVS; B, pulmonary flow—Q_p). BSA, body surface area.