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Pulmonary Vascular Dynamics

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ABSTRACT

The pulmonary circulation carries deoxygenated blood from the systemic veins through the pulmonary arteries to be oxygenated in the capillaries that line the walls of the pulmonary alveoli. The pulmonary circulation carries the cardiac output with a relatively low driving pressure, and so differs considerably in structure and function from the systemic circulation to maintain a low‐resistance vascular system. The pulmonary circulation is often considered to be a quasi‐static system in both experimental and computational studies of pulmonary perfusion and its matching to ventilation (air flow) for exchange. However, the system is highly dynamic, with cardiac output and regional perfusion changing with posture, exercise, and over time. Here we review this dynamic system, with a focus on understanding the physiology of pulmonary vascular dynamics across spatial and temporal scales, and the changes to these dynamics that are reflective of disease. © 2019 American Physiological Society. Compr Physiol 9:1081‐1100, 2019.

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Figure 1. Figure 1. Suggested time‐course of the response of the pulmonary circulation to hypoxic vasoconstriction. Human data, typically obtained under moderate hypoxia (>30 mmHg) typically follows the purple curve. Figure is reproduced from (), with permission.
Figure 2. Figure 2. Visualization of pulmonary blood flow in the largest pulmonary arteries using a 4D MRI flow technique implemented using standard Cartesian k‐space trajectory in a sagittal oblique 3D volume covering the central pulmonary arteries after venous administration of a contrast agent. (A) Shows time‐resolved pathlines and 2D images to show vessel morphology, (B) shows the temporal changes in blood flow velocity in the main pulmonary artery (PA) and the left and right PAs. Image is reproduced from (), with permission.
Figure 3. Figure 3. Pulmonary vascular impedance is derived from simultaneous measurements of pulmonary artery flow and pressure (A) summarizes typical data acquisition and analysis techniques, (B) shows the typical shape of the impedance modulus including important measurable quantities, (C) indicates the elevation in impedance and change in shape of the impedance modulus with frequency typical of pulmonary vascular disease, and (D) shows key metrics derived from pulmonary artery pressure waveforms in the time domain. This figure is reproduced from (), with permission.
Figure 4. Figure 4. A schematic of a typical pulmonary artery pressure wave form obtained from catheterization, with metrics quantifying the nature of the waveform indicated. Metrics defining the pressure waveform are DPAP = diastolic pulmonary artery pressure, PAPP = pulmonary artery pulse pressure, SPAP = systolic pulmonary artery pressure. Characteristics reflecting the balance of forward and reflected components of the waveform are Pi = pulmonary artery pressure at the inflection point (representing the end of the forward wave), SPAP‐Pi = an estimate of the magnitude of the reflected wave, Ti = transit time. A further metric of wave reflection is SPAP‐Pi/PAPP, which is used to quantify the extent of wave reflection. Reproduced from (), with permission.
Figure 5. Figure 5. Computational model predictions of main pulmonary artery impedance spectra in a symmetric model of the pulmonary vasculature (solid gray line), a model with anatomical branching asymmetry but no gravitational influence (dashed gray line), and a model with anatomical branching asymmetry and gravitational effects incorporated. The impact of anatomical vascular branching is to produce wave reflections, which allow predictive models to reflect normal pulmonary impedance spectra. Gravity, on the other hand, plays a negligible role in determining the main pulmonary artery impedance spectrum. Model predictions are reproduced from (), with permission.


Figure 1. Suggested time‐course of the response of the pulmonary circulation to hypoxic vasoconstriction. Human data, typically obtained under moderate hypoxia (>30 mmHg) typically follows the purple curve. Figure is reproduced from (), with permission.


Figure 2. Visualization of pulmonary blood flow in the largest pulmonary arteries using a 4D MRI flow technique implemented using standard Cartesian k‐space trajectory in a sagittal oblique 3D volume covering the central pulmonary arteries after venous administration of a contrast agent. (A) Shows time‐resolved pathlines and 2D images to show vessel morphology, (B) shows the temporal changes in blood flow velocity in the main pulmonary artery (PA) and the left and right PAs. Image is reproduced from (), with permission.


Figure 3. Pulmonary vascular impedance is derived from simultaneous measurements of pulmonary artery flow and pressure (A) summarizes typical data acquisition and analysis techniques, (B) shows the typical shape of the impedance modulus including important measurable quantities, (C) indicates the elevation in impedance and change in shape of the impedance modulus with frequency typical of pulmonary vascular disease, and (D) shows key metrics derived from pulmonary artery pressure waveforms in the time domain. This figure is reproduced from (), with permission.


Figure 4. A schematic of a typical pulmonary artery pressure wave form obtained from catheterization, with metrics quantifying the nature of the waveform indicated. Metrics defining the pressure waveform are DPAP = diastolic pulmonary artery pressure, PAPP = pulmonary artery pulse pressure, SPAP = systolic pulmonary artery pressure. Characteristics reflecting the balance of forward and reflected components of the waveform are Pi = pulmonary artery pressure at the inflection point (representing the end of the forward wave), SPAP‐Pi = an estimate of the magnitude of the reflected wave, Ti = transit time. A further metric of wave reflection is SPAP‐Pi/PAPP, which is used to quantify the extent of wave reflection. Reproduced from (), with permission.


Figure 5. Computational model predictions of main pulmonary artery impedance spectra in a symmetric model of the pulmonary vasculature (solid gray line), a model with anatomical branching asymmetry but no gravitational influence (dashed gray line), and a model with anatomical branching asymmetry and gravitational effects incorporated. The impact of anatomical vascular branching is to produce wave reflections, which allow predictive models to reflect normal pulmonary impedance spectra. Gravity, on the other hand, plays a negligible role in determining the main pulmonary artery impedance spectrum. Model predictions are reproduced from (), with permission.
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Teaching Material

A. Clark, M. Tawhai. Pulmonary Vascular Dynamics. Compr Physiol 9: 2019, 1079-1098.

Didactic Synopsis

Major Teaching Points:

  • Structure and function of the pulmonary vasculature
    • To serve its primary function the pulmonary vasculature has a complex branching structure
    • The branching of the pulmonary circulation facilitates delivery of blood regionally
    • Gravity has an important role in delivery of blood to the gas exchange surface
  • Temporal changes in pulmonary perfusion and the balance between spatial and temporal heterogeneities
    • Blood flow is pulsatile and so is dynamic over a heart beat
    • Active control of blood flow regionally, and remodelling of the vasculature in disease means that important timescales in understanding the function of the pulmonary circulation vary from seconds to years
  • Metrics of pulmonary vascular dynamics
    • Vascular dynamics can be assessed in great detail in the pulmonary macro-circulation
    • Clinically, static measures of function are primarily used
    • The dynamics of pulmonary blood flow as a function of vascular resistance and compliance can be assessed in the frequency and time domain
    • Factoring for the dynamics of flow, in addition to static metrics allows distinction between pathologies that is not possible with static metrics alone

Didactic Legends

The figures—in a freely downloadable PowerPoint format—can be found on the Images tab along with the formal legends published in the article. The following legends to the same figures are written to be useful for teaching.

Figure 1 Teaching points: The pulmonary vascular response to hypoxia is multiphasic and typically shows an acute and chronic response. There appears to be differential response to hypoxia between moderate and severe hypoxia.

Figure 2 Teaching points: Flow dynamics can be measured in detail in the major pulmonary arteries. Disease significantly impacts on these dynamics, introducing perturbations to normal flow conditions.

Figure 3 Teaching points. Simultaneous measurement of pressure and flow in the main pulmonary arteries provides a metric of vascular resistance and stiffness (impedance). Impedance provides more useful information that static measures of vascular resistance because if accounts for stiffness and dynamic changes in blood flow and pressure.

Figure 4 Teaching points: Time domain analyses of pulmonary artery pressure are often simpler to interpret than impedance measures. Several metrics of wave intensity and reflection can be derived from the pressure waveform. However, as the relationship between pressure and flow is obtained the sensitivity of pressure waveform analysis to disease may be limited.

Figure 5 Teaching points: The asymmetry of branching in the pulmonary arterial tree significantly contributes to impedance in the main pulmonary artery. If asymmetry is amplified in disease states, this will be reflected in impedance spectra.

 


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How to Cite

Alys Clark, Merryn Tawhai. Pulmonary Vascular Dynamics. Compr Physiol 2019, 9: 1081-1100. doi: 10.1002/cphy.c180033