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Determinants of Pulmonary Blood Flow Distribution

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Abstract

The primary function of the pulmonary circulation is to deliver blood to the alveolar capillaries to exchange gases. Distributing blood over a vast surface area facilitates gas exchange, yet the pulmonary vascular tree must be constrained to fit within the thoracic cavity. In addition, pressures must remain low within the circulatory system to protect the thin alveolar capillary membranes that allow efficient gas exchange. The pulmonary circulation is engineered for these unique requirements and in turn these special attributes affect the spatial distribution of blood flow. As the largest organ in the body, the physical characteristics of the lung vary regionally, influencing the spatial distribution on large‐, moderate‐, and small‐scale levels. © 2011 American Physiological Society. Compr Physiol 1:39‐59, 2011..

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Figure 1. Figure 1.

External scintillation counters recorded radioactivity over the chest wall of human subjects following inhalation of radioactive CO2. The clearance of radioactivity from a given region was assumed to be directly proportional to blood flow to that area. Radioactive counts at each level were determined by the field of view of the scintillation counter and represented the total radioactivity within an isogravitational plane. Blood flow appeared to increase down the lung.

Figure 2. Figure 2.

The lung compresses under its own weight. Because of gravity, alveoli are smaller, there are more vessels per unit volume, and the hydrostatic pressure is greater at the lung base.

Figure 3. Figure 3.

Experimental setup of West et al. to study the how the relationships between arterial, alveolar, and venous pressures affected the vertical distribution of blood flow in an excised lung. All of the pressures could be finely adjusted and accurately measured while regional blood flow was estimated by the clearance of radioactive gases using external scintillation counters.

Reproduced with permission from reference
Figure 4. Figure 4.

Initial three‐zone model of pulmonary perfusion popularized by John West .

Reproduced with permission from reference
Figure 5. Figure 5.

Diagrammatic representation of anatomic locations of lung regions with 25% highest (dark area) and 25% lowest (light shaded areas) vascular conductances. The areas of high conductance remain high and the low‐conductance areas remain low regardless of posture or lung volume.

Reproduced with permission from reference 12
Figure 6. Figure 6.

Left: Visual map of blood flow to ∼2‐cm3 lung pieces within a horizontal plane of a supine dog. Note the large heterogeneity of perfusion and the spatial organization with high‐flow regions near other high‐flow regions and low‐flow areas neighboring other low‐flow areas. Right: Vascular tree with asymmetrical branching that leads to neighboring regions having similar flows.

Reproduced with permission from reference
Figure 7. Figure 7.

Correlation in blood flow between lung regions as a function of distance between regions. Neighboring regions (centers of regions separated by 1.2 cm) were highly correlated (r = 0.676). Correlation between regions decreased with distance, eventually becoming negatively correlated.

Figure 8. Figure 8.

Regional perfusion using SPECT in which radiolabeled macroaggregate was injected and then imaged in different postures. Note that while the macroaggregate was injected in different postures, when imaged in the same posture, the distributions look very similar. Once injected, the macroaggregate does not move, so any apparent redistribution with posture represents a parenchymal shift.

Figure 9. Figure 9.

The effects of mechanical ventilation and increased alveolar pressure on the vertical distribution of blood flow in the lung. During spontaneous breathing (SB), there is a very small vertical gradient of perfusion. Mechanical ventilation increases this gradient and the addition of 20 cmH2O of positive end‐expiratory pressure (PEEP) further increases the vertical distribution. This experiment demonstrates that positive alveolar pressures are largely the cause of the vertical gradient of perfusion rather than the hydrostatic pressure within the blood vessels.

Reprinted with permission from reference
Figure 10. Figure 10.

The vertical gradient of blood flow in the lung is influenced by gravity. In this experiment, blood flow to nearly 1500 lung pieces was determined within the same animal during 2‐G supine, 0‐G supine, and 2‐G prone conditions. It is clear that gravity redistributes blood flow in the direction expected.

Figure 11. Figure 11.

Blood flow to nearly 1500 lung pieces within the same animal under 2‐G supine and 2‐G prone conditions. Note that despite the large difference in gravity and posture, high‐flow piece remain high flow and low‐flow piece remain low flow.

Figure 12. Figure 12.

Blood flow as a function of height up the lung in an upright primate. Data are from 1265 pieces of lung (2 cm3 in volume). Left: Data averaged within horizontal planes to reproduce the spatial resolution available at the time the gravitational model was conceptualized. Right: Same data but at a resolution that permits the heterogeneity of perfusion to be observed. At the lower spatial resolution, the data are remarkably similar to those of Hughes and West and gravity appears to be a major determinant of perfusion (r2 = 0.640). However, at the higher resolution, gravity can account for at most 28% of the variability in perfusion.

Reproduced with permission from reference
Figure 13. Figure 13.

The distribution of pulmonary perfusion is very stable over time. Blood flow was measured on ∼2‐cm3 lung pieces at six different time points, each separated by 20 min. These are data from one animal. High‐flow pieces remain high flow and low‐flow pieces remain low flow over 80 min in this set of experiments.

Reprinted with permission from reference
Figure 14. Figure 14.

The temporal variability of pulmonary blood flow is spatially clustered. Lung pieces with similar temporal patterns are near each other. In addition, there are complimentary patterns in which blood flow increases to one region at the expense of another region. These observations suggested that most of the variability in blood flow occurs at the level of lobar arteries.

From reference
Figure 15. Figure 15.

Pulmonary perfusion distribution is relatively fixed with both decreasing cardiac output (tilt) and increasing cardiac output (exercise).

Reprinted with permission from reference
Figure 16. Figure 16.

Scanning electron microscopy of alveolar capillaries showing the meshwork‐like covering of each alveolus.

With permission from Guntheroth and colleagues
Figure 17. Figure 17.

Alveolar capillary pathways as drawn from observations through the pleural surface of a laboratory animal. Wearn et al. noted that alveolar capillaries open and close over time without an apparent change in the driving pressures in the feeding artery. They also demonstrated that capillaries could be recruited by increasing cardiac output.

Reprinted with permission from reference
Figure 18. Figure 18.

The hypoxic pulmonary vasoconstriction (HPV) response to global hypoxia varies within regions of the lung. In this study by Lamm et al., nearly 2000 lung pieces (∼2 cm3 in volume) from each animal were clustered into groups defined by changes in the vascular resistance to each piece with gradated hypoxia. The clusters are color coded and then represented in their spatial location above. Note that piece with a similar HPV response are grouped together.



Figure 1.

External scintillation counters recorded radioactivity over the chest wall of human subjects following inhalation of radioactive CO2. The clearance of radioactivity from a given region was assumed to be directly proportional to blood flow to that area. Radioactive counts at each level were determined by the field of view of the scintillation counter and represented the total radioactivity within an isogravitational plane. Blood flow appeared to increase down the lung.



Figure 2.

The lung compresses under its own weight. Because of gravity, alveoli are smaller, there are more vessels per unit volume, and the hydrostatic pressure is greater at the lung base.



Figure 3.

Experimental setup of West et al. to study the how the relationships between arterial, alveolar, and venous pressures affected the vertical distribution of blood flow in an excised lung. All of the pressures could be finely adjusted and accurately measured while regional blood flow was estimated by the clearance of radioactive gases using external scintillation counters.

Reproduced with permission from reference


Figure 4.

Initial three‐zone model of pulmonary perfusion popularized by John West .

Reproduced with permission from reference


Figure 5.

Diagrammatic representation of anatomic locations of lung regions with 25% highest (dark area) and 25% lowest (light shaded areas) vascular conductances. The areas of high conductance remain high and the low‐conductance areas remain low regardless of posture or lung volume.

Reproduced with permission from reference 12


Figure 6.

Left: Visual map of blood flow to ∼2‐cm3 lung pieces within a horizontal plane of a supine dog. Note the large heterogeneity of perfusion and the spatial organization with high‐flow regions near other high‐flow regions and low‐flow areas neighboring other low‐flow areas. Right: Vascular tree with asymmetrical branching that leads to neighboring regions having similar flows.

Reproduced with permission from reference


Figure 7.

Correlation in blood flow between lung regions as a function of distance between regions. Neighboring regions (centers of regions separated by 1.2 cm) were highly correlated (r = 0.676). Correlation between regions decreased with distance, eventually becoming negatively correlated.



Figure 8.

Regional perfusion using SPECT in which radiolabeled macroaggregate was injected and then imaged in different postures. Note that while the macroaggregate was injected in different postures, when imaged in the same posture, the distributions look very similar. Once injected, the macroaggregate does not move, so any apparent redistribution with posture represents a parenchymal shift.



Figure 9.

The effects of mechanical ventilation and increased alveolar pressure on the vertical distribution of blood flow in the lung. During spontaneous breathing (SB), there is a very small vertical gradient of perfusion. Mechanical ventilation increases this gradient and the addition of 20 cmH2O of positive end‐expiratory pressure (PEEP) further increases the vertical distribution. This experiment demonstrates that positive alveolar pressures are largely the cause of the vertical gradient of perfusion rather than the hydrostatic pressure within the blood vessels.

Reprinted with permission from reference


Figure 10.

The vertical gradient of blood flow in the lung is influenced by gravity. In this experiment, blood flow to nearly 1500 lung pieces was determined within the same animal during 2‐G supine, 0‐G supine, and 2‐G prone conditions. It is clear that gravity redistributes blood flow in the direction expected.



Figure 11.

Blood flow to nearly 1500 lung pieces within the same animal under 2‐G supine and 2‐G prone conditions. Note that despite the large difference in gravity and posture, high‐flow piece remain high flow and low‐flow piece remain low flow.



Figure 12.

Blood flow as a function of height up the lung in an upright primate. Data are from 1265 pieces of lung (2 cm3 in volume). Left: Data averaged within horizontal planes to reproduce the spatial resolution available at the time the gravitational model was conceptualized. Right: Same data but at a resolution that permits the heterogeneity of perfusion to be observed. At the lower spatial resolution, the data are remarkably similar to those of Hughes and West and gravity appears to be a major determinant of perfusion (r2 = 0.640). However, at the higher resolution, gravity can account for at most 28% of the variability in perfusion.

Reproduced with permission from reference


Figure 13.

The distribution of pulmonary perfusion is very stable over time. Blood flow was measured on ∼2‐cm3 lung pieces at six different time points, each separated by 20 min. These are data from one animal. High‐flow pieces remain high flow and low‐flow pieces remain low flow over 80 min in this set of experiments.

Reprinted with permission from reference


Figure 14.

The temporal variability of pulmonary blood flow is spatially clustered. Lung pieces with similar temporal patterns are near each other. In addition, there are complimentary patterns in which blood flow increases to one region at the expense of another region. These observations suggested that most of the variability in blood flow occurs at the level of lobar arteries.

From reference


Figure 15.

Pulmonary perfusion distribution is relatively fixed with both decreasing cardiac output (tilt) and increasing cardiac output (exercise).

Reprinted with permission from reference


Figure 16.

Scanning electron microscopy of alveolar capillaries showing the meshwork‐like covering of each alveolus.

With permission from Guntheroth and colleagues


Figure 17.

Alveolar capillary pathways as drawn from observations through the pleural surface of a laboratory animal. Wearn et al. noted that alveolar capillaries open and close over time without an apparent change in the driving pressures in the feeding artery. They also demonstrated that capillaries could be recruited by increasing cardiac output.

Reprinted with permission from reference


Figure 18.

The hypoxic pulmonary vasoconstriction (HPV) response to global hypoxia varies within regions of the lung. In this study by Lamm et al., nearly 2000 lung pieces (∼2 cm3 in volume) from each animal were clustered into groups defined by changes in the vascular resistance to each piece with gradated hypoxia. The clusters are color coded and then represented in their spatial location above. Note that piece with a similar HPV response are grouped together.

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Robb W. Glenny, H. Thomas Robertson. Determinants of Pulmonary Blood Flow Distribution. Compr Physiol 2010, 1: 39-59. doi: 10.1002/cphy.c090002