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1 Unit of Critical Care and 2 Department of Imaging, National Heart and Lung Institute, Imperial College School of Medicine, Royal Brompton Hospital, London SW3 6NP, United Kingdom
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Acute respiratory distress syndrome is characterized by alterations in the ventilation-perfusion ratio. Present techniques for studying regional pulmonary perfusion are difficult to apply in the critically ill. Electron-beam computed tomography was used to study the effects of prone positioning on regional pulmonary perfusion in six healthy subjects. Contrast-enhanced sections were obtained sequentially in the supine, prone, and (original) supine positions at full inspiration. Regions of interest were placed along the nondependent to dependent axis and relative perfusion calculated. When corrected for the redistribution of lung parenchyma, a gravitational gradient of pulmonary perfusion existed in both supine and prone positions. The distribution of perfusion between the supine or prone positions did not differ, but data analysis using smaller regions of interest demonstrated marked heterogeneity of perfusion between anatomically adjacent regions of lung. The distribution of lung parenchyma was more uniform in the prone position. Gravity was estimated to be responsible for 22-34% of perfusion heterogeneity in the supine and 27-41% in the prone positions. These data support the hypothesis that factors other than gravity may be at least as important in determining the distribution of pulmonary perfusion in humans. The influence of nongravitational factors may not be detectable if techniques that sample large tissue volumes are employed.
physiology; normal individuals; repositioning
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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PRONE POSITIONING IMPROVES arterial oxygenation in ~70% of adult patients with acute respiratory distress syndrome (ARDS) undergoing mechanical ventilation (3, 21, 27). Several mechanisms have been proposed to explain this improvement, including favorable changes in ventilation-perfusion matching leading to a decrease in shunt fraction (1). Traditionally, a gravitational distribution of pulmonary perfusion has been described in normal subjects, sustained in all postures and determined by the interrelationship between hydrostatic, alveolar, and interstitial pressures (10, 15, 36). However, in some studies, the gravitational gradient has been reported to decrease in the prone position (31). Moreover, animal experiments employing high spatial resolution techniques have reported no redistribution of perfusion in the prone position (5, 6), suggesting that the influence of gravity is less important than the structure of the pulmonary vascular tree in determining regional blood flow in the lung (7). The degree to which these apparent discrepancies in results are attributable to species differences or to variations in spatial resolution between the techniques employed is unclear.
Several approaches have been employed to measure regional pulmonary perfusion, but most have significant limitations when applied in the clinical setting. Electron-beam computed tomography (EBCT) allows fast (millisecond) acquisition of the data necessary for cardiac imaging (26). Regional blood flow can be calculated by applying an appropriate model to changes in lung density detected by following the passage of contrast. EBCT has been used previously in animal and clinical studies of perfusion (22, 34, 38), the results obtained showing a good correlation with those from microsphere-based investigations.
The first aim of the present study was therefore to characterize the distribution of regional pulmonary perfusion in healthy human subjects, in both supine and prone positions, during the application of positive-pressure ventilation using EBCT. Second, to address issues concerning the influence of spatial resolution, data were analyzed by use of regions of interest (ROI) of differing size.
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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The protocol for these investigations was approved by the Ethics Committee of the Royal Brompton Hospital, and informed consent was obtained from all participants. In all studies, subjects were placed in the supine position within the computerized tomography (CT) scanner (Imatron C150L, Imatron, San Francisco, CA) and established on intermittent positive-pressure ventilation administered via a mouthpiece (Evita II, Drager, Lubeck, Germany), using an inspired oxygen concentration of 0.21 and tidal volume (VT) of 10-12 ml/kg.
CT scanning protocol. For the purpose of constructing time-density curves, a rapid multisection scan acquisition was performed at a single level, immediately before and after the rapid, automated injection (60 ml at 20 ml/s; Angiomat 6000, Liebal-Flarsheim, UK) of radiopaque contrast material (Omnipaque 300 iodine mg/ml, Nycomed, Amersham, UK), via a 16-gauge cannula placed in an antecubital fossa vein. Fifteen to twenty 6-mm sections were obtained in each study. The acquisition time for each section was 100 ms. The interval between the acquisition of each image was designed to allow construction of complete time-density curves for the lung parenchyma and left-sided circulation (descending aorta). The scans were electrocardiogram gated, and each series was performed during an inspiratory breath-holding maneuver.
After commencement of positive-pressure ventilation, each subject was left for 15 min to achieve a steady state, after which a multisection scan was obtained at a level 2-3 cm above the right hemidiaphragm. On completion, the subject's position was marked externally with a laser alignment device. The subject was turned into the prone position, and, after an identical 15-min stabilization period, a second multisection scan was performed at the same level. The subject was then returned to the supine position, aligned as for the first scan, and a final multisection scan was obtained after a further 15 min. Comparable positioning of the prone and second supine scans was additionally confirmed by matching of the pulmonary branching pattern. During each inspiratory breath-hold maneuver, the plateau pressure and VT were noted from the ventilator display.Calculation of perfusion using EBCT.
By using EBCT and following the Sapirstein principle (33),
perfusion can be calculated by using equations derived from
conventional microsphere approaches to blood flow analysis (8, 9,
32, 37)
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Pul is the
peak Hounsfield unit (HU) change due to contrast material, and
CDA dt is the area under the time-density
curve for the descending aorta by a gamma variate fit.
To express blood flow per unit volume of lung parenchyma, it is assumed
that the ROI is composed of air and "water" (i.e., blood and
parenchyma). The disparate densities of these components allow the
fraction of each to be calculated by using the CT gray scale or
Hounsfield number for any ROI. For example, the water fraction can be
calculated by subtracting the CT value of pure air from the mean CT
value of an ROI to give a value reflecting the amount (density) of
parenchyma and blood present in the selected region. Comparing this
value to the continuum ranging from water (0 HU) to air (1,000 HU)
allows the percentage of the ROI that is water (blood and
parenchyma) to be calculated thus (34)
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"water"
fraction. Furthermore, the amount of blood present within an ROI can be computed by comparing the time-density curve of the ROI to that of the
feeding/draining vessel
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Image analysis.
The images obtained were viewed on an off-line workstation and analyzed
by use of the scanner's proprietary software (version 12.4, Imatron,
San Francisco, CA). ROI were placed in five regions, at 10, 30, 50, 70 and 90% of the dependent-nondependent lung distance, and time-density
curves were constructed for each ROI by using a gamma-variate fit to
exclude recirculation. Two approaches were used to calculate perfusion
in each sample region: first, a single ROI (ROIS) with an
approximate sample area of 7-10 cm2 (volume 4-6
cm3) and, second, multiple smaller ROI (ROIM)
with an approximate sample area of 1 cm2 (volume 0.6 cm3), aiming to avoid all pulmonary vessels (Fig.
1). In both cases, perfusion was
calculated by using the technique previously outlined and was expressed
as a fraction of the mean perfusion of the given section. The mean
perfusion was obtained from an ROI that outlined the whole of the lung
section, excluding the hilar and central vessels.
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Statistical analysis.
Comparisons between ventilatory parameters during each intervention and
differences in regional perfusion (ROIS) under the same
study conditions were made by using analyses of variance (Prism v3.1,
Graphpad, San Diego, CA). For comparisons of perfusion distributions
(ROIS) under different study conditions, a two-way analysis
of variance was applied. For comparison of perfusion gradients using
both ROIS and ROIM, linear regression analysis was applied. The coefficient of correlation used to quantify the strength of any linear relationship observed, and the square of the
coefficient of correlation was used to quantify the proportion of flow
variability explicable by the independent variable. A P
value of 
0.05 was considered statistically significant.
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Six healthy, nonsmoking male subjects (age range 23-44 yr)
were studied. All tolerated the procedure without difficulty or adverse
effects. During the course of the study, there was a small but
statistically significant increase in VT (from 0.89 ± 0.01 to 0.98 ± 0.04 liters; P = 0.05) but
no difference in plateau pressure (P > 0.05) (Table
1). In one subject, it was not possible using ROIS to estimate accurately the area under the
time-density curve for the lung and therefore corrected perfusion
values, and tissue composition data were impossible to obtain.
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With the use of ROIS to examine uncorrected perfusion, a
nondependent-to-dependent gradient was apparent in both supine and prone positions (P < 0.01, Fig.
2). There was no difference in the
distribution of perfusion between the two supine scans (data not shown,
P > 0.05) nor between the relative perfusion values in
either position (P = 0.91, Fig. 2). Although the
gradient of perfusion was less in the prone position, this failed to
reach statistical significance (1.30 vs. 1.02%mean
perfusion/%height of lung section, supine vs. prone; P = 0.15, Fig. 2).
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With the use of ROIM to examine uncorrected perfusion, the
variation in perfusion values in anatomically adjacent regions was
marked (Fig. 2). A nondependent-to-dependent gradient was apparent in
both positions (r2 = 0.74 supine;
r2 = 0.68: P < 0.01) but
was more uniform in the prone position with evidence of redistribution
of perfusion to nondependent regions (1.15 vs. 0.94%mean
perfusion/%height of lung section, supine vs. prone; P < 0.001).
When perfusion (ROIS, ROIM) was corrected for
the volume of lung parenchyma (Fig.
3), the gravitational
gradient persisted with the use of both methods of analysis in both
positions, although it was reduced. When ROIS was used,
there was no significant difference in the distribution of perfusion
between the two supine scans (data not shown P > 0.05), nor between supine and prone positions (P > 0.24). When ROIM analysis was used, the relationship
between nondependent/dependent position and relative perfusion was
weaker than that seen for uncorrected perfusion values
(r2 = 0.22 supine;
r2 = 0.28 prone: P < 0.01). The data also revealed decreased perfusion in the lowest regions
of the lung section. In such areas, it has been shown that other
factors, such as differences in alveolar ventilation and increased
tissue pressure, may exert an additional effect on pulmonary perfusion.
Thus excluding data from the lowest 20% of the lung section
strengthened the relationship between nondependent/dependent
position and relative perfusion (r2 = 0.34 supine, r2 = 0.41 prone; P < 0.01). With either means of analysis, there was no difference in the
gradient of the perfusion distributions in either position
(P = 0.81-0.98).
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When using ROIS, there was an increase in lung parenchyma
per unit volume of tissue in the supine position moving from
nondependent to dependent lung regions (P < 0.01)
(Fig. 4). By contrast, no such gradient
was seen in the prone position, the distribution of lung parenchyma
being uniform across the lung section (P > 0.74). When
ROIM was used, a vertical gradient in lung parenchyma per
unit volume of tissue was observed in both supine and prone positions
(P < 0.01). In the prone position, the gradient of the distribution was less pronounced (P < 0.01) (Fig. 4).
Tissue composition data (ROIS) are not shown but are
available from the authors by request.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Changing ventilation-perfusion relationships through prone positioning has assumed increasing therapeutic significance in critically ill patients with lung injury requiring mechanical ventilation. EBCT can quantify pulmonary blood flow and may provide further insights into this physiological response. To our knowledge, this study is the first to employ this approach to investigate regional pulmonary perfusion in human subjects, mechanically ventilated to reproduce the effects of ventilatory support applied to critically ill patients.
In the present study, we have demonstrated a vertical gradient of perfusion that persists in the supine and prone positions. This might be predicted in that lung tissue is compressible, leading to a greater tissue density in dependent regions. However, the preservation of this gradient after volume correction suggests the existence of a true gravitational effect in both positions. Our data also suggest that, in the prone position, uncorrected perfusion was slightly increased in nondependent regions. However, this less steep gradient did not persist when perfusion was corrected for tissue volume, suggesting that it is attributable to the redistribution of lung tissue. Indeed, in this study, the distribution of lung parenchyma was more uniform in the prone position. Although not a direct measure of regional ventilation, because studies were timed to end-inspiration, the more uniform distribution of parenchyma supports the concept of a more even distribution of ventilation in the prone position (19, 20, 29).
Second, we aimed to investigate the influence of spatial resolution by analyzing data using ROI of differing sizes. Although higher resolution sampling did not significantly alter the distribution of perfusion observed in either position, it gives much clearer insights into the degree of perfusion heterogeneity within the lung and raises the possibility that factors other than gravity may be equally or more important in determining the distribution of pulmonary perfusion. The influence of gravity on the distribution of pulmonary perfusion has been traditionally explained by the interrelationships among alveolar, pulmonary arterial and venous, and interstitial pressures (15, 35, 36). The gravitational distribution has since been demonstrated in all postures, although it may be less pronounced in the prone position (10, 31). Recent studies in animals using injected microspheres and high-spatial-resolution techniques have suggested that the branching pattern of the pulmonary vascular tree leads to more heterogeneity of perfusion than could be explained by gravity alone, the so-called fractal hypothesis (5, 6). Gravity was found to account for only 2-10% of the perfusion heterogeneity in the prone and supine postures in dogs (6) but up to 27% in upright baboons (5). In experimental dogs, blood flow remained preferentially distributed to nondependent dorsal regions when prone (6).
Our results are both in agreement and at variance with these studies. Using ROIM, we found high levels of perfusion heterogeneity throughout the lung section. Moreover, in the present study, gravity accounted for 22-31% and 27-41% of perfusion heterogeneity in the supine and prone positions, respectively. These findings are comparable to those described in recent animal studies, although the effect of gravity is seemingly slightly greater in humans. In support of our findings, studies performed during spaceflight reveal that the distribution of pulmonary blood flow is more uniform under conditions of microgravity (30), suggesting that gravity does indeed play a role in the distribution of perfusion in humans under normal conditions.
By contrast, several factors could explain the differences between our data and these recent animal studies. First, it has been suggested that, in quadrupeds, gravity may not be as important a determinant of regional pulmonary blood flow because of their relatively smaller lung volumes (14, 15). Second, the pulmonary vasculature of most laboratory animals is more muscularized, with a different distribution of vascular resistance. In humans (as well as other primates), a smaller fraction of vascular resistance resides in the microvasculature; therefore, the gravitational effects of hydrostatic pressure may be more marked (14). Third, the application of positive-pressure ventilation accentuates the normal ventral-dorsal gradient of pulmonary perfusion in the supine position (11, 12, 15, 18) and could partly explain the more prominent gravitational gradient observed in our study. Finally, differences in animal size, and therefore vertical gravitational gradient, may also have an effect.
Technical considerations may interfere with the ability of EBCT to measure regional pulmonary perfusion. Both experimental (16, 24) and clinical (2, 9, 17, 23, 32) studies indicate a correlation between EBCT-generated measures of perfusion and "true" perfusion values derived from conventional techniques. However, EBCT measures of perfusion may underestimate true perfusion, principally because of early washout of contrast from the ROI. This effect is most pronounced at higher flow rates, so it is possible that our results represent an underestimation of the true gravitational gradient. Second, unlike mechanical CT scanners, the X-ray source of the EBCT does not rotate about the scanned object through a full 360° (26). Consequently, irradiation of the patient, scatter, and noise distribution are radially asymmetrical. In the present study, the descending aorta was used as the reference when calculating pulmonary perfusion. In the prone position, the nondependent descending aorta lies in a region of higher exposure variability. Furthermore, in the prone position, beam hardening from contrast-enhanced intracardiac blood interposed between the beam and descending aorta may affect density values (4). However, if such considerations are valid, reference values in the prone position should have been consistently less than those for the supine scans. This was not the case after analysis of curves from individual subjects. Third, radiographic contrast agents may influence vascular tone (13, 25, 28). However, we identified no difference in the distribution of perfusion nor between the reference values when comparing the two supine scans, arguing against a significant vasodilator effect due to contrast.
The degree of random noise inherent in our data and its possible effect
on our estimations of a gravitational effect are more difficult to
calculate. Our data do not represent repeated measures; therefore,
accurate estimates of random noise are not possible. EBCT measures of
parenchymal density encountered during this study ranged between 600
and 950 HU, and the standard deviation for the given values within
this range was ±5-10 HU. Although we express the degree of
perfusion heterogeneity due to gravitational forces estimated by our
data as between (at least) 22 and (at most) 41%, depending on the
position and region of the lung section examined, this leaves
59-78% of perfusion heterogeneity to be explained by other
factors. These include the structure of the pulmonary vascular tree, effects of positive-pressure ventilation, regional changes in local alveolar pressures, and differences in cardiac output between subjects, as well as the effect of random noise. However, we suggest it to be unrealistic to attempt to apportion the
amount of this unexplained range that is due to random noise, because
the wide differences in levels of perfusion within the lung section
would cause any estimates for coefficients of variation for the data to
vary, depending on the region examined.
In summary, we have shown that the regional distribution of pulmonary perfusion may be quantified in human subjects by using EBCT. Our findings concur with recent animal studies that suggest that there is a large degree of perfusion heterogeneity with the lung, which is only partly explained by the effects of gravity. The influence of nongravitational factors, which include the anatomical arrangement of the pulmonary vasculature tree, may not be accurately identified when techniques that use larger ROI are employed.
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ACKNOWLEDGEMENTS |
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A. T. Jones was supported by a Smith and Nephew Fellowship. Work supported in part by the British Lung Foundation.
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FOOTNOTES |
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Address for reprint requests and other correspondence: T. W. Evans, Royal Brompton Hospital, Sydney St., London SW3 6NP, UK.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 28 December 1999; accepted in final form 21 November 2000.
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
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, Pooled supine position data; 
, prone
position data. A: ROIS; data are means ± SE. A significant nondependent-to-dependent perfusion gradient was seen
in both positions (*P < 0.01). The perfusion gradient
in the prone position was more uniform but not statistically
significant (P = 0.15). B: ROIM.
Linear relationships between vertical height and regional perfusion:
solid line, supine position; broken line, prone position. A vertical
gradient perfusion was observed in both positions (P < 0.01). In the prone position, the gradient of the distribution was less
pronounced (P < 0.01). In both positions, there was
evidence of marked perfusion heterogeneity between anatomically close
regions of lung.
