September 1999
Volume 40, Issue 10
Free
Physiology and Pharmacology  |   September 1999
Regional Differences in Retinal Vascular Reactivity
Author Affiliations
  • Hak Sung Chung
    From the Department of Ophthalmology, Indiana University School of Medicine, Indianapolis;
  • Alon Harris
    From the Department of Ophthalmology, Indiana University School of Medicine, Indianapolis;
  • Paul J. Halter
    Division of Vision Sciences, Aston University, Birmingham, United Kingdom; and
  • Larry Kagemann
    From the Department of Ophthalmology, Indiana University School of Medicine, Indianapolis;
  • Emma J. Roff
    Division of Vision Sciences, Aston University, Birmingham, United Kingdom; and
  • Hanna J. Garzozi
    From the Department of Ophthalmology, Indiana University School of Medicine, Indianapolis;
  • Sarah L. Hosking
    Division of Vision Sciences, Aston University, Birmingham, United Kingdom; and
  • Bruce J. Martin
    Medical Sciences Program, Indiana University, Bloomington.
Investigative Ophthalmology & Visual Science September 1999, Vol.40, 2448-2453. doi:https://doi.org/
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      Hak Sung Chung, Alon Harris, Paul J. Halter, Larry Kagemann, Emma J. Roff, Hanna J. Garzozi, Sarah L. Hosking, Bruce J. Martin; Regional Differences in Retinal Vascular Reactivity. Invest. Ophthalmol. Vis. Sci. 1999;40(10):2448-2453. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

purpose. Although glaucomatous visual field defects are more common in the superior field than in the inferior field, microaneurysms are more frequent in the superior than in the inferior retina in diabetic retinopathy. The authors hypothesized that differences in vascular hemodynamics in the two areas might contribute to these phenomena.

methods. The blood flow response to hyperoxia and hypercapnia was evaluated in peripapillary retinal tissue superior and inferior to the optic nerve head using confocal scanning laser Doppler flowmetry. In 14 young, healthy persons, blood flow was measured while breathing room air and during isocapnic hyperoxia (100% O2 breathing) and isoxic hypercapnia (Pco2 increased 15% above baseline). Histograms were generated from pixel-by-pixel analysis of retinal portions of superior and inferior temporal quadrants of the entire image.

results. Baseline blood flow in the inferior temporal quadrant was significantly greater than in the superior temporal quadrant (P < 0.05). However, the inferior region failed to increase in perfusion during hypercapnia and experienced significant mean blood flow reduction; flow reduction in the pixels at the 25th, 50th, 75th, and 90th percentile of flow; and an increased percentage of pixels without measurable flow, during hyperoxia (each P < 0.05). In contrast, in the superior temporal region, hyperoxia failed to reduce blood volume, velocity, or flow, whereas hypercapnia significantly increased mean flow; increased flow in the pixels at the 25th, 50th, 75th, and 90th percentile of flow; and reduced the percentage of pixels without measurable flow (each P < 0.05).

conclusions. The inferior temporal quadrant of the peripapillary retina is, in comparison with the superior temporal region, less responsive to vasodilation and more responsive to vasoconstriction. These differences could contribute to different susceptibility to visual field defect or vascular dysfunction in the superior and inferior retina.

Defects in the superior visual field are more common than in the inferior visual field in glaucoma. 1 Further, narrowing of the retinal arteries and veins, a development that occurs in proportion to disease severity, is most pronounced inferiorly. 2 In contrast, in diabetic retinopathy, microaneurysms, and acellular capillaries are more than twice as common in the superior than in the inferior retina. 3 Additionally, enlargement of the retinal veins, a change that correlates with the severity of disease and the magnitude of hyperglycemia, is also most pronounced superiorly. 4 The mechanisms that give rise to these distinct, disease-specific regional differences in vascular and visual field defect have not been defined. 
It is possible that differences in vulnerability to ischemic insult or to hyperglycemic damage arise from inherent retinal regional differences in vasoreactivity. To test this hypothesis, we compared the blood flow responses of the inferior and superior retinal regions to vasoconstrictor and vasodilator stimuli. Hyperoxia, which provokes cerebral and whole-retinal vasoconstriction, 5 and hypercapnia, which dilates arteries and arterioles within the brain and the eye, 6 were used as vasoprovocative stimuli. Differing responses of the superior and inferior retina to these stimuli would support the hypothesis that these retinal regions differ in their susceptibility to ischemic or hyperglycemic insult. 
Materials and Methods
Subjects
Fourteen healthy volunteers (7 men, 7 women; mean age, 27 ± 6 years; age range, 18–40 years) participated in the study. Subjects had normal eye examinations, with corrected visual acuity 20/30 or better, intraocular pressure (IOP) below 22 mm Hg, refractive error between −6.00 and +2.00 diopters, and astigmatism less than 1.50 diopters cylinder. Subjects were free from heart or lung disease, had no family history of glaucoma or diabetes, and were not pregnant or anticipating pregnancy at the time of study. All procedures conformed to the tenets of the Declaration of Helsinki and were reviewed and approved by an institutional review board, with subjects signing informed consent. 
Experimental Design
Two experimental sessions, one involving hyperoxia and the other hypercapnia, took place on separate days. The mean interval between experiments was 10 ± 5 days (range, 2–19 days). Ocular blood flow was measured using confocal scanning laser Doppler flowmetry (cSLDF, Heidelberg Retinal Flowmeter; Heidelberg Engineering, Heidelberg, Germany). Heart rate and arterial oxygen saturation were monitored using pulse oximetry. After 5 minutes acclimation, baseline recordings were made with the subject breathing room air. End-tidal CO2 and O2 were monitored continuously from a mouthpiece (Pulse Oximeter and End-Tidal Gas Analyzer: POET II model 602-3, Criticare Systems, Milwaukee, WI). 
Hyperoxia and Hypercapnia
Hyperoxia was induced by adding 100% O2 to the inspired gas mixture; CO2 was added to maintain isocapnia during this procedure. Five minutes after the end-tidal O2 fraction exceeded 70%, ocular blood flow measurements were made. In experiments involving hypercapnia, end-tidal Pco 2 was elevated 15% above baseline levels for 5 minutes before measurement of ocular blood flow. Elevation of Pco 2 was accomplished by addition of 4 to 6% CO2 to the inspiratory gas mixture. 
Measurement of Ocular Blood Flow: cSLDF
One eye from each subject was randomly selected for study. With undilated pupils, subjects fixed on a static target 3 feet away. Using a 10° field, two mapped images (superior and inferior) were obtained across the optic nerve head for each experimental condition. Images were focused on the superficial retina, with focus setting and anatomic location constant across all images from a given subject. 
One observer reviewed all images (Fig. 1) . Unlike conventional analysis that uses a single 10 pixel × 10 pixel sample, each qualifying pixel from the superficial peripapillary retinal field within the 256 × 64 pixel image was included in the analysis (Fig. 1) . This methodology significantly increases the reproducibility of measurements of blood velocity, volume, and flow. 7 Excluded were pixels from the cup and rim (which were poorly focused), pixels from major blood vessels, image areas interrupted by movement saccades, and areas without acceptable levels of brightness (any brightness [DC] value <70 or >200). To ensure that the same retinal locations were used for each image, a transparent overlay was used to map the retinal vasculature of each optic nerve head. This template was then overlaid on the image, and the temporal peripapillary area was separated into inferior and superior divisions. To produce a histogram, the total number of pixels for all images was determined, the average was calculated, and a normalized pixel count was calculated that gave equal weight to each subject. Pixels with less than one arbitrary unit of flow were counted as “zero flow” pixels. The number of zero flow pixels and the flow, volume, and velocity in pixels at the 25th, 50th, 75th, and 90th percentile in each category were used for analysis. 7  
Statistical Analysis
Two-tailed paired t-tests were used to compare ocular blood volume, velocity, and total flow between baseline and gas perturbation conditions, with P < 0.05 regarded as significant. The sample size of 14 was chosen for a power of 80% andα = 0.05, while providing the capability for detection of a 12% difference in blood flow. 
Results
Hyperoxia and Hypercapnia
Hyperoxia increased end-tidal Po 2 from 103 ± 5 (mean ± SD) to 562 ± 80 mm Hg (P < 0.05); hypercapnia increased end-tidal Pco 2 from 32 ± 2 to 39 ± 4 mm Hg (P < 0.05). Hyperoxia reduced heart rate from 84 ± 9 to 78 ± 7 beats/min (P < 0.05) at constant arterial blood pressure, while hypercapnia increased systolic blood pressure from 112 ± 8 to 115 ± 8 mm Hg (P < 0.05) at constant heart rate and diastolic pressure. 
Pixel Counts from HRF images
Group mean pixel counts did not differ between images taken from the superior and inferior peripapillary retina (Tables 1 2 3) . Pixel counts also did not differ between baseline images and those taken during hyperoxia or hypercapnia (Tables 1 2 3) . The overall mean pixel count averaged 1156 pixels/image, a quantity 11.5 times larger than the default 10 pixel × 10 pixel box. 
Baseline Blood Flow: Superior versus Inferior Temporal Peripapillary Retina
When baseline blood flow before the imposition of hyperoxia was compared between the superior and inferior temporal regions of the retina, mean volume, velocity, and flow were significantly greater in the inferior area (Table 1) . A similar, nonsignificant tendency for greater inferior mean volume, velocity, and flow also was present in baseline measurements before the imposition of hypercapnia, and the average baseline volume and flow from the two experiments also was greater inferiorly (Table 1) . Inferior and superior portions of the temporal peripapillary retina did not differ in the percentage of zero-flow pixels (Table 1)
The two baseline readings, when compared over the same anatomic retinal regions, showed similar volume, velocity, and flow recordings except in regard to superior temporal blood flow at the 90th percentile pixel. This flow value was higher in the prehyperoxia recording (751 ± 34; range, 499–906 arbitrary units) than in the prehypercapnia reading (693 ± 34; range, 499–930 arbitrary units; P < 0.05). 
Response to Hyperoxia and Hypercapnia: Superior Temporal Peripapillary Retina
In the superior temporal peripapillary retina, hyperoxia failed to change mean blood flow (Table 2) . Hyperoxia also failed to change the percentage of zero flow pixels, or the volume, velocity, or flow in either the 25th, 50th, 75th, or 90th percentile pixel (Table 2) . In contrast, hypercapnia significantly increased mean blood volume, velocity, and flow; decreased the percentage of zero flow pixels; and increased blood volume, velocity, and flow within pixels at the 25th, 50th, 75, and 90th percentiles of each of these variables (Table 2)
Response to Hyperoxia and Hypercapnia: Inferior Temporal Peripapillary Retina
In contrast to results found in the superior retina, in the inferior temporal peripapillary retina, hyperoxia significantly reduced mean blood flow (Table 3) . Although the percentage of zero-flow pixels was unchanged by hyperoxia, mean blood volume and blood volume within pixels at the 25th, 50th, 75th, and 90th percentiles of this variable was reduced (Table 3) . In addition, mean velocity was reduced within the 90th percentile pixel (Table 3) . Blood flow was reduced during hyperoxia in the 75th and 90th percentile pixels (Table 3) . Hypercapnia, however, failed to change any measured aspect of hemodynamics in the inferior temporal quadrant. During CO2 elevation, mean volume, velocity, and flow were unaffected, the percentage of zero-flow pixels was unchanged, and at each percentile of the cSLDF histogram, volume, velocity, and flow were unaltered (Table 3)
Discussion
Higher baseline perfusion in the inferior temporal compared with the superior temporal retina may arise from several possibilities. There is evidence that the normal inferior temporal artery and vein are larger than the analogous superior vessels. 2 Past authors have speculated that these vessels are increased in diameter in the inferior retina in part because the fovea is located slightly inferior to a horizontal midline and in part because the neuroretinal rim is broader inferiorly than superiorly. 2 Our findings suggest in addition that the inferior temporal retina receives a slightly greater capillary perfusion. It is unknown if greater basal perfusion is associated with increased density of ganglion cells, of cells of the intermediate cell layer, or is instead linked to other factors. In other regions of the brain, although differences in metabolic activity are directly tied to differences in oxygen consumption, these differences are only roughly related to differences in blood flow. 8  
A number of previous studies have used hyperoxia and hypercapnia as stimuli for vasoconstriction and vasodilation. Hyperoxia reduces total cerebral blood flow, whereas hypercapnia increases bulk cerebral perfusion, with these effects mediated locally via changes in arteriolar diameter and unrelated (as again seen in this study) to any changes in systemic arterial blood pressure. However, changes in both Po 2 and Pco 2 give rise to substantial cerebral inter-regional variation in the constrictor or dilator response. 9 This regional variation exists also within the retina, with our results showing the most anatomically localized inter-regional difference yet described in cerebral circulatory responsiveness to vasoactive stimuli. 
The mechanisms that underlie regional vasoresponsiveness within the retina remain ill-defined. In the brain as a whole, it is clear that the visual cortex, for example, maintains a relatively high blood flow and high oxygen extraction in comparison to the sensorimotor cortex, 8 but the factors regulating this difference are not known. Cerebral capillary perfusion appears to be controlled at least in part by neuronally derived nitric oxide: inhibition of neuronal nitric oxide synthase blocks the cerebral capillary perfusion increase provoked by hypoxia. 10 However, this generalization does not explain why various tissues (or regions within a relatively homogeneous tissue) may respond differently to vasoactive stimuli. There is evidence, however, that chronically increased or decreased perfusion of regions within a single organ leads to subsequent alterations in vasoreactivity, due to changes in both neuronal and endothelially mediated vascular regulatory processes. 11  
The significance of intraretinal differences in vasodilatory and vasoconstrictor responsiveness also is as yet undefined. There are several possibilities, however, by which these differences might be linked to susceptibility to disease. Reduced vasodilator reserve, as seen in the temporal inferior retina, is associated in other organs with diminished capacity to withstand reductions in perfusion pressure or arterial oxygen content or increases in tissue metabolic demands. 12 For the retina, reduced ocular perfusion pressure, as induced by either elevated IOP or reduced arterial pressure, could create risk for ischemic damage. 13 Although most authors presume that the short posterior ciliary arterial supply of the laminar and prelaminar optic nerve head is of primary importance for the development of ischemia-induced damage in glaucoma, it is indeed in the inferior retina that at least indirect evidence for ischemia is most pronounced in glaucomatous ocular disease. 2  
Although the loss or absence of vasodilator reserve may exacerbate the risk of ischemic damage to tissue, an inability to generate autoregulatory vasoconstrictor responses also may expose cells to potential damage. In diabetes mellitus, a number of primary nonvascular mechanisms, ranging from the induction of angiogenic growth factors to the actions of advanced glycation end products, may underlie development of retinopathy. 14 However, the microvascular complications of chronic hyperglycemia do include impaired vasoconstriction in response to endogenous endothelin-1, neuropeptide Y, and to nonspecific stimuli such as cold exposure. 15 Loss of normal vascular smooth muscle contractile responses could expose tissue to hyperperfusion and subsequent microvascular damage. 15 These cellular level changes may account for the loss of overall retinal vasoconstrictor responsiveness to hyperoxia that proceeds in proportion to progression of diabetes. 16 The relative lack of normal vasoconstrictor responsiveness in the superior temporal retina could explain why that region is more susceptible to development of microaneurysms and acellular capillaries in diabetes 3 and why dilation of the retinal veins, which also occurs in proportion to diabetes severity, is most prominent superiorly. 4  
In summary, variation in vasoreactivity within the healthy retina may help explain differences in regional susceptibility to a number of retinal and optic nerve head diseases. Localized retinal under- or over-perfusion, as induced by a wide range of physiological or pathophysiological perturbations, may occur predictably on the basis of normal tissue autoregulatory capacity. 
 
Figure 1.
 
Sampling window of the reflectivity image (DC) and volume, flow, and velocity perfusion maps showing the single pixel (arrow) analysis of a normal subject in the superior region (left) and the inferior region (right). The square in the left panel is the conventional default measurement box (10 × 10 pixels).
Figure 1.
 
Sampling window of the reflectivity image (DC) and volume, flow, and velocity perfusion maps showing the single pixel (arrow) analysis of a normal subject in the superior region (left) and the inferior region (right). The square in the left panel is the conventional default measurement box (10 × 10 pixels).
Table 1.
 
Baseline Blood Flow in the Superior and Inferior Temporal Peripapillary Retina
Table 1.
 
Baseline Blood Flow in the Superior and Inferior Temporal Peripapillary Retina
Superior Inferior
Baseline before hyperoxia
Mean pixel count 1052 1184
Volume (arbitrary units) 21.7 ± 3.3 23.5 ± 4.1*
Velocity (arbitrary units) 1.21 ± 0.17 1.32 ± 0.25*
Mean flow (arbitrary units) 350 ± 55 386 ± 83*
Baseline before hypercapnia
Mean pixel count 1151 1233
Volume (arbitrary units) 21.3 ± 3.6 22.8 ± 3.6
Velocity (arbitrary units) 1.17 ± 0.24 1.23 ± 0.26
Mean flow (arbitrary units) 330 ± 69 361 ± 85
Mean of two baselines
Mean pixel count 1102 1209
Volume (arbitrary units) 21.5 ± 2.9 23.1 ± 3.2*
Velocity (arbitrary units) 1.19 ± 0.18 1.28 ± 0.21
Mean flow (arbitrary units) 340 ± 57 374 ± 69*
Zero-flow pixels (% of total pixels) 10.1 ± 3.2 11.3 ± 4.1
Table 2.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Superior Temporal Peripapillary Retina
Table 2.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Superior Temporal Peripapillary Retina
Aspect of histogram Baseline Hyperoxia Baseline Hypercapnia
Mean pixel count 1052 1122 1151 1147
Zero-flow pixels (% of total pixels) 9.9 ± 4.0 10.5 ± 3.1 10.4 ± 4.0 8.9 ± 3.7*
Mean flow (arbitrary units) 350 ± 55 361 ± 132 330 ± 69 400 ± 108*
Flow at specific percentiles (arbitrary units)
25th 118 ± 32 114 ± 45 106 ± 35 136 ± 54*
50th 266 ± 46 268 ± 86 255 ± 55 294 ± 80*
75th 471 ± 76 477 ± 72 444 ± 88 523 ± 126*
90th 751 ± 158 775 ± 323 693 ± 128 864 ± 242*
Mean volume (arbitrary units) 21.7 ± 3.3 20.5 ± 3.5 21.3 ± 3.6 24.4 ± 5.1*
Volume at specific percentiles (arbitrary units)
25th 12.1 ± 1.8 11.3 ± 2.2 11.5 ± 2.1 12.9 ± 2.9*
50th 18.5 ± 2.8 16.9 ± 3.4 17.5 ± 3.1 20.0 ± 4.8*
75th 27.9 ± 4.4 26.0 ± 4.6 27.4 ± 4.6 31.2 ± 6.6*
90th 40.0 ± 7.0 37.7 ± 6.8 39.0 ± 6.9 45.4 ± 10.1*
Mean velocity (arbitrary units) 1.21 ± 0.17 1.23 ± 0.39 1.17 ± 0.24 1.35 ± 0.33*
Velocity at specific percentiles (arbitrary units)
25th 0.44 ± 0.12 0.43 ± 0.16 0.40 ± 0.13 0.50 ± 0.20*
50th 0.93 ± 0.18 0.94 ± 0.32 0.90 ± 0.24 1.03 ± 0.32*
75th 1.67 ± 0.25 1.67 ± 0.53 1.60 ± 0.31 1.83 ± 0.40*
90th 2.56 ± 0.40 2.63 ± 0.98 2.44 ± 0.47 2.87 ± 0.71*
Table 3.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Inferior Temporal Peripapillary Retina
Table 3.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Inferior Temporal Peripapillary Retina
Aspect of histogram Baseline Hyperoxia Baseline Hypercapnia
Mean pixel count 1184 1174 1233 1186
Zero-flow pixels (% of total pixels) 10.3 ± 4.0 10.8 ± 3.7 12.2 ± 5.9 11.4 ± 5.3
Mean flow (arbitrary units) 386 ± 83 332 ± 40* 361 ± 85 391 ± 109
Flow at specific percentiles (arbitrary units)
25th 127 ± 49 108 ± 31 105 ± 52 117 ± 57
50th 288 ± 66 254 ± 38 258 ± 63 282 ± 81
75th 509 ± 109 447 ± 53* 474 ± 97 518 ± 132
90th 824 ± 184 702 ± 92* 789 ± 190 880 ± 273
Mean volume (arbitrary units) 23.5 ± 4.1 20.4 ± 2.8* 22.8 ± 3.6 24.5 ± 5.3
Volume at specific percentiles (arbitrary units)
25th 12.8 ± 2.4 11.2 ± 1.7* 11.9 ± 2.0 12.7 ± 2.5
50th 19.8 ± 3.6 17.4 ± 2.0* 18.8 ± 2.7 20.1 ± 3.9
75th 30.0 ± 5.5 25.9 ± 3.4* 29.1 ± 5.0 31.6 ± 7.1
90th 43.2 ± 9.1 37.1 ± 6.7* 43.1 ± 8.2 46.6 ± 11.8
Mean velocity (arbitrary units) 1.31 ± 0.25 1.18 ± 0.17 1.23 ± 0.26 1.36 ± 0.35
Velocity at specific percentiles (arbitrary units)
25th 0.47 ± 0.18 0.41 ± 0.13 0.39 ± 0.19 0.44 ± 0.22
50th 1.05 ± 0.23 0.94 ± 0.16 0.94 ± 0.22 1.03 ± 0.29
75th 1.78 ± 0.33 1.62 ± 0.22 1.67 ± 0.31 1.85 ± 0.44
90th 2.78 ± 0.55 2.51 ± 0.40* 2.66 ± 0.55 3.00 ± 0.80
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Figure 1.
 
Sampling window of the reflectivity image (DC) and volume, flow, and velocity perfusion maps showing the single pixel (arrow) analysis of a normal subject in the superior region (left) and the inferior region (right). The square in the left panel is the conventional default measurement box (10 × 10 pixels).
Figure 1.
 
Sampling window of the reflectivity image (DC) and volume, flow, and velocity perfusion maps showing the single pixel (arrow) analysis of a normal subject in the superior region (left) and the inferior region (right). The square in the left panel is the conventional default measurement box (10 × 10 pixels).
Table 1.
 
Baseline Blood Flow in the Superior and Inferior Temporal Peripapillary Retina
Table 1.
 
Baseline Blood Flow in the Superior and Inferior Temporal Peripapillary Retina
Superior Inferior
Baseline before hyperoxia
Mean pixel count 1052 1184
Volume (arbitrary units) 21.7 ± 3.3 23.5 ± 4.1*
Velocity (arbitrary units) 1.21 ± 0.17 1.32 ± 0.25*
Mean flow (arbitrary units) 350 ± 55 386 ± 83*
Baseline before hypercapnia
Mean pixel count 1151 1233
Volume (arbitrary units) 21.3 ± 3.6 22.8 ± 3.6
Velocity (arbitrary units) 1.17 ± 0.24 1.23 ± 0.26
Mean flow (arbitrary units) 330 ± 69 361 ± 85
Mean of two baselines
Mean pixel count 1102 1209
Volume (arbitrary units) 21.5 ± 2.9 23.1 ± 3.2*
Velocity (arbitrary units) 1.19 ± 0.18 1.28 ± 0.21
Mean flow (arbitrary units) 340 ± 57 374 ± 69*
Zero-flow pixels (% of total pixels) 10.1 ± 3.2 11.3 ± 4.1
Table 2.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Superior Temporal Peripapillary Retina
Table 2.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Superior Temporal Peripapillary Retina
Aspect of histogram Baseline Hyperoxia Baseline Hypercapnia
Mean pixel count 1052 1122 1151 1147
Zero-flow pixels (% of total pixels) 9.9 ± 4.0 10.5 ± 3.1 10.4 ± 4.0 8.9 ± 3.7*
Mean flow (arbitrary units) 350 ± 55 361 ± 132 330 ± 69 400 ± 108*
Flow at specific percentiles (arbitrary units)
25th 118 ± 32 114 ± 45 106 ± 35 136 ± 54*
50th 266 ± 46 268 ± 86 255 ± 55 294 ± 80*
75th 471 ± 76 477 ± 72 444 ± 88 523 ± 126*
90th 751 ± 158 775 ± 323 693 ± 128 864 ± 242*
Mean volume (arbitrary units) 21.7 ± 3.3 20.5 ± 3.5 21.3 ± 3.6 24.4 ± 5.1*
Volume at specific percentiles (arbitrary units)
25th 12.1 ± 1.8 11.3 ± 2.2 11.5 ± 2.1 12.9 ± 2.9*
50th 18.5 ± 2.8 16.9 ± 3.4 17.5 ± 3.1 20.0 ± 4.8*
75th 27.9 ± 4.4 26.0 ± 4.6 27.4 ± 4.6 31.2 ± 6.6*
90th 40.0 ± 7.0 37.7 ± 6.8 39.0 ± 6.9 45.4 ± 10.1*
Mean velocity (arbitrary units) 1.21 ± 0.17 1.23 ± 0.39 1.17 ± 0.24 1.35 ± 0.33*
Velocity at specific percentiles (arbitrary units)
25th 0.44 ± 0.12 0.43 ± 0.16 0.40 ± 0.13 0.50 ± 0.20*
50th 0.93 ± 0.18 0.94 ± 0.32 0.90 ± 0.24 1.03 ± 0.32*
75th 1.67 ± 0.25 1.67 ± 0.53 1.60 ± 0.31 1.83 ± 0.40*
90th 2.56 ± 0.40 2.63 ± 0.98 2.44 ± 0.47 2.87 ± 0.71*
Table 3.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Inferior Temporal Peripapillary Retina
Table 3.
 
Effects of Hyperoxia and Hypercapnia on Blood Volume, Velocity, and Flow in Inferior Temporal Peripapillary Retina
Aspect of histogram Baseline Hyperoxia Baseline Hypercapnia
Mean pixel count 1184 1174 1233 1186
Zero-flow pixels (% of total pixels) 10.3 ± 4.0 10.8 ± 3.7 12.2 ± 5.9 11.4 ± 5.3
Mean flow (arbitrary units) 386 ± 83 332 ± 40* 361 ± 85 391 ± 109
Flow at specific percentiles (arbitrary units)
25th 127 ± 49 108 ± 31 105 ± 52 117 ± 57
50th 288 ± 66 254 ± 38 258 ± 63 282 ± 81
75th 509 ± 109 447 ± 53* 474 ± 97 518 ± 132
90th 824 ± 184 702 ± 92* 789 ± 190 880 ± 273
Mean volume (arbitrary units) 23.5 ± 4.1 20.4 ± 2.8* 22.8 ± 3.6 24.5 ± 5.3
Volume at specific percentiles (arbitrary units)
25th 12.8 ± 2.4 11.2 ± 1.7* 11.9 ± 2.0 12.7 ± 2.5
50th 19.8 ± 3.6 17.4 ± 2.0* 18.8 ± 2.7 20.1 ± 3.9
75th 30.0 ± 5.5 25.9 ± 3.4* 29.1 ± 5.0 31.6 ± 7.1
90th 43.2 ± 9.1 37.1 ± 6.7* 43.1 ± 8.2 46.6 ± 11.8
Mean velocity (arbitrary units) 1.31 ± 0.25 1.18 ± 0.17 1.23 ± 0.26 1.36 ± 0.35
Velocity at specific percentiles (arbitrary units)
25th 0.47 ± 0.18 0.41 ± 0.13 0.39 ± 0.19 0.44 ± 0.22
50th 1.05 ± 0.23 0.94 ± 0.16 0.94 ± 0.22 1.03 ± 0.29
75th 1.78 ± 0.33 1.62 ± 0.22 1.67 ± 0.31 1.85 ± 0.44
90th 2.78 ± 0.55 2.51 ± 0.40* 2.66 ± 0.55 3.00 ± 0.80
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