March 2014
Volume 55, Issue 3
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Retina  |   March 2014
Associations of Retinal Oximetry in Healthy Young Adults
Author Affiliations & Notes
  • Ryan Eyn Kidd Man
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
  • Muhammad Bayu Sasongko
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
    Department of Ophthalmology, Faculty of Medicine, Gadjah Mada University, Yogyakarta, Indonesia
  • Ryo Kawasaki
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
  • Jonathan Edward Noonan
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
  • Tiffany Ching Shen Lo
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
  • Chi D. Luu
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
  • Ecosse Luc Lamoureux
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
    Singapore Eye Research Institute, National University of Singapore, Singapore
    Duke-National University of Singapore Graduate Medical School, Singapore
  • Jie Jin Wang
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
    Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, New South Wales, Australia
  • Correspondence: Jie Jin Wang, Centre for Vision Research, Department of Ophthalmology and Westmead Millenium Institute, University of Sydney C24, Westmead Hospital, Hawkesbury Road, Westmead, NSW 2145, Australia; jiejin.wang@sydney.edu.au
Investigative Ophthalmology & Visual Science March 2014, Vol.55, 1763-1769. doi:10.1167/iovs.13-13320
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      Ryan Eyn Kidd Man, Muhammad Bayu Sasongko, Ryo Kawasaki, Jonathan Edward Noonan, Tiffany Ching Shen Lo, Chi D. Luu, Ecosse Luc Lamoureux, Jie Jin Wang; Associations of Retinal Oximetry in Healthy Young Adults. Invest. Ophthalmol. Vis. Sci. 2014;55(3):1763-1769. doi: 10.1167/iovs.13-13320.

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

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Abstract

Purpose.: To assess factors associated with retinal oximetry values in healthy young adults.

Methods.: Retinal oximetry readings were assessed using the oximetry module of the Vesselmap System in 100 eyes of 50 healthy subjects aged 18 to 58 years. Generalized estimating equation models were used to estimate the associations of candidate variables (age, sex, retinal capillary flow, HbA1c, triglyceride, total cholesterol, ocular perfusion pressure, and finger oxygen saturation [SO2]) with retinal oximetry measures (arteriolar SO2, venular SO2, and the arterio-venous [A-V] difference).

Results.: Of the candidate factors assessed, only age and finger SO2 were found to be significantly associated with one or more measures of retinal oximetry in unadjusted analyses. After adjusting for age, sex, and significant factors from unadjusted analyses, age and finger SO2 values remained significant. Age was associated with retinal arteriolar and venular SO2 values (per year increase in age, β = 0.31, 95% confidence interval [CI]: 0.15–0.48 and β = 0.26, 95% CI: 0.08–0.43, respectively), but not associated with the A-V difference. Finger SO2 values were associated with retinal arteriolar SO2 and A-V difference (per percentage change in finger SO2, β = 1.34, 95% CI: 0.40–2.28 and β = 0.74, 95% CI: 0.36–1.11, respectively), but not with venular SO2.

Conclusions.: In healthy young adults, age was positively associated with the retinal arteriolar and venular SO2 values, whereas finger SO2 was positively correlated with greater arteriolar SO2 and A-V difference. Our findings serve as a basis for future studies assessing retinal oximetry values in young adults under normal and pathophysiological conditions.

Introduction
The recent advent of modern spectrophotometric retinal oximetry techniques has gained increasing interest. It is based on the fact that oxygenated and deoxygenated hemoglobin have different light absorption spectra, and by using these differences in absorption wavelengths, the oxygen saturation (SO2) in retinal blood vessels can be estimated noninvasively. 1,2 Using these oximetry techniques, researchers have demonstrated changes in retinal SO2, with flicker light stimulation, 3 changes in illumination, 4 diabetes, 5,6 and retinal vein occlusions. 7,8 However, little is known about the variables that might influence oximetry values under normal physiological conditions. 
Previous work has evaluated the effects of age, sex, and cardiovascular parameters (e.g., finger SO2 values and ocular perfusion pressure [OPP]) on retinal oximetry measures (i.e., arteriolar, venular, and the arterio-venous [A-V] difference in SO2). 9 However, the associations of hemodynamic parameters (i.e., retinal blood flow) and serum hemoglobin and lipid measures (e.g., glycated hemoglobin [HbA1c], total cholesterol, and triglyceride levels) with these retinal oximetry values have not been investigated. Given that these factors have been implicated in the pathogenesis of retinal metabolic disorders, such as diabetic retinopathy, 10,11 it is important to understand the correlation between these hemodynamic and serum parameters with retinal oximetry measures in healthy adults to enable an appropriate assessment of retinal vessel SO2 and better utilization of retinal oximeters in research and clinical practice. 
In this study, we aimed to assess associations of age, sex, retinal capillary flow (RCF), HbA1c, triglyceride, total cholesterol, OPP, and finger pulse SO2 values with retinal arteriolar, venular, and the A-V difference in SO2 measured in a sample of healthy Caucasian adults, using the oximetry module of the Vesselmap System (Imedos UG, Jena, Germany). Our results will serve to describe a more complete normative profile for retinal oximetry data in the Caucasian population. 
Methods
Study Population
Fifty healthy Caucasian individuals aged 18 years or older without self-reported medical history of any systemic diseases that might affect the retinal microvasculature (i.e., diabetes and hypertension) were recruited. This was further confirmed with information obtained from blood pressure measurements (<140/80 mm Hg) 12 and biochemistry analysis (e.g., HbA1c [<6.5%] 13 and random glucose [<11.1 mM]). 14 All participants had a best-corrected logarithm of minimum angle of resolution visual acuity of 0.00 (equivalent to 6/6 on the Snellen chart) or better. Subjects were excluded if they had IOP higher than 21 mm Hg, cataracts or other media opacities, or any history or signs of retinal or optic nerve degeneration/disease. All subjects were also advised to refrain from consuming caffeinated products and alcohol for at least 12 hours before the study. The study was approved by the human ethics committee of the Royal Victorian Eye and Ear Hospital (#11/1034H) and abided by the tenets of the Declaration of Helsinki. 
Blood Biochemistry Measures
Nonfasting blood samples were collected for analysis of blood glucose, HbA1c, and lipids (total, high-density lipoprotein cholesterol, LDL-cholesterol, and triglycerides). All blood analyses were performed at Melbourne Pathology, Melbourne, Australia, with individual results electronically delivered through a password-protected program. The laboratory is accredited to the International Standard ISO15189 (Medical Laboratories) and is certified by the National Association of Testing Authorities. The reference ranges for healthy subjects of the serum markers analyzed in our study were 4.4% to 5.6% for HbA1c, lower than 1.5 mM for triglycerides, and 3.5 to 5.5 mM for total cholesterol. 
Image Capture for Retinal Capillary Flow
Retinal capillary flow was captured using the Heidelberg Retinal (HRF; Heidelberg Engineering, Inc., Heidelberg, Germany). Briefly, the examination was performed in a sitting position at room temperature with diffuse natural light on undilated pupils. An optic disc–centered scan was obtained, together with the regions within 1.5 disc diameters to either side of the optic disc margin. A total area of 2.56 × 0.64 mm (horizontal and vertical orientation, respectively) was scanned within 2 seconds at a resolution of 256 points × 64 lines × 128 times with the default 780-nm wavelength laser head installed in the HRF camera. During the data acquisition, the participant was asked to fixate on an adjustable mounted artificial light spot. The scans were taken from both eyes of each person. 
Analysis of Capillary Flow
Image analysis was performed using the automatic full-field perfusion image analyzer (AFFPIA) software (version 3.3; University of Erlangen, Germany). Briefly, AFFPIA calculates the Doppler frequency shift of 780-nm laser light from the HRF arising from moving blood cells within each pixel of the entire image and estimates the overall flow in the form of arbitrary units. 15 For a valid estimation of RCF, the software adjusts brightness to mask under- or overexposed pixels and also eliminates noise from artificial movement (saccades), avoids measuring extremely wide retinal vessels and the optic nerve head, and accounts for the heart phases (systole and diastole) by averaging the differences between the two phases. Figure 1 shows an example of an image processed using the AFFPIA software. For analytical purposes, the flow readings from the temporal and nasal regions adjacent to the optic disc were averaged. 
Figure 1
 
Image showing an optic nerve–centered scan from the Heidelberg Retinal Flowmeter. The orange regions adjacent to the optic disc (gray circular area) are the areas where capillary flow is assessed.
Figure 1
 
Image showing an optic nerve–centered scan from the Heidelberg Retinal Flowmeter. The orange regions adjacent to the optic disc (gray circular area) are the areas where capillary flow is assessed.
Dilated Slit Lamp Examination and Imaging for SO2 Measurements
Subjects' pupils were dilated using 1% tropicamide. Slit lamp examination was performed to check for signs of cataracts or other media opacities. Optic disc–centered images (30-degree field) of the right eye were then taken using a fundus camera (FF450, Carl Zeiss, Jena, Germany). Care was taken to ensure that the images were sufficiently illuminated (as indicated by the “illumination indicator” algorithm provided in the Oximetry module of the Vesselmap System (Imedos UG), the magnification and flash settings were not changed between images, and that the background illumination remained constant. 
Assessment of Retinal Vessel SO2 and A-V Difference
Retinal vessel oxygenation measurements in both retinal arteries and veins were estimated using the Oximetry module of the Vesselmap System. In brief, two monochromatic fundus images were obtained using a double-band pass filter (light transmission at 548 ± 10 nm and 610 ± 10 nm) inserted in the illumination path of a fundus camera FF450 (Carl Zeiss). Only one observer (REKM) was assigned to take the images. The ratio of the optical densities at 610 nm to that at the isosbestic wavelength 548 nm (known as the optical density ratio) is proportional to the vessel hemoglobin SO2 16 after compensation for vessel diameter and fundus pigmentation, as retinal oximetry values were inversely associated with vessel diameter and fundus pigmentation. 17  
For each image, a peripapillary annulus (specifically designed by Imedos UG to be adjustable to account for different optic disc sizes as per our request) was used to mark an area in the image for analysis (Fig. 2). Within this area (inner radius of 1.0 and outer radius of 1.5 disc diameters), the O2 saturation was measured for all arterioles and venules. For each vessel, approximately 10 to 20 SO2 values, depending on the length of the vessel within the measurement area, were calculated and averaged by the algorithm. Any SO2 values that were more than 20% over the mean SO2 value of that vessel were excluded to eliminate the confounding effects of specular reflection. 17  
Figure 2
 
A fundus photograph showing the peripapillary annulus where oxygen saturation readings were taken. A false color map showing saturation values has been superimposed on the image. Saturation values are color coded according to the scale bar.
Figure 2
 
A fundus photograph showing the peripapillary annulus where oxygen saturation readings were taken. A false color map showing saturation values has been superimposed on the image. Saturation values are color coded according to the scale bar.
Typically, about 20 measurements consisting of approximately 8 to 10 arterioles and 8 to 10 venules that were above 50 μm in diameter were averaged to give the mean arteriolar and venular SO2 for each eye. This vessel diameter threshold was chosen as it was observed that the algorithm of the Vesselmap System had difficulty tracing and measuring the O2 saturation of vessels smaller than 50 μm in diameter without repeated efforts by the observer to mark the edges of the vessel walls accurately. The A-V difference was then calculated as the difference between the arteriolar and venular SO2 values. A reliability and reproducibility study we did on the same sample using the above technique produced extremely good intraobserver reliability (i.e., the ability to obtain consistent oximetry values when analyzing the same image twice by the same observer), intraobserver reproducibility (i.e., the ability to obtain consistent values from images of the same subject taken at different times by the same observer), and interobserver reproducibility (i.e., the ability to obtain consistent oximetry values when analysis of the same image was undertaken by different observers) in all three measures of retinal oximetry. 18  
Assessment of Other Key Covariables
Standardized questionnaires were used to assess basic demographic details (age, sex), history of ocular and systemic conditions, and medication use. Systolic blood pressure and diastolic blood pressure measurements were taken using the Omron Automatic Blood Pressure Monitor (Model IAIB; Omron Healthcare Co., Kyoto, Japan). IOP was assessed using Goldmann applanation tonometry. OPP was then derived from the formula ⅔ (mean arterial pressure) – IOP, where mean arterial pressure = ⅔ diastolic blood pressure + ⅓ systolic blood pressure. Finger SO2 values (measure of finger arteriolar SO2) were obtained using the Rossmax Pulse Oximeter, Model SB100. Key covariables were age, sex, finger pulse SO2, and OPP. Two-field fundus images of the right eye were also taken using the Canon CR-6–45NM camera (Canon, Inc., Tokyo, Japan). The images were graded at the Centre for Eye Research Australia, and eyes with any degenerative changes other than tessellated fundi or slight crescents at the optic disc were excluded from the study. 
Statistical Analysis
Analyses were performed using Intercooled STATA version 12.1 for Windows (Stata Corp., College Station, TX). First, we tested for differences and correlations in the outcome variables (arteriolar SO2, venular SO2, and the A-V difference) between the left and right eyes using the Wilcoxon signed-rank test/paired t-test where appropriate, as well as Pearson's correlation coefficient. Eye-specific data (arteriolar, venular, and the A-V difference in SO2, RCF, OPP) from both eyes of each subject and person-specific data (age, sex, HbA1c, triglyceride levels, total cholesterol levels) were then used in analyses. Beta coefficients (β), derived from generalized estimating equation (GEE) models with exchangeable correlation matrix, were used to estimate the unadjusted associations between the candidate determinants (age, sex, RCF, HbA1c levels, triglyceride levels, total cholesterol levels, OPP, and finger SO2) with the outcome variables while controlling for the correlations between two eyes. We undertook the analyses using the inverse Gaussian function, which was the closest fit to the highly skewed data (arteriolar and venular SO2). 19 Multivariable-adjusted models, including age, sex, and significant variables in unadjusted analyses, were then used to assess the associations between candidate variables and the SO2 values of arterioles, venules, and the A-V difference. 
Results
Data from 100 eyes of 50 subjects were included in the analysis. The median age (interquartile range [IQR]) was 26 (23–31) years and 28 (56%) were female. The median (IQR) for arteriolar and venular SO2 of all 100 eyes were 96.02% (90.62%–98.57%) and 61.99% (56.68%–64.08%), respectively. The mean (SD) for the A-V difference was 33.83% (3.36%). Table 1 summarizes the demographic and clinical parameters of the sample. 
Table 1
 
Demographic and Clinical Parameters of Participants (n = 100 Eyes)
Table 1
 
Demographic and Clinical Parameters of Participants (n = 100 Eyes)
Parameters Mean (SD) or Median (IQR) Range of Values
Age, y 26 (23–31) 18–58
Female, % 56
Arteriolar SO2, % 96.02 (90.62–98.57) 77.03–100.82
Venular SO2, % 61.99 (56.68–64.08) 41.15–71.65
A-V difference, % 33.83 (3.36) 24.13–42.47
Blood flow, arbitrary units 247.66 (39.50) 126.22–345.92
HbA1c,* % 5.24 (0.31) 4.50–5.80
Triglycerides, mM 1.00 (0.80–1.30) 0.40–3.30
Total cholesterol, mM 4.94 (1.02) 2.60–8.00
Finger SO2, % 98 (97–99) 92–99
OPP, mm Hg† 45.48 (6.30) 32.00–60.33
Comparison of Oximetry Measures Between Eyes
All oximetry readings were not significantly different, and were highly correlated, between the left and right eyes. The median (IQR) of the arteriolar SO2 values was 95.94% (91.53%–98.49%) for the right eye, and 96.54% (89.55%–98.91%) for the left eye (correlation coefficient: 0.83, P < 0.001). The median (IQR) of the venular SO2 values was 62.35% (57.65%–64.17%) for the right eye, and 62.28% (56.60%–64.03%) for the left eye (correlation coefficient: 0.77, P < 0.001). Finally, the mean (SD) of the A-V difference was 33.79% (3.37%) for the right eye, and 33.57% (3.45%) for the left eye (correlation coefficient: 0.78, P < 0.001) (Table 2). 
Table 2
 
Comparison and Correlation of Retinal Arteriolar, Venular, and A-V SO2 Values Between the Right and Left Eyes (n = 50 Subjects)
Table 2
 
Comparison and Correlation of Retinal Arteriolar, Venular, and A-V SO2 Values Between the Right and Left Eyes (n = 50 Subjects)
Outcome Parameters Median (IQR) or Mean (SD) P Value Correlation Coefficient
Arteriolar SO2
 Right eye, % 95.94 (91.53–98.49) <0.001 0.83
 Left eye, % 96.54 (89.55–98.91)
Venular SO2
 Right eye, % 62.35 (57.65–64.17) <0.001 0.77
 Left eye, % 62.28 (56.60–64.03)
A-V Difference
 Right eye, % 33.79 (3.37) <0.001 0.78
 Left eye, % 33.57 (3.45)
Associations Between Age and Gender With Retinal Oximetry Measures
Unadjusted analyses revealed that increasing age was associated with greater arteriolar and venular SO2 (per year increase in age, β = 0.33, P < 0.001, and β = 0.25, P = 0.003, for arteriolar and venular SO2, respectively, Table 3), but was not associated with the A-V difference. Scatter plots of age versus arteriolar and venular SO2 confirmed a linear pattern of the associations, although most study subjects were aged between 18 and 40 years (Figures 3 and 4). These associations persisted after additional adjustment of other cofactors (per year increase in age, β = 0.31, P < 0.001; and β = 0.26, P = 0.002, for arteriolar and venular SO2 respectively, Table 4). 
Figure 3
 
A scatter plot showing the distribution of oxygen saturation for retinal arterioles with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 3
 
A scatter plot showing the distribution of oxygen saturation for retinal arterioles with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 4
 
A scatter plot showing the distribution of oxygen saturation for retinal venules with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 4
 
A scatter plot showing the distribution of oxygen saturation for retinal venules with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Table 3
 
Unadjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Table 3
 
Unadjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Study Factors Arteriolar SO2 Venular SO2 A-V Difference
β (95% CI) β (95% CI) β (95% CI)
Age, y 0.33 (0.17–0.48)* 0.25 (0.09–0.42)* 0.07 (−0.01–0.16)
Female 2.11 (−1.10–5.33) 1.00 (−2.15–4.15) 1.11 (−0.68–2.90)
Capillary flow, arbitrary units −0.01 (−0.04–0.02) −0.004 (−0.03–0.03) −0.006 (−0.02–0.01)
HbA1c, % 3.10 (−1.47–7.67) 0.67 (−3.82–5.15) 2.51 (−0.50–5.52)
Triglycerides, mM 1.01 (−2.55–4.58) 1.50 (−1.75–4.76) −0.36 (−1.53–0.80)
Total cholesterol, mM 0.60 (−1.03–2.23) 0.03 (−1.69–1.74) 0.61 (−0.30–1.52)
Finger SO2, % 1.42 (0.19–2.66)* 0.66 (−0.56–1.88) 0.80 (0.44–1.17)*
OPP, mm Hg 0.02 (−0.18–0.22) 0.06 (−0.10–0.22) −0.03 (−0.15–0.09)
Table 4
 
Multivariable-Adjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Table 4
 
Multivariable-Adjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Study Factors Arteriolar SO2 Venular SO2 Arterio-venous Difference
β* (95% CI) β† (95% CI) β* (95% CI)
Age, y 0.31 (0.15–0.48)‡ 0.26 (0.08–0.43)‡ 0.06 (−0.007–0.13)
Female 1.07 (−1.43–3.58) 0.67 (−2.39–3.73) 0.63 (−1.05–2.31)
Capillary flow, arbitrary units −0.007 (−0.03–0.02) −0.007 (−0.04–0.02) −0.005 (−0.02–0.08)
HbA1c, % 2.57 (−1.08–6.22) 1.29 (−3.67–6.26) 2.74 (−0.16–5.64)
Triglycerides, mM 0.31 (−2.39–3.01) 0.73 (−2.65–4.12) −0.41 (−1.62–0.80)
Total cholesterol, mM −0.15 (−2.19–1.90) −1.22 (−3.17–0.74) 0.86 (−0.03–1.69)
Finger SO2 (%) 1.34 (0.40–2.28)‡ 0.14 (−0.82–1.11) 0.73 (0.36–1.11)‡
OPP, mm Hg −0.04 (−0.23–0.15) 0.03 (−0.16–0.23) −0.05 (−0.16–0.05)
Associations Between RCF and Serum Markers With Retinal Oximetry Measures
Neither RCF, nor any of the serum markers, were associated with any of the three retinal oximetry measures in unadjusted analyses (Table 3). Additional adjustments for age, sex, and significant factors found in unadjusted analyses confirmed that no associations exist between RCF and serum markers with the SO2 measurements of arterioles, venules, and the A-V difference (Table 4). 
Associations Between Cardiovascular Parameters With Retinal Oximetry Measures
Finger SO2 values were found to be associated with a greater arteriolar SO2 and the A-V difference (per percentage change in finger SO2, β = 1.42, P = 0.02, and β = 0.80, P < 0.001, for arteriolar SO2 and the A-V difference respectively, Table 3), but not with the venular SO2. These associations remained after multivariable adjustments (per percentage change in finger SO2, β = 1.34, P = 0.005 for arteriolar SO2, and β = 0.74, P < 0.001, for the A-V difference, respectively, Table 4). No significant association was found between OPP and arteriolar SO2, venular SO2, and the A-V difference. 
Discussion
In this study, we demonstrated that in healthy young adults, increasing age was significantly associated with increased arteriolar and venular SO2 values but not the A-V difference, whereas increasing finger SO2 values were significantly associated with increased arteriolar SO2 and the A-V difference, but not venular SO2 values. Importantly, we established that there were no associations between retinal capillary flow, OPP, and any of the serum markers (HbA1c, total cholesterol, triglyerides), with the SO2 values of arterioles, venules, and the A-V difference in this sample. 
Only one previous study has evaluated the effect of age on retinal oximetry values. Geirsdottir and colleagues 9 found that increasing age did not affect retinal arteriolar SO2 values, but was associated with decreasing venular SO2 values, as well as an increased A-V difference. The difference in sample population between our sample and that of Geirsdottir's group 9 may be a major factor that could have contributed to the differences in association between age and retinal oximetry values. First, Geirsdottir's group 9 did not exclude subjects with systemic hypertension (albeit they were well controlled), which may have influenced their results due to hypertension-related capillary nonperfusion and sheathing of vessel walls. More importantly, our sample consisted predominantly of younger subjects (90% of subjects < 45 years), whereas Geirsdottir and colleagues' 9 sample had a much larger age range (18–80 years). Therefore, the difference in results may have arisen from the effects of cataract and other media opacities that may have been present in participants of the latter study, as well as the possibility that age affects retinal oximetry differently after the age of 40 years. 
A distinction also should be made between the SO2 assessed from retinal oximeters with the actual SO2 in retinal vessels, especially with regard to age. The actual SO2 may differ from measured SO2 values, with increasing age as a result of influence from several factors, such as age-related lenticular and vascular changes. Hence, caution needs to be taken when extrapolating the results of age-related SO2 changes from our study sample to older subjects (aged > 40 years). Consequently, further investigations into the effects of age on retinal SO2 values in the older population are needed. 
Geirsdottir and colleagues 9 further demonstrated that the OPP was associated with a higher arteriolar SO2 value, with a similar trend seen in venules. They also established that the finger SO2 values were not associated with any of the oximetry values. This was in contrast to our study, where we discovered that OPP was not correlated with any of the SO2 values, whereas the finger SO2 values were strongly associated with the arteriolar SO2 and A-V difference values, but not the venular SO2. Given the tight autoregulation of retinal metabolism, small changes within the range of OPP values should not have influenced O2 metabolism, 20 which is consistent with our results. The positive correlation between finger SO2 values and the retinal arteriolar and A-V difference in SO2 in our study is also plausible, as finger SO2 is essentially a measurement of SO2 in the finger arterioles, and the SO2 value of arteriolar blood before reaching the small vessels (i.e., capillaries) should be consistent across all end organs of the body, barring the presence of local vascular abnormalities. Our results, therefore, suggest a close correlation between local (retinal) SO2 and that of the systemic circulation. The difference in results between our study and the study by Geirsdottir and colleagues 9 could have arisen because of the differences in study sample: subjects with systemic hypertension were included in the study by Geirsdottir and colleagues, 9 whereas they were excluded in our study. The vascular changes inherent to hypertension (such as sheathing of vessel walls, and capillary nonperfusion) might have confounded the SO2 measurements. 
We also found that the RCF was not associated with any of the retinal oximetry values (arteriolar, venular, and the A-V difference in SO2). It has been proposed that blood flow and O2 metabolism are closely related, as demonstrated by Riva and colleagues, 21 who quantified the relationship between O2 tension and retinal arterial and venular blood flow in porcine models. Even though the RCF is not a direct measurement of blood flow in the arterioles and venules, it should still be highly correlated with these two parameters. The nonassociation of RCF with the retinal oximetry values could be due to several possible reasons. First, this could be due to lack of statistical power as evident from the large variation in RCF readings. However, given that the β regression coefficient of the association between RCF and all three retinal oximetry measures are very small (β for all three associations ≤ −0.01), even if these results were statistically significant, it would not be clinically meaningful. Second, it has been proposed that the coupling between blood flow and O2 metabolism is nonlinear (i.e., it takes large changes in blood flow to bring about small changes in O2 metabolism). 22,23 Third, the algorithm in the oximeter analysis software corrects for vessel size when calculating SO2 values, resulting in measurements that are independent of vessel diameter. However, the Hagen-Poiseuille law states that blood flow is directly proportional to the diameter (to the fourth power) of the vessel. 24 By correcting the influence of vessel diameter on retinal SO2 during analysis, the algorithm might have invariably weakened any associations between blood flow and SO2 values. Fourth, there could be possible influence from the choriocapillaries as demonstrated by Strenn et al. 25 However, Strenn and colleagues 25 assessed capillary flow near the macular, where there are very few retinal vessels due to proximity to the foveal avascular zone, which may allow the scanning laser from the HRF to reflect moving red blood cells in the underlying choroidal blood vessels instead. In contrast, we assessed RCF in the areas adjacent to the optic disc, where most retinal capillaries are located. Therefore, light scattering and resultant influence from the choroidal capillaries is likely to be minimal in our study. 
No data are currently available on the relationship between serum markers, such as HbA1c, triglycerides, and total cholesterol levels, and retinal SO2 values. This is important, as these markers are risk factors in retinal metabolic disorders (e.g., increased HbA1c 10 and dyslipidemia 11 in diabetic retinopathy). In our study, we found no associations between these serum markers and the arteriolar, venular, or A-V difference in SO2 values. These results are novel and demonstrate that the retinal oximetry values obtained with this retinal oximeter are not influenced by normal physiological variations in serum markers. 
Strengths of this study include quantitative measures of RCF and one researcher (REKM) performing all fundus photography, as well as all RCF and oximetry imaging measures. Limitations include a small sample size, as well as the relatively young age group of this study sample, which might have limited generalization of our findings to samples of other age ranges. In addition, 20% of our sample population had total cholesterol and triglyceride levels exceeding the “healthy” reference range provided by the laboratory. Consequently, we performed additional analyses between triglyceride and total cholesterol with the three measures of retinal oximetry after excluding subjects who had triglyceride levels and/or total cholesterol levels exceeding these reference ranges (>1.5 mM for triglycerides and >5.5 mM for total cholesterol), and found that the results did not alter (see Table 5). 
Table 5
 
Multivariable-Adjusted Associations Between Triglycerides and Total Cholesterol Levels With Retinal Oximetry Values in Subjects With Normal Triglyceride and Total Cholesterol Levels
Table 5
 
Multivariable-Adjusted Associations Between Triglycerides and Total Cholesterol Levels With Retinal Oximetry Values in Subjects With Normal Triglyceride and Total Cholesterol Levels
Study Factors Arteriolar SO2 Venular SO2 A-V Difference
β* (95% CI) β† (95% CI) β* (95% CI)
Triglycerides, mM 3.08 (−2.09–8.26) 4.05 (−0.91–9.02) 0.02 (−2.73–2.79)
Total cholesterol, mM 1.24 (−0.93–3.41) 0.42 (−2.26–3.10) 0.79 (−1.11–2.69)
In conclusion, our study provides novel data on factors associated with retinal oximetry values under normal physiological conditions in healthy young adults. We have demonstrated that age was positively correlated with retinal arteriolar and venular SO2 values, whereas increased finger SO2 values were strongly associated with greater arteriolar SO2 and the A-V difference in SO2. Our results may inform future studies evaluating the associations of these factors with retinal oximetry values in older age groups, as well as in retinal metabolic dysfunction. 
Acknowledgments
The Centre for Eye Research Australia receives operational infrastructure support from the Victorian government. The authors alone are responsible for the content and writing of the paper. 
Disclosure: R.E.K. Man, None; M.B. Sasongko, None; R. Kawasaki, None; J.E. Noonan, None; T.C.S. Lo, None; C.D. Luu, None; E.L. Lamoureux, None; J.J. Wang, None 
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Figure 1
 
Image showing an optic nerve–centered scan from the Heidelberg Retinal Flowmeter. The orange regions adjacent to the optic disc (gray circular area) are the areas where capillary flow is assessed.
Figure 1
 
Image showing an optic nerve–centered scan from the Heidelberg Retinal Flowmeter. The orange regions adjacent to the optic disc (gray circular area) are the areas where capillary flow is assessed.
Figure 2
 
A fundus photograph showing the peripapillary annulus where oxygen saturation readings were taken. A false color map showing saturation values has been superimposed on the image. Saturation values are color coded according to the scale bar.
Figure 2
 
A fundus photograph showing the peripapillary annulus where oxygen saturation readings were taken. A false color map showing saturation values has been superimposed on the image. Saturation values are color coded according to the scale bar.
Figure 3
 
A scatter plot showing the distribution of oxygen saturation for retinal arterioles with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 3
 
A scatter plot showing the distribution of oxygen saturation for retinal arterioles with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 4
 
A scatter plot showing the distribution of oxygen saturation for retinal venules with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Figure 4
 
A scatter plot showing the distribution of oxygen saturation for retinal venules with age. Note due to the high correlation between the oxygen saturation values for the right and left eye of each subject, some data points may overlap and appear as one data point with thicker lines.
Table 1
 
Demographic and Clinical Parameters of Participants (n = 100 Eyes)
Table 1
 
Demographic and Clinical Parameters of Participants (n = 100 Eyes)
Parameters Mean (SD) or Median (IQR) Range of Values
Age, y 26 (23–31) 18–58
Female, % 56
Arteriolar SO2, % 96.02 (90.62–98.57) 77.03–100.82
Venular SO2, % 61.99 (56.68–64.08) 41.15–71.65
A-V difference, % 33.83 (3.36) 24.13–42.47
Blood flow, arbitrary units 247.66 (39.50) 126.22–345.92
HbA1c,* % 5.24 (0.31) 4.50–5.80
Triglycerides, mM 1.00 (0.80–1.30) 0.40–3.30
Total cholesterol, mM 4.94 (1.02) 2.60–8.00
Finger SO2, % 98 (97–99) 92–99
OPP, mm Hg† 45.48 (6.30) 32.00–60.33
Table 2
 
Comparison and Correlation of Retinal Arteriolar, Venular, and A-V SO2 Values Between the Right and Left Eyes (n = 50 Subjects)
Table 2
 
Comparison and Correlation of Retinal Arteriolar, Venular, and A-V SO2 Values Between the Right and Left Eyes (n = 50 Subjects)
Outcome Parameters Median (IQR) or Mean (SD) P Value Correlation Coefficient
Arteriolar SO2
 Right eye, % 95.94 (91.53–98.49) <0.001 0.83
 Left eye, % 96.54 (89.55–98.91)
Venular SO2
 Right eye, % 62.35 (57.65–64.17) <0.001 0.77
 Left eye, % 62.28 (56.60–64.03)
A-V Difference
 Right eye, % 33.79 (3.37) <0.001 0.78
 Left eye, % 33.57 (3.45)
Table 3
 
Unadjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Table 3
 
Unadjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Study Factors Arteriolar SO2 Venular SO2 A-V Difference
β (95% CI) β (95% CI) β (95% CI)
Age, y 0.33 (0.17–0.48)* 0.25 (0.09–0.42)* 0.07 (−0.01–0.16)
Female 2.11 (−1.10–5.33) 1.00 (−2.15–4.15) 1.11 (−0.68–2.90)
Capillary flow, arbitrary units −0.01 (−0.04–0.02) −0.004 (−0.03–0.03) −0.006 (−0.02–0.01)
HbA1c, % 3.10 (−1.47–7.67) 0.67 (−3.82–5.15) 2.51 (−0.50–5.52)
Triglycerides, mM 1.01 (−2.55–4.58) 1.50 (−1.75–4.76) −0.36 (−1.53–0.80)
Total cholesterol, mM 0.60 (−1.03–2.23) 0.03 (−1.69–1.74) 0.61 (−0.30–1.52)
Finger SO2, % 1.42 (0.19–2.66)* 0.66 (−0.56–1.88) 0.80 (0.44–1.17)*
OPP, mm Hg 0.02 (−0.18–0.22) 0.06 (−0.10–0.22) −0.03 (−0.15–0.09)
Table 4
 
Multivariable-Adjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Table 4
 
Multivariable-Adjusted Associations Between Age, Sex, Capillary Flow, Glucose, Triglycerides, Total Cholesterol, Finger SO2, and OPP, With Retinal Oximetry Values
Study Factors Arteriolar SO2 Venular SO2 Arterio-venous Difference
β* (95% CI) β† (95% CI) β* (95% CI)
Age, y 0.31 (0.15–0.48)‡ 0.26 (0.08–0.43)‡ 0.06 (−0.007–0.13)
Female 1.07 (−1.43–3.58) 0.67 (−2.39–3.73) 0.63 (−1.05–2.31)
Capillary flow, arbitrary units −0.007 (−0.03–0.02) −0.007 (−0.04–0.02) −0.005 (−0.02–0.08)
HbA1c, % 2.57 (−1.08–6.22) 1.29 (−3.67–6.26) 2.74 (−0.16–5.64)
Triglycerides, mM 0.31 (−2.39–3.01) 0.73 (−2.65–4.12) −0.41 (−1.62–0.80)
Total cholesterol, mM −0.15 (−2.19–1.90) −1.22 (−3.17–0.74) 0.86 (−0.03–1.69)
Finger SO2 (%) 1.34 (0.40–2.28)‡ 0.14 (−0.82–1.11) 0.73 (0.36–1.11)‡
OPP, mm Hg −0.04 (−0.23–0.15) 0.03 (−0.16–0.23) −0.05 (−0.16–0.05)
Table 5
 
Multivariable-Adjusted Associations Between Triglycerides and Total Cholesterol Levels With Retinal Oximetry Values in Subjects With Normal Triglyceride and Total Cholesterol Levels
Table 5
 
Multivariable-Adjusted Associations Between Triglycerides and Total Cholesterol Levels With Retinal Oximetry Values in Subjects With Normal Triglyceride and Total Cholesterol Levels
Study Factors Arteriolar SO2 Venular SO2 A-V Difference
β* (95% CI) β† (95% CI) β* (95% CI)
Triglycerides, mM 3.08 (−2.09–8.26) 4.05 (−0.91–9.02) 0.02 (−2.73–2.79)
Total cholesterol, mM 1.24 (−0.93–3.41) 0.42 (−2.26–3.10) 0.79 (−1.11–2.69)
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