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Articles  |   October 2021
Variability of Retinal Oxygen Metrics in Healthy and Diabetic Subjects
Author Affiliations & Notes
  • Mansour Rahimi
    Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
  • Sophie Leahy
    Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
  • Norman P. Blair
    Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL, USA
  • Mahnaz Shahidi
    Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
  • Correspondence: Mahnaz Shahidi, Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, 1450 San Pablo Street, Los Angeles, CA 90033, USA. e-mail: mshahidi@usc.edu 
Translational Vision Science & Technology October 2021, Vol.10, 20. doi:https://doi.org/10.1167/tvst.10.12.20
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      Mansour Rahimi, Sophie Leahy, Norman P. Blair, Mahnaz Shahidi; Variability of Retinal Oxygen Metrics in Healthy and Diabetic Subjects. Trans. Vis. Sci. Tech. 2021;10(12):20. https://doi.org/10.1167/tvst.10.12.20.

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Abstract

Purpose: Previous studies have reported alterations in total retinal blood flow (TRBF), oxygen delivery (DO2), oxygen metabolism (MO2), and oxygen extraction fraction (OEF) due to retinal diseases. The purposes of the current study were to determine variabilities and establish normal confidence intervals (CIs) for these metrics.

Methods: A total of 22 healthy and 14 diabetic subjects participated in the study. Retinal vascular oxygen saturation (SO2) and TRBF were measured by oximetry and Doppler optical coherence tomography, respectively. DO2, MO2, and OEF were calculated from SO2 and TRBF measurements. Means, standard deviations (SDs), and CIs of metrics were determined in healthy subjects. Intra-visit variability was determined by the mean SDs of repeated measurements. Inter-visit variability was determined by the difference of measurements between two visits.

Results: TRBF was 44 ± 15 µL/min (95% CI, 37–51) in healthy subjects. Intra-visit variabilities of TRBF were 5 µL/min and 6 µL/min in healthy and diabetic subjects, respectively. Inter-visit variability of TRBF was 3 µL/min in diabetic subjects. DO2, MO2, and OEF were 8.3 ± 2.9 µLO2/min (95% CI, 7.0–9.6), 3.2 ± 0.9 µLO2/min (95% CI, 2.8–3.6), and 0.40 ± 0.08 (95% CI, 0.36–0.43), respectively, in healthy subjects. Inter-visit variabilities of DO2, MO2, and OEF were 0.6 µLO2/min, 0.1 µLO2/min, and 0.03, respectively, in diabetic subjects.

Conclusions: The findings established variabilities and normal baselines for TRBF, DO2, MO2, and OEF measurements in a small cohort of subjects.

Translational Relevance: The variability and normal baselines of retinal oxygen metrics may be useful for diagnosing and monitoring patients with retinal diseases.

Introduction
The retina is one of the most metabolically active tissues, thus requiring a high oxygen demand. Retinal and choroidal circulations supply oxygen that is utilized by the retinal tissue for energy production. Adequate oxygen is essential to maintain retinal metabolism and visual function. Inadequate retinal blood flow (RBF) and oxygen delivery (DO2), coupled with impaired oxygen metabolism (MO2) and altered oxygen extraction fraction (OEF), have been implicated in various retinal diseases.15 Specifically, changes in retinal microvasculature, RBF, and vascular oxygenation have been reported in diabetic retinopathy.610 Furthermore, there are reports of retinal oxygenation changes due to retinal vascular occlusions,1113 retinopathy of prematurity,14 and inherited retinal degenerations.15,16 Moreover, measurements of retinal oxygen saturation and metabolism have been reported in exudative age-related macular degeneration,17 glaucoma,12,1820 and sickle cell retinopathy.1 
Evaluating the variabilities of total RBF (TRBF) and retinal oxygen metrics (DO2, MO2, and OEF) is essential to determine the sensitivity of measurements for detecting changes due to disease. Previous studies have reported variability of RBF in healthy2123 and diabetic24 subjects and retinal vascular oxygen saturation in healthy subjects.25 However, to the best of our knowledge, the variabilities of retinal DO2, MO2, and OEF have not been reported previously. The purposes of the current study were to (1) determine intra- and inter-visit variabilities of TRBF, DO2, MO2, and OEF in healthy and diabetic subjects; and (2) establish normal confidence intervals (CIs) for the means of these metrics in healthy subjects. 
Materials and Methods
Subjects
The study was performed following the tenets of the Declaration of Helsinki and was approved by the institutional review board of the University of Southern California. All subjects provided written informed consent, and the study was in accordance with Health Insurance Portability and Accountability Act regulations. Fourteen diabetic subjects diagnosed with either no diabetic retinopathy (DR) or untreated mild non-proliferative DR (NPDR) were included in the study. The clinical diagnosis was based on retinal examination performed by specialists according to the International Clinical Disease Severity Scale for Diabetic Retinopathy.26 Twenty-two healthy subjects with normal clinical eye and retinal examinations participated in the study. Imaging was performed in one eye of each subject at one visit in healthy subjects and at two visits (6 ± 3 months apart) in diabetic subjects. 
Image Acquisition and Analysis
TRBF was measured using a commercially available optical coherence tomography (OCT) instrument (Avanti; Optovue, Inc., Fremont, CA). A custom scan protocol and image analysis software were used to measure Doppler phase shifts and blood flow within retinal veins on multiple optimized en face planes, as previously described.27,28 Briefly, an image set consisting of five consecutive volume scans covering a 2 × 2-mm area centered on the central retinal vein was acquired. Each volume contained 80 B-scans with 500 A-lines per B-scan and 195 en face planes. From each volume, TRBF was determined as the sum of flow in all detected retinal veins. Measurements from volumes within each image set were averaged to calculate TRBF. Repeated TRBF measurements were determined from multiple image sets and averaged to compute TRBF per subject. Figure 1A shows an example of an en face OCT image of the optic nerve head in a diabetic subject. 
Figure 1.
 
(A) Example of an en face OCT image of the optic nerve head in a diabetic subject. Blood flow measurements were obtained in veins detected in multiple en face planes. (B) A retinal image acquired in the same subject. Retinal vascular oxygen saturation was measured in blood vessel segments within the concentric rings.
Figure 1.
 
(A) Example of an en face OCT image of the optic nerve head in a diabetic subject. Blood flow measurements were obtained in veins detected in multiple en face planes. (B) A retinal image acquired in the same subject. Retinal vascular oxygen saturation was measured in blood vessel segments within the concentric rings.
Retinal vascular oxygen saturation (SO2) measurements were obtained by dual-wavelength oximetry using our custom-built slit-lamp biomicroscope as previously published.2,29 Nine retinal images were acquired at each imaging wavelength in a 5 × 5-mm area centered on the optic disk. Retinal images were analyzed to measure SO2 in all retinal vessels within a circumpapillary region of interest extending between one and two disk radii from the perimeter of the optic disk (Fig. 1B). The following relation determined the oxygen content of retinal arteries (O2A) and veins (O2V): O2 content = oxygen-binding capacity of hemoglobin (Hb) × Hb × SO2. Retinal arteriovenous oxygen content difference (O2AV) was calculated as O2A – O2V. DO2, MO2, and OEF were calculated according to the following equations: DO2 = TRBF × O2A; MO2 = TRBF × O2AV; and OEF = MO2/DO2
Statistical Analysis
Descriptive statistics were used to compare demographic characteristics between groups. Data were compared using the unpaired t-test for the continuous variables and the χ2 test or Fisher's exact test for categorical variables. Intra-visit variability of TRBF was determined by the mean of the standard deviation (SD) of multiple repeated measurements in each subject obtained on the same day, averaged in each group. Mean, SD, and 95% CIs for the metrics were established based on data in healthy subjects. We determined whether the means of metrics at each visit in the diabetic group were within the normal 95% CIs. Also, metrics were compared between groups by unpaired t-tests. Inter-visit variabilities of metrics were determined from the difference between measurements at two visits. Bland–Altman plots30 were generated that displayed inter-visit differences plotted as a function of the average of measurements at the two visits. Mean difference (bias) and 95% upper and lower limits of agreement, defined by mean ± 2 × SD of differences, were determined. The D'Agostino–Pearson omnibus test and Q–Q plots were used to assess the normality of data distributions. Pearson’s correlation was performed to assess the associations of TRBF with age. A two-sided P ≤ 0.05 was considered statistically significant. All analyses were performed using Prism 9.0.0 for Mac OS (GraphPad Software, San Diego, CA). 
Results
Subject Demographics
The demographics of the subjects are presented in Table 1. Age and sex did not significantly differ between healthy and diabetic subjects (P > 0.31). Race was statistically different between groups (P = 0.03). 
Table 1.
 
Subject Demographics
Table 1.
 
Subject Demographics
Blood Flow
TRBF data from image sets ranging between three and seven in healthy subjects and three and six in diabetic subjects were included. The number of image sets was five ± one in each group of subjects. Intra-visit variability of TRBF measurements (mean of SDs of repeated measurements) was 5 µL/min and 6 µL/min in healthy and diabetic subjects, respectively. TRBF (mean ± SD) was 44 ± 15 µL/min (95% CI, 37–51) in healthy subjects. Normal 95% CIs and TRBF measured in diabetic subjects are shown in Table 2. TRBF measurements at both visits in diabetic subjects were within normal 95% CIs and not significantly different than the mean in healthy subjects (P > 0.30). Inter-visit variability of TRBF (mean of measurement differences) was 3 µL/min in diabetic subjects. Figure 2 shows the Bland–Altman plot of TRBF. Upper and lower limits of agreement for differences were 18 and –12 µL/min, respectively. There was an inverse correlation between mean TRBF and age in healthy subjects (r = –0.45; P = 0.03; n = 22). 
Table 2.
 
Retinal Blood Flow and Oxygen Metrics in Diabetic Subjects (n = 14) at Two Visits and in Healthy Subjects (n = 22) at One Visit
Table 2.
 
Retinal Blood Flow and Oxygen Metrics in Diabetic Subjects (n = 14) at Two Visits and in Healthy Subjects (n = 22) at One Visit
Figure 2.
 
Inter-visit variability of TRBF displayed using the Bland–Altman plot. The difference in measurements between visits is plotted as a function of the average of measurements at two visits. The solid line shows the mean difference (bias) and the dashed lines denote upper and lower 95% limits of agreement.
Figure 2.
 
Inter-visit variability of TRBF displayed using the Bland–Altman plot. The difference in measurements between visits is plotted as a function of the average of measurements at two visits. The solid line shows the mean difference (bias) and the dashed lines denote upper and lower 95% limits of agreement.
Oxygen Metrics
The means, SDs, and 95% CIs for DO2, MO2, and OEF in healthy subjects are shown in Table 2. DO2 and MO2 were 8.3 ± 2.9 µLO2/min (95% CI, 7.0–9.6) and 3.2 ± 0.9 µLO2/min (95% CI, 2.8–3.6), respectively. OEF was 0.40 ± 0.08 (95% CI, 0.37–0.43). As shown in Table 2, DO2, MO2, and OEF measurements obtained at both visits in diabetic subjects were within the normal 95% CIs and not significantly different than the means in healthy subjects (P > 0.30). In diabetic subjects, inter-visit variabilities of DO2 and MO2 were 0.6 µLO2/min and 0.1 µLO2/min, respectively. Inter-visit variability of OEF was 0.03. Figure 3 shows Bland–Altman plots for DO2, MO2, and OEF. The upper and lower limits of agreement for differences were 3.6 and –2.4, 2.1 and –2.0, and 0.22 and –0.15 for DO2, MO2, and OEF, respectively. 
Figure 3.
 
Inter-visit variability of DO2 and MO2 (A) and OEF (B) displayed using Bland–Altman plots. The differences in measurements between visits are plotted as a function of the average of measurements at two visits. The solid line indicates mean difference (bias), and the dashed lines denote upper and lower 95% limits of agreement.
Figure 3.
 
Inter-visit variability of DO2 and MO2 (A) and OEF (B) displayed using Bland–Altman plots. The differences in measurements between visits are plotted as a function of the average of measurements at two visits. The solid line indicates mean difference (bias), and the dashed lines denote upper and lower 95% limits of agreement.
Discussion
Determining the variabilities of TRBF and oxygen metrics (DO2, MO2, and OEF) is necessary to determine alterations due to certain diseases and monitor changes over time. In the current study, intra-visit variability of TRBF and inter-visit variability of TRBF, DO2, MO2, and OEF were reported. Additionally, normal 95% CIs for these metrics were established in healthy subjects. 
Previous studies have reported intra-visit coefficient of variation of TRBF to be 4% in diabetic subjects24 and 8% to 11% in healthy subjects.22,31 These values are slightly lower than 10% in healthy subjects and 12% in diabetic subjects in the current study. Multiple factors can contribute to differences in measurement variabilities, such as subjects’ fixation and eye motion, the numbers of subjects evaluated and measurements obtained per subject, as well as previously demonstrated differences in technical instrumentation,32 and age of subjects.33 On the other hand, inter-visit variability of TRBF in the current study (3 µL/min) was lower than previously reported variabilities of 6 µL/min and 11 µL/min in young and elderly healthy subjects, respectively.22 
TRBF measurements in the current study were in agreement with previously reported values obtained using Doppler OCT methods.24,27,31,34,35 Additionally, the current study showed no significant difference in TRBF between healthy and diabetic subjects with no DR or untreated mild NPDR. Consistent with our results, other studies also reported no significant decrease in TRBF at the early stages of DR.24,36 However, one study reported lower TRBF in mild-to-moderate NPDR subjects compared to control subjects.4 
Finally, our finding of an inverse correlation between TRBF and age in healthy subjects agrees with published reports of decreases in retinal vessel density, venular blood flow velocity, and artery blood column diameter associated with aging.33,3739 The reduction in TRBF with age can be attributed to both vascular constriction and reduced vessel density, as previously suggested.33 
DO2, MO2, and OEF measurements in healthy subjects in the current study were comparable to those reported in previous studies.1,3,5,29 Additionally, normal 95% CIs established in healthy subjects provide a baseline for evaluating changes due to diseases. The current study also reported inter-visit variability of these metrics in diabetic subjects with no DR or mild NPDR. These results may be potentially used in future longitudinal studies to determine progressive changes in oxygen metrics over time or evaluate treatment outcomes. 
The current study had limitations. First, inter-visit variability of retinal oxygen metrics was assessed in diabetic subjects. Although the diabetic subjects had no or minimal retinopathy with oxygen metrics within the normal CIs at both visits and the time interval between visits was relatively short, the potential for changes over time may not be eliminated. Second, the sample size for this study was small, which may have limited the accurate establishment of normal baselines. Additionally, due to the small sample size, the potential effects of age, race, and sex on the variability of measurements were not evaluated, and differences in race could not be accounted for. Future studies with larger cohorts and multiple visits are necessary to determine more accurately the variabilities and normal CIs of metrics according to race, sex, and age. 
Overall, the findings established variabilities and normal baselines for TRBF, DO2, MO2, and OEF measurements, providing a basis for detecting and monitoring changes due to retinal diseases. 
Acknowledgments
Supported by grants from the National Eye Institute, National Institutes of Health (EY030115 and EY029220) and by an unrestricted departmental award from Research to Prevent Blindness. 
MS designed the study. MR and SL performed image analysis. MR and MS analyzed the data. MR wrote and edited the manuscript. MR, SL, NPB, and MS read and revised the manuscript. MS approved the manuscript for submission. 
Presented in part at the Association for Research in Vision and Ophthalmology virtual meeting, May 1–7, 2021. 
Disclosure: M. Rahimi, None; S. Leahy, None; N.P. Blair, None; M. Shahidi, None 
References
Shahidi M, Felder AE, Tan O, Blair NP, Huang D. Retinal oxygen delivery and metabolism in healthy and sickle cell retinopathy subjects. Invest Ophthalmol Vis Sci. 2018; 59: 1905–1909. [CrossRef] [PubMed]
Felder A, Wanek J, Blair N, et al. The effects of diabetic retinopathy stage and light flicker on inner retinal oxygen extraction fraction. Invest Ophthalmol Vis Sci. 2016; 57: 5586–5592. [CrossRef] [PubMed]
Fondi K, Wozniak PA, Howorka K, et al. Retinal oxygen extraction in individuals with type 1 diabetes with no or mild diabetic retinopathy. Diabetologia. 2017; 60: 1534–1540. [CrossRef] [PubMed]
Tayyari F, Khuu LA, Flanagan JG, Singer S, Brent MH, Hudson C. Retinal blood flow and retinal blood oxygen saturation in mild to moderate diabetic retinopathy. Invest Ophthalmol Vis Sci. 2015; 56: 6796–6800. [CrossRef] [PubMed]
Werkmeister RM, Schmidl D, Aschinger G, et al. Retinal oxygen extraction in humans. Sci Rep. 2015; 5: 15763. [CrossRef] [PubMed]
Nippert AR, Newman EA. Regulation of blood flow in diabetic retinopathy. Vis Neurosci. 2020; 37: E004. [CrossRef] [PubMed]
Hafner J, Ginner L, Karst S, et al. Regional patterns of retinal oxygen saturation and microvascular hemodynamic parameters preceding retinopathy in patients with type II diabetes. Invest Ophthalmol Vis Sci. 2017; 58: 5541–5547. [CrossRef] [PubMed]
Cheung CY, Ikram MK, Klein R, Wong TY. The clinical implications of recent studies on the structure and function of the retinal microvasculature in diabetes. Diabetologia. 2015; 58: 871–885. [CrossRef] [PubMed]
Hardarson SH, Stefánsson E. Retinal oxygen saturation is altered in diabetic retinopathy. Br J Ophthalmol. 2012; 96: 560–563. [CrossRef] [PubMed]
Nesper PL, Roberts PK, Onishi AC, et al. Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2017; 58: BIO307–BIO315. [CrossRef] [PubMed]
Rilvén S, Torp TL, Grauslund J. Retinal oximetry in patients with ischaemic retinal diseases. Acta Ophthalmol. 2017; 95: 119–127. [CrossRef] [PubMed]
Stefánsson E, Olafsdottir OB, Einarsdottir AB, et al. Retinal oximetry discovers novel biomarkers in retinal and brain diseases. Invest Ophthalmol Vis Sci. 2017; 58: BIO227–BIO233. [CrossRef] [PubMed]
Yoneya S, Saito T, Nishiyama Y, et al. Retinal oxygen saturation levels in patients with central retinal vein occlusion. Ophthalmology. 2002; 109: 1521–1526. [CrossRef] [PubMed]
Hartnett ME. Advances in understanding and management of retinopathy of prematurity. Surv Ophthalmol. 2017; 62: 257–276. [CrossRef] [PubMed]
Türksever C, López Torres LT, Valmaggia C, Todorova MG. Retinal oxygenation in inherited diseases of the retina. Genes (Basel). 2021; 12: 272. [CrossRef] [PubMed]
Bojinova RI, Türksever C, Schötzau A, Valmaggia C, Schorderet DF, Todorova MG. Reduced metabolic function and structural alterations in inherited retinal dystrophies: investigating the effect of peripapillary vessel oxygen saturation and vascular diameter on the retinal nerve fibre layer thickness. Acta Ophthalmol. 2017; 95: 252–261. [CrossRef] [PubMed]
Geirsdottir A, Hardarson SH, Olafsdottir OB, Stefánsson E. Retinal oxygen metabolism in exudative age-related macular degeneration. Acta Ophthalmol. 2014; 92: 27–33. [CrossRef] [PubMed]
Shughoury A, Mathew S, Arciero J, et al. Retinal oximetry in glaucoma: investigations and findings reviewed. Acta Ophthalmol. 2020; 98: 559–571. [CrossRef] [PubMed]
Evangelho K, Mogilevskaya M, Losada-Barragan M, Vargas-Sanchez JK. Pathophysiology of primary open-angle glaucoma from a neuroinflammatory and neurotoxicity perspective: a review of the literature. Int Ophthalmol. 2019; 39: 259–271. [CrossRef] [PubMed]
Tobe LA, Harris A, Schroeder A, et al. Retinal oxygen saturation and metabolism: how does it pertain to glaucoma? An update on the application of retinal oximetry in glaucoma. Eur J Ophthalmol. 2013; 23: 465–472. [CrossRef] [PubMed]
Tani T, Song YS, Yoshioka T, et al. Repeatability and reproducibility of retinal blood flow measurement using a Doppler optical coherence tomography flowmeter in healthy subjects. Invest Ophthalmol Vis Sci. 2017; 58: 2891–2898. [CrossRef] [PubMed]
Tayyari F, Yusof F, Vymyslicky M, et al. Variability and repeatability of quantitative, Fourier-domain optical coherence tomography Doppler blood flow in young and elderly healthy subjects. Invest Ophthalmol Vis Sci. 2014; 55: 7716–7725. [CrossRef] [PubMed]
Guan K, Hudson C, Flanagan JG. Variability and repeatability of retinal blood flow measurements using the Canon Laser Blood Flowmeter. Microvasc Res. 2003; 65: 145–151. [CrossRef] [PubMed]
Pechauer AD, Hwang TS, Hagag AM, et al. Assessing total retinal blood flow in diabetic retinopathy using multiplane en face Doppler optical coherence tomography. Br J Ophthalmol. 2018; 102: 126–130. [CrossRef] [PubMed]
O'Connell RA, Anderson AJ, Hosking SL, Batcha AH, Bui BV. Test-retest reliability of retinal oxygen saturation measurement. Optom Vis Sci. 2014; 91: 608–614. [CrossRef] [PubMed]
Wilkinson CP, Ferris FL, Klein RE, et al. Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology. 2003; 110: 1677–1682. [CrossRef] [PubMed]
Tan O, Liu G, Liang L, et al. En face Doppler total retinal blood flow measurement with 70 kHz spectral optical coherence tomography. J Biomed Opt. 2015; 20: 066004. [CrossRef] [PubMed]
Pechauer AD, Tan O, Liu L, et al. Retinal blood flow response to hyperoxia measured with en face Doppler optical coherence tomography. Invest Ophthalmol Vis Sci. 2016; 57: OCT141–OCT145. [CrossRef] [PubMed]
Felder A, Wanek J, Blair N, Shahidi M. Inner retinal oxygen extraction fraction in response to light flicker stimulation in humans. Invest Ophthalmol Vis Sci. 2015; 56: 6633–6637. [CrossRef] [PubMed]
Bland JM, Altman DG. Agreement between methods of measurement with multiple observations per individual. J Biopharm Stat. 2007; 17: 571–582. [CrossRef] [PubMed]
Wang Y, Lu A, Gil-Flamer J, Tan O, Izatt JA, Huang D. Measurement of total blood flow in the normal human retina using Doppler Fourier-domain optical coherence tomography. Br J Ophthalmol. 2009; 93: 634–637. [CrossRef] [PubMed]
Luksch A, Lasta M, Polak K, et al. Twelve-hour reproducibility of retinal and optic nerve blood flow parameters in healthy individuals. Acta Ophthalmol. 2009; 87: 875–880. [CrossRef] [PubMed]
Ehrlich R, Kheradiya NS, Winston DM, Moore DB, Wirostko B, Harris A. Age-related ocular vascular changes. Graefes Arch Clin Exp Ophthalmol. 2009; 247: 583–591. [CrossRef] [PubMed]
Wang Y, Fawzi AA, Varma R, et al. Pilot study of optical coherence tomography measurement of retinal blood flow in retinal and optic nerve diseases. Invest Ophthalmol Vis Sci. 2011; 52: 840–845. [CrossRef] [PubMed]
Dai C, Liu X, Zhang HF, Puliafito CA, Jiao S. Absolute retinal blood flow measurement with a dual-beam Doppler optical coherence tomography. Invest Ophthalmol Vis Sci. 2013; 54: 7998–8003. [CrossRef] [PubMed]
Lorenzi M, Feke GT, Cagliero E, et al. Retinal haemodynamics in individuals with well-controlled type 1 diabetes. Diabetologia. 2008; 51: 361–364. [CrossRef] [PubMed]
Wei Y, Jiang H, Shi Y, et al. Age-related alterations in the retinal microvasculature, microcirculation, and microstructure. Invest Ophthalmol Vis Sci. 2017; 58: 3804–3817. [CrossRef] [PubMed]
Kotliar KE, Mücke B, Vilser W, Schilling R, Lanzl IM. Effect of aging on retinal artery blood column diameter measured along the vessel axis. Invest Ophthalmol Vis Sci. 2008; 49: 2094–2102. [CrossRef] [PubMed]
Bata AM, Fondi K, Szegedi S, et al. Age-related decline of retinal oxygen extraction in healthy subjects. Invest Ophthalmol Vis Sci. 2019; 60: 3162–3169. [CrossRef] [PubMed]
Figure 1.
 
(A) Example of an en face OCT image of the optic nerve head in a diabetic subject. Blood flow measurements were obtained in veins detected in multiple en face planes. (B) A retinal image acquired in the same subject. Retinal vascular oxygen saturation was measured in blood vessel segments within the concentric rings.
Figure 1.
 
(A) Example of an en face OCT image of the optic nerve head in a diabetic subject. Blood flow measurements were obtained in veins detected in multiple en face planes. (B) A retinal image acquired in the same subject. Retinal vascular oxygen saturation was measured in blood vessel segments within the concentric rings.
Figure 2.
 
Inter-visit variability of TRBF displayed using the Bland–Altman plot. The difference in measurements between visits is plotted as a function of the average of measurements at two visits. The solid line shows the mean difference (bias) and the dashed lines denote upper and lower 95% limits of agreement.
Figure 2.
 
Inter-visit variability of TRBF displayed using the Bland–Altman plot. The difference in measurements between visits is plotted as a function of the average of measurements at two visits. The solid line shows the mean difference (bias) and the dashed lines denote upper and lower 95% limits of agreement.
Figure 3.
 
Inter-visit variability of DO2 and MO2 (A) and OEF (B) displayed using Bland–Altman plots. The differences in measurements between visits are plotted as a function of the average of measurements at two visits. The solid line indicates mean difference (bias), and the dashed lines denote upper and lower 95% limits of agreement.
Figure 3.
 
Inter-visit variability of DO2 and MO2 (A) and OEF (B) displayed using Bland–Altman plots. The differences in measurements between visits are plotted as a function of the average of measurements at two visits. The solid line indicates mean difference (bias), and the dashed lines denote upper and lower 95% limits of agreement.
Table 1.
 
Subject Demographics
Table 1.
 
Subject Demographics
Table 2.
 
Retinal Blood Flow and Oxygen Metrics in Diabetic Subjects (n = 14) at Two Visits and in Healthy Subjects (n = 22) at One Visit
Table 2.
 
Retinal Blood Flow and Oxygen Metrics in Diabetic Subjects (n = 14) at Two Visits and in Healthy Subjects (n = 22) at One Visit
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