Page S1 of S4
Supplementary material
Supplementary to the Methods
Calibration constants a and b
Schweitzer et al.6 used imaging spectroscopy to measure oxygen saturation of human whole
blood in vitro and in vivo and found that mean oxygen saturation of retinal arterioles and
venules was 92.2% and 57.9%, respectively. The calibration of a and b (equation 3 in the
paper) for Oxymap T1 was achieved by matching the optical density ratios from healthy
individuals measured with Oxymap T1, with the oxygen saturation measurements from
Schweitzer et al. That resulted in the calibration constants a=-1.1755 (previously -0.953 with
the Oxymap Analyzer software 2.2.1, version 3847) and b=1.1917 (previously 1.16).
Previously, Palsson et al.43 used the same version of the Oxymap Analyzer software but the
former calibration constants.
Correction factor for vessel diameter
For determination of a correction factor for vessel diameter, 21 eyes from 21 healthy persons
aged 18-40 years old were analyzed. The main superotemporal arteriole and venule from each
eye were analyzed at the bifurcation of the vessels from the primary branch (pri) to the
secondary branches (sec). Vessel segments 20-50 pixels in length were analyzed on both sides
of the bifurcation and a 15 pixel exclusion mark was placed at the top of the bifurcation.
Assumption was made that oxygen saturation (SatO2) was the same on both sides of the
bifurcation for both arterioles and venules (although for venules this might not be entirely true
but sufficiently close for this purpose). Therefore, we can assume that the mean oxygen
saturation of the secondary branches (sec1, sec2) is equal to the oxygen saturation of the
primary branch (pri):
SatO2(cor , pri) 
SatO2(cor ,sec1)  SatO2(cor ,sec 2)
(S1),
2
where SatO2(cor) is the oxygen saturation after correction for vessel diameter for primary (pri)
and secondary (sec) branches. To correct for vessel diameter we used the following equation:
SatO2(cor )  k * (d  d )  SatO2(uncor)
(S2),
where k is the correction factor, d is the vessel diameter, d is the mean vessel diameter, and
SatO2(uncor) is the measured oxygen saturation without correction. The mean diameter ( d ) was
11.24 pixels for arterioles and 14.46 pixels for venules. These values were used to calculate
the deviation in diameter. For each pixel, by which a vessel was wider than the mean, 1.16
Page S2 of S4
percentage points were added to the saturation value (and vice versa for vessels narrower than
the mean).
Combining equations S1 and S2 and solving for k results in:
k
SatO2(uncor,sec1)  SatO2(uncor,sec 2)  2 * SatO2(uncor, pri)
2 * d pri  dsec1  dsec 2
(S3).
Equation S3 was used to calculate k for each healthy eye and the median of the 21 eyes was
1.17% per pixel for arterioles and 1.15% per pixel for venules. As the numbers for arterioles
and venules were within the standard deviation of each other, we decided to average them to
the number of 1.16% per pixel for both arterioles and venules.
In summary, the original oxygen saturation values from the oximeter software were
recalculated to incorporate the new calibration constants as well as the vessel diameter
correction factor. This was done for every vessel measured for all the participants in the
present study (n=120).
Page S3 of S4
Supplementary to the Results
Three models of oxygen saturation
In the first linear regression model (A1, V1, AV1), we included only age and gender
variables. As we noticed the different slopes of males and females with age, we included the
interaction between age and gender in the second model (A2, V2, AV2) in order to test if age
had different effects in the two genders. In the third model (A3, V3, AV3) we included all
available variables for the subjects.
Table 1: The results of additional three models of multiple linear regression models for (a)
arterioles (models A1, A2, and A3), (b) venules (V1, V2, and V3), and (c) arteriovenous
difference (AV1, AV2, and AV3) (n=116). The linear regression equation for each model is
shown in the appropriate heading and the coefficients are named accordingly.
(a) Arterioles
Variable
Estimate
Standard Error
p-value
Model A1: Multiple linear regression for age and gender with no interaction between age and gender.
Oxygen saturation = a0 + a1 * age + a2 * gender
(Intercept)
90.7 (a0)
1.16
<0.0001
Age (years)
0.0012 (a1)
0.021
0.95
Gender (males=0; females=1)
2.44 (a2)
0.69
0.0006
Model A2: Multiple linear regression for age and gender with interaction between age and gender.
Oxygen saturation = b0 + b1 * age + b2 * gender + b3 * age * gender
(Intercept)
92.7 (b0)
1.66
<0.0001
Age (years)
-0.038 (b1)
0.031
0.23
Gender (males=0; females=1)
-0.74 (b2)
2.07
0.72
Age:Gender (years; males=0; females=1)
0.068 (b3)
0.042
0.11
Model A3: Multiple linear regression of all variables with no interaction between age and gender
Oxygen saturation = c0 + c1 * age + c2 * gender + c3 * smoker + c4 * pulseox + c5 * perfusion
(Intercept)
59.8 (c0)
27.7
0.033
Age (years)
-0.018 (c1)
0.023
0.45
Gender (males=0; females=1)
2.58 (c2)
0.69
0.0003
Current smoker (non-smoker=0; smoker=1)
-1.23 (c3)
1.02
0.23
Finger pulse oximetry (pulseox; %)
0.28 (c4)
0.28
0.33
Ocular perfusion pressure (perfusion; mmHg)
0.097 (c5)
0.041
0.020
Adjusted R2 for models A1, A2, and A3 were 0.086, 0.099, and 0.13, respectively.
Page S4 of S4
(b) Venules
Variable
Estimate
Standard Error
p-value
Model V1: Multiple linear regression for age and gender with no interaction between age and gender.
Oxygen saturation = a0 + a1 * age + a2 * gender
(Intercept)
58.1 (a0)
1.82
<0.0001
Age (years)
-0.12 (a1)
0.033
0.0004
Gender (males=0; females=1)
4.4 (a2)
1.09
<0.0001
Model V2: Multiple linear regression for age and gender with interaction between age and gender.
Oxygen saturation = b0 + b1 * age + b2 * gender + b3 * age * gender
(Intercept)
61.6 (b0)
2.60
<0.0001
Age (years)
-0.19 (b1)
0.050
0.0003
Gender (males=0; females=1)
-1.21 (b2)
3.25
0.71
Age:Gender (years; males=0; females=1)
0.12 (b3)
0.066
0.069
Model V3: Multiple linear regression of all variables with interaction between age and gender
Oxygen saturation = c0 + c1 * age + c2 * gender + c3 * smoker + c4 * pulseox + c5 * perfusion
(Intercept)
-11.0 (c0)
44.4
0.81
Age (years)
-0.13 (c1)
0.038
0.001
Gender (males=0; females=1)
4.43 (c2)
1.11
0.0001
Current smoker (non-smoker=0; smoker=1)
0.29 (c3)
1.64
0.86
Finger pulse oximetry (pulseox; %)
0.66 (c4)
0.45
0.15
Ocular perfusion pressure (perfusion; mmHg)
0.12 (c5)
0.066
0.065
Adjusted R2 for models V1, V2, and V3 were 0.23, 0.25, and 0.25, respectively.
(c) Arteriovenous difference
Variable
Estimate
Standard Error
p-value
Model AV1: Multiple linear regression for age and gender with no interaction between age and gender.
Oxygen saturation = a0 + a1 * age + a2 * gender
(Intercept)
32.6 (a0)
1.60
<0.0001
Age (years)
0.12 (a1)
0.029
<0.0001
Gender (males=0; females=1)
-1.98 (a2)
0.96
0.042
Model AV2: Multiple linear regression for age and gender with interaction between age and gender.
Oxygen saturation = b0 + b1 * age + b2 * gender + b3 * age * gender
(Intercept)
31.1 (b0)
2.32
<0.0001
Age (years)
0.15 (b1)
0.045
0.001
Gender (males=0; females=1)
0.48 (b2)
2.89
0.87
Age:Gender (years; males=0; females=1)
-0.053 (b3)
0.059
0.37
Model AV3: Multiple linear regression of all variables with interaction between age and gender
Oxygen saturation = c0 + c1 * age + c2 * gender + c3 * smoker + c4 * pulseox + c5 * perfusion +
c6 * age * gender
(Intercept)
71.5 (c0)
39.7
0.074
Age (years)
0.14 (c1)
0.047
0.0039
Gender (males=0; females=1)
0.66 (c2)
2.94
0.82
Current smoker (non-smoker=0; smoker=1)
-1.47 (c3)
1.46
0.32
Finger pulse oximetry (pulseox; %)
-0.40 (c4)
0.41
0.33
Ocular perfusion pressure (perfusion; mmHg)
-0.024 (c5)
0.059
0.69
Age:Gender (years; males=0; females=1)
-0.053 (c6)
0.059
0.37
Adjusted R2 for models AV1, AV2, and AV3 were 0.17, 0.17, and 0.16, respectively.