The normal retinal vascular system provides all metabolic needs, such as nourishment, oxygen transport, and immune response control, and is vital for continuity of normal visual function.1 This system is damaged in various retinal and choroidal vascular diseases, such as diabetic retinopathy, retinal artery or vein occlusions, and optic neuropathies.2–5 Ocular blood flow is also affected by many systemic disorders.6 Therefore, quantitative and qualitative assessment of the retinal vascular system is essential for the management of such diseases.
Fluorescein angiography is still the gold standard for clinically evaluating the retinal and choroidal vasculature and its pathologies, and can locate abnormalities by providing dynamic visualization with a wide field of view.7 However, the invasive nature of fluorescein angiography and providing only two-dimensional data without depth resolution are key drawbacks. Additionally, adverse effects such as nausea, vomiting, and allergic reactions, including anaphylactic shock, can occur from the dye used in this procedure.7 On the other hand, optical coherence tomography angiography (OCTA), a non-contact and non-invasive method of detecting blood flow using amplitude or phase decorrelation, provides comprehensive data on the retinal and choroidal microvascular network.8,9 The human arterial and venous network has three capillary plexuses: intermediate, superficial (inner) (SCP), and deep (outer) (DCP). OCTA is a new technology that can detect blood flow, tissue structure, and pathologies at all levels and localize the exact depth and location of lesions.8,9
An important advantage of OCTA is its ability to quantify the vessel perfusion density of the radial peripapillary capillary vessel density, SCP, DCP, and choriocapillaris, allowing understanding of the exact underlying pathology. With the quantification of vessel density and the foveal avascular zone (FAZ), follow-up can also be more effective and reliable, resulting in appropriate treatment planning.10 Repeatability and reproducibility of OCTA has also been demonstrated for both parapapillary and macular perfusion.11–14 Therefore, OCTA could be a standard method for the future.
Understanding the differences between normal and pathologic retinal vessel density will help validate abnormal OCTA findings in retinal vascular disorders. These data can help quantify ischemic areas and neovascularization. Using OCTA, normative data for macular vessel density in healthy individuals have been quantified and its associations with age, sex, and refractive errors assessed by recent studies, especially in adult eyes,15–20 but few studies have focused on the normal eyes of children.21,22 Zhang et al21 recently described the variation and characteristics of vessel density of the macula and optic nerve in healthy Chinese children. Because the quantification measured by OCTA varies among different ethnicities,19,20 there is still a lack of normative data for children to assess vessel density in macular and optic nerve diseases. Factors such as age, gender, axial length, refractive errors, and even ethnicity should also be evaluated for effective use of OCTA.
In this prospective study, we first aimed to quantify the vessel density of both the macula and optic nerve and FAZ values in normal eyes of children. Second, we evaluated the effects of age, gender, axial length, body mass index (BMI), and refractive errors on macular and peripapillary vessel density and FAZ.
Patients and Methods
This prospective study was conducted at the ophthalmology clinic of a tertiary referral center in Turkey. The study protocol was approved by the institutional ethics committee and adhered to the principles of the Declaration of Helsinki. Written informed consent was obtained from the legal guardians of participants after explanation of the nature of the study prior to enrollment.
The inclusion criteria were as follows: age 18 years or younger, refractive error of 6.00 diopters (D) or less, axial length between 20 and 26 mm, best corrected visual acuity (BCVA) of 20/20 or better, and intraocular pressure of less than 21 mm Hg. The right eyes of all participants with no history or clinical evidence of retinal disease were included in the study. Exclusion criteria were any history or clinical evidence of retinal disease; presence of macular edema; history of any systemic disorder (eg, diabetes mellitus); diabetic retinopathy; previous ocular surgery or laser photocoagulation; refractive error of greater than 6.00 D; signs of any other chorioretinal disease; glaucoma; topical corticosteroid use within 6 months prior to study enrollment; glaucomatous findings such as glaucomatous optic nerve changes, peripapillary hemorrhage, cupping, notching, or focal thinning of the neuroretinal rim; or intraocular pressure readings of greater than 20 mm Hg in the absence of anti-glaucomatous agents for anterior segment opacities. Only images with a signal strength index of 8 or greater were included in the study. Eyes with poor quality images on OCTA due to eye movements, poor fixation, or media opacities were excluded.
The demographic data of all participants were recorded, and all underwent a full ophthalmological examination, including autorefraction (Tonoref III; Nidek Co. Ltd), BCVA with a Snellen chart, intraocular pressure measurement with an air-puff tonometer (Tonoref III), slit-lamp examination, and dilated funduscopy, as well as axial length measurements using the IOLMaster (Carl Zeiss Meditec), macular and peripapillary vessel density, and FAZ quantification using AngioVue software (version 2017.1.0.151) of the RTVue XR Avanti (Optovue, Inc). Participants were grouped according to the autorefraction results. Spherical equivalent between −1 and +1 was assessed as emmetropic, −1 and −6 as myopic, and +1 and +6 as hyperopic.
All OCTA image acquisitions were performed by the same experienced clinician (YSG) using AngioVue software (version 2017.1.0.151) of the RTVue XR Avanti. All OCTA scans were performed under the same environmental conditions during the same daily time interval (between 9:00 AM and 12:00 PM). Before examinations, all eyes were dilated with 1% tropicamide eye drops. At the time of scanning, participants were directed to focus on an internal fixation target after stabilization was achieved with standard chinrest and forehead supports. Three consecutive scans were captured for each eye, and the one with the best quality was considered for analysis.
The OCTA system used in the study has a split-spectrum amplitude decorrelation angiography algorithm and operates at 70,000 A-scans per second to acquire OCTA volumes of 400 × 400 A-scans. All eye scans were of a 6 × 6 mm scanning area centered on the fovea. All OCTA images were reviewed by one experienced independent grader (YSG) to determine whether the correct segmentation was achieved. Poor quality scans with motion artifacts or blurred images, or where the data were insufficient for proper analysis, were also identified. Participants with the following criteria were excluded: low signal strength index of less than 8, media opacity obscuring the view of the vasculature, poor fixation leading to motion or doubling artifacts, the presence of one or more blink artifacts, or the presence of cystoid macular changes causing disrupted retinal anatomic features or segmentation errors.
Vascular density was defined as the percentage of the sample area occupied by vessel lumens following binary reconstruction of images. Nonflow area was defined as capillary dropout areas where blood flow is lower than normal due to relative or total ischemia. OCTA automatic quantification tool measures flow area, nonflow area, and flow area density.
The device's automatic system inserted three fovea-centered circles on the macula via a density assessment tool for the SCP and DCP. The slab taken from the internal limiting membrane to the inner plexiform layer–inner nuclear layer interface was defined as the SCP slab, and the slab taken from the inner plexiform layer–inner nuclear layer interface to the outer plexiform layer–outer nuclear layer interface was defined as the DCP slab. The vessel density in the area of the small circle with a diameter of 1 mm was defined as the foveal zone vessel density, the area of the middle circle with a diameter of 3 mm was defined as the parafoveal zone vessel density, and the outer circle with a diameter of 6 mm was defined as the perifoveal zone vessel density. Additionally, the zones were automatically divided into two equal hemispheres (superior and inferior) and four equal quadrants (temporal, nasal, inferior, and superior). Vessel density measurements by OCTA are shown in Figure 1. The nonflow area in the SCP was automatically obtained using the nonflow assessment tool and measurements were taken for the FAZ area in the whole retinal vasculature and FAZ perimeter. The acircularity index of the FAZ and foveal density (FD-300) were automatically obtained using the FAZ assessment tool. The acircularity index was defined as the ratio of the perimeter of the FAZ and the perimeter of a circle with an equal area. The FD-300 is the vessel density located 300 mm around the FAZ. With complementation of these measurements, the nonflow area in the SCP, FAZ area of the whole retina, FAZ perimeter, acircularity index, and FD-300, as well as the vessel density values for the SCP and DCP in the foveal, parafoveal, and perifoveal zones, were recorded for analysis. Nonflow and FAZ assessment tools of OCTA are shown in Figure 2.
Density assessment tool of optical coherence tomography angiography (OCTA). Superficial (A) and deep (B) capillary plexuses demonstrated by OCTA. The zones that were automatically divided by the analytic software of the device are shown at the right corner of each figure.
(A) Nonflow and (B) foveal avascular zone (FAZ) assessment tools of optical coherence tomography angiography. Nonflow area (mm2), FAZ area (mm2) in full retinal vasculature, FAZ perimeter (mm), acircularity index of the FAZ, and foveal density (FD-300) are demonstrated.
For evaluation of the radial peripapillary capillary plexus, all of the eye scans were of a 4.5 × 4.5 mm (400 × 400 pixels) scanning area centered on the optic nerve head. The device automatically attached two concentric circles centered on the optic nerve head with diameters of 2 mm (inner) and 4 mm (outer), with a ring width of 1 mm. The automatic system calculated the radial peripapillary capillary vessel density between these rings at the two equal hemispheres (superior and inferior) and eight equal sectors using the density assessment tool of the OCTA. Segmentation was between the inner limiting membrane and the retinal nerve fiber layer. Radial peripapillary capillary vessel density was automatically calculated by OCTA is shown as Figure 3.
Radial peripapillary capillary vessel density (RPCvd) was automatically calculated between two optic nerve head–centered concentric circles with a diameter of 2 mm (inner) and 4 mm (outer) (ring width, 1 mm) at eight equal sectors and two equal hemispheres (superior and inferior).
SPSS software version 22.0 for Windows (SPSS, Inc) was used for the statistical analysis of the study. The mean ± standard deviation was calculated for quantitative variables. Visual (histogram and probability graphs) and analytical (Kolmogorov–Smirnov and Shapiro–Wilk tests) methods were used to check whether the sample came from a normally distributed population. Depending on the distribution, comparisons of means or medians of independent variables were performed using the Student t test, Mann–Whitney test, or one-way analysis of variance test in the case of three groups. An independent t test was used to observe differences in gender. The Pearson correlation coefficient was used to determine correlation between the investigated OCTA parameters and age, axial length, and BMI. A P value of .05 was considered statistically significant.
This study enrolled 92 eyes of 92 participants (42 boys and 50 girls). The mean age was 13.4 ± 2.65 years (range: 7 to 18 years). The demographic characteristics of the participants are shown in Table 1.
Demographic and Ocular Characteristics
We found no differences between the genders when evaluating age (P = .10), axial length (P = .45), or BMI (P = .35). In evaluation of the nonflow area and FAZ area at the fovea, girls had a significantly larger zone (P = .01 and .02, respectively). Vessel density at the fovea in the SCP and DCP was significantly greater in boys (P = .01 and .03, respectively). No significant differences were found in other sectors or in the whole image. The mean macular vessel density of the enrolled eyes, including the fovea, parafovea, and perifovea of the superficial retina and deep retina, and the FAZ area for both genders are shown in Table 2.
Comparison of the FAZ and Macular Vessel Density Assessment Tool Parameters in Different Sections by Gender
Table 3 summarizes the vessel densities of the inside disc and peripapillary areas. When we evaluated radial peripapillary capillary vessel density by gender, only the inferior temporal and superior temporal vessel densities were significantly higher in girls than boys (P = .01 and .03, respectively).
Comparison of the Radial Peripapillary Capillary Vessel Density Parameters in Different Sections by Gender
We further divided participants into three groups as emmetropic, myopic, and hypermetropic according to their refractive status. No significant differences were found in the macular and optic nerve vessel density measurements within groups according to refractive status (P > .05, for all).
When we correlated the age with the FAZ and vessel density parameters, only nonflow area was positively correlated with age (r = 0.22, P = .03; Figure 4). The correlation of BMI (Figure 5) and axial length (Figure 6) with FAZ and vessel density parameters showed no significant correlation (P > .05, for all).
The correlation between age and vascular density (VD) of the macula and optic disc. FAZ = foveal avascular zone
The correlation between body mass index (BMI) and vascular density (VD) of the macula and optic disc. FAZ = foveal avascular zone
The correlation between axial length and vascular density (VD) of the macula and optic disc. FAZ = foveal avascular zone
In recent years, OCTA has become an important tool in detecting vascular abnormalities in the posterior segment of the eye. Many studies have found vessel density and FAZ abnormalities in various diseases in children.23–25 However, the lack of data on the normal eyes of children is a limitation for its clinical application. In this study, we evaluated the FAZ and vessel density of the optic nerve and macula by OCTA in the normal eyes of children aged 7 to 18 years to determine normative values. Further, we assessed the influence of gender, age, axial length, and BMI on the FAZ and vessel density of the macula and optic nerve head.
The evaluation of the macula is one of the main characteristics of OCTA. Many studies have evaluated normative data of the FAZ and vessel density of the macula in adults.19–22 However, studies in children are limited. Inanc et al23 evaluated vascular abnormalities in children with diabetes mellitus and compared the vessel density and FAZ values with a control group. The mean FAZ area, nonflow area, acircularity index, and FAZ perimeter were 0.27 mm2, 0.49 mm2, 1.90 mm, and 1.03, respectively.23 These values were similar to our results of 0.28 mm2, 0.49 mm2, 1.99, and 1.08, respectively. Another study evaluating normative data of children found the mean FAZ area was 0.28 mm2, similar to our results.21 The same study also found the mean vessel densities of the fovea, parafovea, and perifovea at the superficial retina and deep retina were 20.1%, 50.2%, 49.4%, 36.1%, 53.9%, and 48.1%, respectively.21 These values in our study were 20.6%, 54.4%, 51.9%, 38.3%, 57.9%, and 55.7%, respectively. Inanc et al23 found the same values in controls were 20.5%, 52.9%, 51.0%, 38.2%, 56.7%, and 53.6%, respectively. The vessel density values in our studies were higher than those obtained by Zhang et al21 and similar to those of Inanc et al.23 All three studies used the AngioVue device (version 2017.1.0.151 of the RTVue XR Avanti; OptoVue, Inc), and all of the eye scans were of a 6 × 6 mm scanning area centered on the fovea, making the comparison more direct. The difference in vessel density between our study and Zhang et al21 might be due to the age range of 7 to 18 years in our study and 5 to 18 years in their study. We could not include children younger than 7 years due to lack of cooperation with the measurement. Participants younger than 7 years could be the reason for the difference between the two studies.
We further analyzed the vessel density properties of the optic nerve. The mean peripapillary and inside disc radial peripapillary capillary density were 51.3% and 52.8%, respectively. Zhang et al21 found the mean radial peripapillary capillary vessel density and inside disc vessel density were 51.6% and 51.7%, respectively, which was similar to our results. They found the highest vessel densities at the inferior temporal and superior temporal areas, and lowest vessel densities at the nasal inferior and nasal superior areas, which was also consistent with our results.21
The change in vessel density by age has been evaluated by many studies, which have found a negative correlation.19,26,27 Hashmani et al19 reported that the mean vessel density decreased as age increased, especially in the fifth decade of life.19 However, these studies were performed in adults.19,26,27 Zhang et al21 found that macular vessel density had no significant correlation with age. They proposed that age might not be a key factor affecting macular vessel density in children aged 5 to 18 years. Similar to these results, we also did not find any significant correlation between age and macular and optic nerve vessel density in children aged 7 to 18 years. Different from our results, Zhang et al21 found a correlation between age and inside disc vessel density. Previous studies reported that radial peripapillary capillary density decreased with age in adults.26 Zhang et al21 proposed that this could be the result of the study group age ranging from 5 to 18 years, because the retinal nerve fiber layer thickness was positively correlated with age and axial length in participants younger than 15 years but negatively correlated with age in adults.28 Despite no significant correlation between age and vessel density, we found a positive weak correlation between nonflow area and age. This could be the result of the decrease in vessel density of the macula by age, but the difference was not statistically significant.
The difference in FAZ areas and vessel density by gender has also been evaluated by several studies. Shahlaee et al27 reported no gender difference in vessel density in a study including adults. However, Hashmani et al19 found greater foveal vessel density in males. Yilmaz et al20 reported a greater FAZ area in girls than boys, but no significant difference in vessel density was observed between genders. A study evaluating children aged from 5 to 18 years reported that the mean superficial and deep retinal fovea vessel densities of boys were greater than those of girls, and the mean FAZ area of boys was smaller than that of girls.21 Similar to these results, we also found greater densities at the fovea at the SCP and DCP. As expected, the mean FAZ area was smaller in boys than girls. Additionally, we found greater nonflow area and FD-300 values in girls than boys. We can postulate that these changes could be induced by hormonal variations, which are more pronounced in women than in men. Ocular tissues express estrogen receptors and future studies may clarify their possible role in the foveal microvascular changes. We found no statistical difference between genders in the parafovea and perifovea vessel densities of the SCP and DCP.
The refractive status of the eye could also affect the FAZ area and vessel density of the optic nerve and macula. A study evaluating myopic patients by Tsui et al29 found reduced deep vessel density in eyes with high myopia compared to eyes with moderate and low myopia. Wang et al30 reported decreased peripapillary retinal perfusion in eyes with high myopia in comparison with emmetropic eyes. We compared eyes with low to moderate myopia, low to moderate hyperopia, and emmetropia and found no significant changes in FAZ and vessel density values at either the DCP or SCP. We selected participants with refractive status between −6.00 and +6.00 D. Therefore, this result was not surprising, according to the findings of the previous studies.
Unlike the existing articles in the literature, we analyzed the effect of BMI on the FAZ and vessel density of the optic nerve and macula. The correlation of BMI with the FAZ area and vessel density values showed no significant changes. Therefore, when analyzing OCTA in patients with different BMIs, we can be comfortable with remembering that data.
The strength of our study is the automatic segmentation and automatic data analysis of the device, which reduces researcher error. Moreover, all measurements were repeated three times; repeatability of the device was seen by the researchers and only measurements with high signal strength index were selected for analysis.
Our study has several limitations. First, because cooperation is a problem in children, we only recruited those aged between 7 and 18 years. Second, the sample size was relatively small in age and axial length subgroups. Third, our measurements were only at 6 × 6 mm, which can only include a small area in the posterior pole and may limit our understanding of the microvascular changes in the peripheral retina. Limited ethnic backgrounds were also a drawback. Therefore, well-designed multicenter studies with large samples and different ethnic backgrounds are needed for better understanding of the effect of OCTA on these issues.
In this study, we showed the normative values of the FAZ area and vessel density of the optic nerve and macula in children. Although boys had greater foveal vessel density at the SCP and DCP, girls had greater FAZ area and nonflow area. The refractive status of the eye did not influence OCTA parameters. Regarding the correlation of age with FAZ and vessel density parameters, only nonflow area was positively correlated with age. No significant correlation was found between BMI or axial length and FAZ or vessel density parameters. This study provides useful normative data that will be important in interpreting OCTA results in various diseases in children.
- Jia Y, Bailey ST, Hwang TS, et al. Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye. Proc Natl Acad Sci USA. 2015;112(18):E2395–E2402. doi:10.1073/pnas.1500185112 [CrossRef]
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- Wylegala A. Principles of OCTA and applications in clinical neurology. Curr Neurol Neurosci Rep. 2018;18(12):96. doi:10.1007/s11910-018-0911-x [CrossRef]
- Johnson RN, Fu AD, McDonald HR, et al. Fluorescein angiography: basic principles and interpretation. In: Retina. 5th ed. London: Elsevier Inc.2012. p. 2–50.e1.
- Tokayer J, Jia Y, Dhalla AH, Huang D. Blood flow velocity quantification using split-spectrum amplitude-decorrelation angiography with optical coherence tomography. Biomed Opt Express. 2013;4(10):1909–1924. doi:10.1364/BOE.4.001909 [CrossRef]
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- Rodríguez FJ, Staurenghi G, Gale RVision Academy Steering Committee. The role of OCT-A in retinal disease management. Graefes Arch Clin Exp Ophthalmol. 2018;256(11):2019–2026. doi:10.1007/s00417-018-4109-3 [CrossRef]
- Lei J, Durbin MK, Shi Y, et al. Repeatability and reproducibility of superficial macular retinal vessel density measurements using optical coherence tomography angiography en face images. JAMA Ophthalmol. 2017;135(10):1092–1098. doi:10.1001/jamaophthalmol.2017.3431 [CrossRef]
- Corvi F, Pellegrini M, Erba S, Cozzi M, Staurenghi G, Giani A. Reproducibility of vessel density, fractal dimension, and foveal avascular zone using 7 different optical coherence tomography angiography devices. Am J Ophthalmol. 2018;186:25–31. doi:10.1016/j.ajo.2017.11.011 [CrossRef]
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Demographic and Ocular Characteristics
|Characteristic||Mean ± SD (Range)|
|Age (years)||13.4 ± 2.6 (7 to 18)|
|Body height (cm)||157.2 ± 11.7 (120 to 176)|
|Body weight (kg)||51.7 ± 13.0 (19 to 84)|
|Body mass index (kg/m2)||20.6 ± 3.8 (15.3 to 30.1)|
|Axial length (mm)||23.3 ± 0.9 (21.2 to 25.4)|
Comparison of the FAZ and Macular Vessel Density Assessment Tool Parameters in Different Sections by Gendera
|Parameter||Male + Female (n = 92)||Female (n = 50)||Male (n = 42)||Pb,c|
|Nonflow area, mm2, SCP||0.49 ± 0.14||0.52 ± 0.14||0.44 ± 0.14||.01|
| FAZ area, mm2, whole retina||0.28 ± 0.11||0.30 ± 0.11||0.25 ± 0.09||.02|
| FAZ perimeter, mm||1.99 ± 0.40||2.05 ± 0.42||1.89 ± 0.35||.08|
| Acircularity index||1.08 ± 0.02||1.08 ± 0.02||1.09 ± 0.02||.69|
| Foveal density, %||56.58 ± 3.74||57.29 ± 3.83||55.30 ± 3.27||.01|
|Vessel density, SCP flow (%)|
| Whole retina||51.36 ± 2.53||51.53 ± 2.33||51.06 ± 2.86||.38|
| Superior-hemi||51.37 ± 2.45||51.52 ± 2.25||51.10 ± 2.79||.43|
| Inferior-hemi||51.35 ± 2.85||51.54 ± 2.60||51.02 ± 3.27||.41|
| Fovea||20.66 ± 6.61||19.40 ± 6.21||22.90 ± 6.81||.01|
| Parafovea||54.46 ± 2.89||54.68 ± 2.49||54.08 ± 3.49||.34|
| Superior-hemi||54.39 ± 3.07||54.49 ± 2.80||54.22 ± 3.54||.69|
| Inferior-hemi||54.52 ± 3.09||54.86 ± 2.55||53.91 ± 3.85||.16|
| Temporal||54.21 ± 3.08||54.50 ± 2.76||53.69 ± 3.56||.23|
| Superior||54.96 ± 3.43||55.03 ± 3.19||54.83 ± 3.87||.79|
| Nasal||53.70 ± 3.24||53.78 ± 2.89||53.56 ± 3.84||.74|
| Inferior||55.18 ± 3.45||55.55 ± 2.86||54.51 ± 4.28||.16|
| Perifovea||51.90 ± 2.59||52.07 ± 2.42||51.59 ± 2.88||.39|
| Superior-hemi||51.84 ± 2.52||52.04 ± 2.29||51.50 ± 2.90||.32|
| Inferior-hemi||51.90 ± 2.99||52.10 ± 2.78||51.53 ± 3.35||.39|
| Temporal||48.49 ± 3.10||48.62 ± 3.11||48.26 ± 3.12||.60|
| Superior||51.89 ± 2.96||52.23 ± 2.59||51.27 ± 3.48||.13|
| Nasal||55.65 ± 2.54||55.87 ± 2.32||55.26 ± 2.90||.26|
| Inferior||51.94 ± 3.53||52.30 ± 3.34||51.28 ± 3.81||.19|
|Vessel density, DCP flow (%)|
| Whole retina||53.95 ± 5.00||54.14 ± 4.96||53.60 ± 5.12||.62|
| Superior-hemi||54.38 ± 5.15||54.61 ± 5.23||53.96 ± 5.06||.56|
| Inferior-hemi||53.53 ± 5.05||53.68 ± 4.91||53.27 ± 5.34||.71|
| Fovea||38.30 ± 7.61||37.05 ± 7.74||40.53 ± 6.93||.03|
| Parafovea||57.97 ± 3.70||58.37 ± 3.47||57.25 ± 4.04||.16|
| Superior-hemi||58.34 ± 3.60||58.59 ± 3.59||57.91 ± 3.62||.38|
| Inferior-hemi||57.83 ± 3.69||58.14 ± 3.68||57.28 ± 3.69||.28|
| Temporal||58.70 ± 3.61||58.86 ± 3.75||58.41 ± 3.38||.56|
| Superior||57.84 ± 3.98||58.08 ± 3.90||57.39 ± 4.14||.42|
| Nasal||58.76 ± 3.66||59.15 ± 3.25||58.05 ± 4.26||.16|
| Inferior||56.99 ± 4.08||57.37 ± 4.20||56.33 ± 3.82||.24|
| Perifovea||55.72 ± 5.13||55.99 ± 5.05||55.23 ± 5.31||.50|
| Superior-hemi||55.80 ± 5.37||55.98 ± 5.55||55.47 ± 5.10||.66|
| Inferior-hemi||55.30 ± 5.46||55.51 ± 5.32||54.91 ± 5.77||.61|
| Temporal||57.69 ± 4.65||57.69 ± 4.68||57.69 ± 4.68||.99|
| Superior||54.88 ± 5.97||54.89 ± 6.21||54.85 ± 5.63||.97|
| Nasal||55.08 ± 5.78||55.49 ± 5.78||54.35 ± 5.80||.36|
| Inferior||54.58 ± 6.12||54.92 ± 5.83||53.96 ± 6.67||.47|
Comparison of the Radial Peripapillary Capillary Vessel Density Parameters in Different Sections by Gendera
|Parameter||Male + Female (n = 92)||Female (n = 50)||Male (n = 42)||Pb,c|
|Whole image||49.64 ± 2.22||49.84 ± 2.13||49.27 ± 2.36||.24|
|Inside disc||52.89 ± 4.68||53.24 ± 5.07||52.24 ± 3.83||.33|
|Peripapillary||51.33 ± 2.84||51.64 ± 2.67||50.75 ± 3.07||.15|
| Superior-hemi||51.70 ± 3.00||52.12 ± 2.85||50.93 ± 3.15||.07|
| Inferior-hemi||50.5 ± 7.16||49.79 ± 8.53||50.54 ± 3.44||.64|
| Nasal superior||48.44 ± 3.47||48.83 ± 3.23||47.74 ± 3.82||.15|
| Nasal inferior||47.07 ± 4.49||47.26 ± 4.59||46.74 ± 4.34||.60|
| Inferior nasal||50.02 ± 4.57||50.09 ± 4.68||49.89 ± 4.42||.84|
| Inferior temporal||56.04 ± 4.84||57.02 ± 3.84||54.18 ± 5.97||.01|
| Temporal inferior||52.56 ± 5.24||52.11 ± 5.67||53.42 ± 4.29||.26|
| Temporal superior||54.86 ± 3.23||54.93 ± 3.12||54.73 ± 3.48||.79|
| Superior temporal||55.20 ± 4.44||55.93 ± 4.23||53.88 ± 4.57||.03|
| Superior nasal||49.18 ± 4.37||49.54 ± 4.29||48.53 ± 4.51||.29|