Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Superficial capillary plexus vessel density/deep capillary plexus vessel density ratio in healthy eyes

BMC Ophthalmology volume 22, Article number: 482 (2022) Cite this article

Abstract

Background

To identify factors differently affecting the superficial capillary plexus (SCP) and deep capillary plexus (DCP) in healthy eyes using their vessel density (VD) ratio.

Methods

Healthy eyes were enrolled. The ratio between the VD of SCP and DCP (SVD/DVD ratio) was calculated. Pearson correlation analyses were performed to identify the relationships between this ratio and other factors.

Results

The mean SVD and DVD were 36.2 ± 5.7 and 37.7 ± 4.9%, respectively, and the mean SVD/DVD ratio was 0.96 ± 0.15. The SVD was significantly correlated with the best-corrected visual acuity (BCVA) (r = − 0.368, P <  0.001), age (r = − 0.408, P <  0.001), and OCTA quality (r = 0.520, P <  0.001). The DVD was significantly correlated with the BCVA (r = − 0.150, P = 0.008), age (r = − 0.229, P <  0.001), and OCTA quality (r = 0.555, P <  0.001). Among various factors, age (r = − 0.296, P <  0.001), the BCVA (r = − 0.237, P <  0.001), axial length (r = 0.234, P <  0.001), and OCTA quality (r = 0.270, P < 0.001) were significantly correlated with the SVD/DVD ratio.

Conclusions

Age, BCVA, axial length, and OCTA image quality were significantly correlated with the SVD/DVD ratio. Age, the BCVA, and OCTA quality were more strongly correlated with the SCP, and the axial length was more strongly correlated with the DCP.

Peer Review reports

Background

Fluorescein angiography (FA) has been the gold standard for evaluation of the retinal microcirculation and microvasculature. However, FA is invasive and time-consuming, and it is difficult to observe the retinal microvasculature in detail because of dye diffusion. After the development of optical coherence tomography angiography (OCTA), which is non-invasive and enables visualization of retinal microvasculature with high resolution, OCTA has replaced FA in many clinical fields. One of the advantages of OCTA is that the retinal microvasculature can be examined in each retinal layer and can be quantified. OCTA yields various quantitative parameters including vessel density (VD), vessel length density, and the area of the foveal avascular zone (FAZ) of the superficial capillary plexus (from the internal limiting membrane [ILM] to the inner plexiform layer [IPL]; SCP) and the deep capillary plexus (from the outer border of the IPL to the outer border of the outer plexiform layer [OPL]; DCP) with relatively high reliability [1,2,3,4].

Previous studies have reported impairment of retinal microvasculature in various ophthalmic diseases using OCTA. Chen et al. [5] reported that changes in the fractal dimension in the DCP could be an early indicator of microvasculature changes associated with diabetic retinopathy. Another study found that VD of the DCP (DVD) decreased in abnormal multifocal electroretinography patients using hydroxychloroquine for rheumatoid arthritis, but VD in the SCP (SVD) did not [6]. Meanwhile, Chou et al. [7] reported a greater decrease in macular perfusion density of SCP than that of DCP in patients with non-arteritic anterior ischemic optic neuropathy. As such, the SCP and DCP can be differently affected by various conditions.

Therefore, we hypothesized that the factors affecting the normal retinal microvasculature would differ between the SCP and DCP. In this study, We derived the SVD/DVD ratio and identified factors that affect it.

Methods

Subjects

This retrospective, cross-sectional study adhered to the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board of Konyang University Hospital, Daejeon, Korea. We reviewed the charts of patients who visited our retinal clinic for a floater, cataract, unilateral epiretinal membrane, macular hole, or intraocular lens dislocation, with fellow eyes without any ophthalmic disease. The inclusion criteria were age 30 years old or older, spherical equivalent within 6 diopters, no medial opacities that affect fundus imaging, and normal clinical ocular examination findings with no evidence of retinal pathologies. The retrospective review of participants’ records and the waiver of informed consent were approved by the Institutional Review Board/Ethics committee of Konyang University Hospital. We obtained patient information of best-corrected visual acuity (BCVA), intraocular pressure, spherical equivalent, axial length (using an IOL master; Carl Zeiss, Jena, Germany, version 5.02), and parameters of OCT and OCTA. The exclusion criteria consisted of a history of systemic disease including diabetes and hypertension, glaucoma, optic nerve disorder, intraocular pressure ≥ 21 mmHg, axial length ≥ 26 mm, intraocular surgery except for cataract extraction, and a BCVA < 20/40 (logMAR 0.301). If both eyes met the inclusion criteria, one eye was randomly selected.

OCTA imaging protocol

OCTA was performed by a single skilled examiner using a Spectralis OCT2 device (Heidelberg Engineering, Heidelberg, Germany). The Spectralis OCT2 instrument can perform 70,000 A-scan/sec using a light source centered at 870 nm, with axial and transverse resolution of 3.0 and 6 μm in tissue, respectively. En face images of the SCP, defined as the layer from the ILM to the IPL, and the DCP, defined as the layer from the outer border of the IPL to the OPL, were visualized automatically by segmenting two separate slabs defined by arbitrary segmentation lines, which are created by the device software. In this study, a full area of 6.0 × 4.5 mm OCTA scans centered on the fovea was acquired and analyzed. The VD was calculated as the percentage area occupied by blood vessels, with the blood vessels being defined as pixels having decorrelation values above the threshold level using ImageJ software (National Institutes of Health, Bethesda, MD, USA )[8, 9]. After setting images with 8-bit type, the adjusted threshold tool was applied with default settings, and the dark background option was selected as a previous study [10]. This tool automatically sets the lower and upper threshold values (arbitrarily chosen as 110 and 255, respectively, for every image) and segmented grayscale images into features of interest and background (Fig. 1). The Littman and Bennett formulas were used to correct the magnification effect and to calculate true image siz e[11, 12]. In short, the relationship between the measured OCTA image diameter (Dm) and the true diameter of the fundus (Dt) was computed using the equation: Dt = p × q × Dm; where p × q was the overall image magnification factor, p was the magnification factor of the imaging system and q was that of the eye. Factor q was determined from the Bennett formula: q = 0.01306 × (axial length – 1.82), where 1.82 is a constant related to the distance between the corneal apex and the second principal plane. Factor p was computed from the Bennett formula if the axial length at which Dt = Dm is known [13]. For the Heidelberg systems used, the value of the magnification factor (p) was 3.39, given a nominal axial length of 24.385 mm. The OCTA quality is expressed in dB and ranges from 0 to 40. Any image exhibiting fixation loss, segmentation errors, motion artifacts, or the value of OCTA quality < 25 dB was excluded.

Fig. 1
figure 1

Original optical coherence tomography angiography images of the superficial capillary plexus (A) and deep capillary plexus (B), and images after conversion by ImageJ [(C) and (D), respectively]

Full size image

Statistical analysis

Mean and standard deviation values were calculated for continuous variables, and frequency and percentage were calculated for categorical variables. All statistical analyses were performed using SPSS statistical software (version 18.0; IBM Corp., Armonk, NY, USA). Pearson correlation analyses were performed to identify the relationship between the SVD/DVD ratio and variable factors.

Results

Demographics and the SVD and the DVD values

A total of 222 eyes were enrolled. The demographic characteristics including age, sex, BCVA, axial length, or central macular thickness are listed in Table 1.

Table 1 Demographics and characteristics of participants
Full size table

The mean SVD was 36.2 ± 5.7%, the mean DVD was 37.7 ± 4.9%, and the SVD/DVD ratio was 0.96 ± 0.15 (Table 2).

Table 2 Optical coherence tomography angiography parameters of participants
Full size table

Correlations between OCTA parameters and various factors

The SVD was negatively correlated with the BCVA (r = − 0.368, P < 0.001) and age (r = − 0.408, P < 0.001), and positively correlated with OCTA quality (r = 0.520, P < 0.001). The axial length was not significantly associated with the SVD (r = − 0.227, P = 0.374). The DVD was negatively correlated with BCVA (r = − 0.150, P = 0.008) and age (r = − 0.299, P < 0.001), positively correlated with OCTA quality (r = 0.555, P < 0.001). The axial length was significantly correlated with the DVD, which was different from the SVD (r = − 0.307, P = 0.014).

Among various factors, age (P < 0.001) and the BCVA (P < 0.001) were negatively correlated, and the axial length (P < 0.001) and OCTA quality (P < 0.001) were positively correlated with the SVD/DVD ratio (Table 3 and Fig. 2).

Table 3 Correlations between the SVD/DVD ratio and other factors
Full size table
Fig. 2
figure 2

Scatter plots showing a significant correlation between the SVD/DVD ratio and age (P < 0.001), the BCVA (P < 0.001), axial length (P = 0.002), and OCTA quality (P < 0.001)

Full size image

Discussion

In an OCTA image, the SCP appears as a defined silhouette morphology with a linear and continuous white shape against a black background, which is lying in the retinal nerve fiber layer (RNFL) and the ganglion cell layer (GCL). The DCP is shown as a regular distribution around the FAZ with many complex, tiny radial and horizontal interconnections lying in the boundary plane between the inner nuclear layer (INL) and the OPL [14]. These differences in SCP and DCP locations, sizes, and morphologies suggest that various factors might affect them differently [9]. We tried to analyze this using the SVD/DVD ratio in normal eyes and found that age, the BCVA, the axial length, and OCTA quality were significantly correlated with the SVD/DVD ratio. However, since the SVD and DVD values are different for each OCTA device, different OCTA devices may show different SVD/DVD ratios from our study, which would give somewhat different results from ours statistically [15, 16]. However, the trend is expected to remain the same and we believe that our findings would be helpful for clinical situations and research using OCTA.

Previous studies reported a retinal microvascular decrease in eyes with high myopia, which would result from the elongation of eyeballs [17,18,19]. We found that the axial length was positively correlated with the SVD/DVD ratio, which could mean that the longer the axial length, the greater the DVD reduction than the SVD reduction. Actually, the axial length was significantly correlated with only the DVD, not the SVD in our study. You et al. [9] reported that longer axial length was significantly associated with the lower DVD, not with the lower SVD in their multivariate analyses, which is consistent with our study. This result would be associated with a previous study about the retinal layer thickness of high myopia. Kim et al. [20] reported that in high myopia, both the inner and outer rings of the ETDRS grid were thinned in the INL (where the DCP is located). However, only the outer ring was thinned in the inner retinal layer including the GCL and IPL (where the SCP is located), indicating that the range of the thinned INL was wider than that of the thinned inner retinal layer. The density of the smaller vessels in the DCP is greater than that in the SCP, and these smaller vessels may be more sensitive to elongation change, potentially leading to a greater decrease of the DVD than SVD according to increasing axial length [14, 21]. However, this result associated with axial length would contain a limitation that we excluded the eyes with axial length over 26.0 mm. Further studies including more range of axial length including ≥26.0 mm are needed to confirm this hypothesis.

When analyzing OCTA images, OCTA quality is crucial, which ranges from 0 (no signal) to 40 dB (excellent quality) and is considered good if the value is over 25 dB. Similar concepts are signal strength or signal strength index in other devices. Previous studies found that these values affected the measurement of VD and its reliability [1, 2, 9, 22,23,24]. You et al. [9] reported that a lower SVD and DVD were significantly associated with a lower signal strength index, and it was the strongest impact on the measured retinal VD. Additionally, even if the quality value is relatively high so the reliability of the test is good, such value can still affect the OCTA parameters. Lim et al. [25] reported that as the signal strength increased from 7 to 10, the OCTA parameters including VD and perfusion density increased. Our study also found that the SVD/DVD ratio was positively correlated with OCTA quality in images with over 25 dB, indicating that the SVD is more directly affected by OCTA quality than the DVD. Although the exact mechanism is unclear, OCTA quality should be considered when comparing retinal VDs, especially of SCP.

Yu et al. [22] found that the parafoveal flow index and vessel area density decrease with increasing age at a rate of 0.6 and 0.4% per year. Jo et al. [8] also reported that age substantially affected VD in most of the peripapillary and macular areas. In our study, age was negatively correlated with SVD and DVD, which is consistent with previous studies. Additionally, the SVD/DVD ratio was significantly correlated with age. This would result from different locations of the SCP and DCP. The thickness of the inner retina including the RNFL, GCL, and IPL, which locates SCP, is known to decrease with increasing age. Previous studies reported a decrease in the RNFL and GC-IPL with increasing age not only in diseased eyes but also in healthy eyes [26,27,28,29,30,31]. Additionally, the close relationship between the inner retinal layer thickness and the SVD has been known through many studies [32,33,34,35]. Therefore, the SVD may interact with a thinning inner retina over time and decrease along with them. Whereas, the DCP lies on the INL and its thickness is relatively less affected by age. Therefore, the SCP would be more sensitive to VD changes with aging than the DCP.

You et al. [9] reported that lower SVD and DVD were significantly associated with worse BCVA in a normal population in their univariate linear regression analysis. Our study showed a significant correlation between the BCVA and both the SVD and DVD in healthy eyes, which is consistent with a previous study. We also found that the SVD/DVD ratio was negatively correlated with the BCVA. The SVD located in the inner retina, which could be sensitive to ischemia associated with the reduction in macular perfusion by the aging effect and subsequently contributed to the photoreceptor cell damage and impaired BCVA, seemed to be correlated with BCVA more directly than the DVD in healthy eyes [8, 9, 22]. However, since some eyes with relatively poor visual acuity were included due to low BCVA criteria in the study, we could not totally exclude the possibility that a few eyes would have contained ophthalmic disease potentially that was not discovered by the examinations performed at that time. Further studies are needed to confirm this result.

Our study has several limitations. First, the retrospective nature of the work inevitably introduces some selection bias. Second, since eyes with axial length ≥ 26.0 mm were excluded, additional studies including high myopia are needed to more accurately identify the relationship between axial length and the OCTA parameters as we mentioned above. Third, the OCTA measurements were not performed at the same period of the day, which may cause diurnal variation. However, a previous study reported that the macular VD showed no significant diurnal variation, unlike the peripapillary VD [36]. So diurnal variation would not have a decisive effect on the results of our study. Fourth, we could not analyze the patient’s body mass index or smoking status, which could also affect macular VD, because of lacking relevant information on the chart [37, 38]. The strength of this study was that we included a relatively large number of patients from a wide range of age groups, and enrolled OCTA images with OCTA quality ≥25 dB, allowing accurate analyses. Additionally, this is the first study to identify different impacts on the SCP and DCP by various factors via SVD/DVD ratio.

Conclusions

We investigated through the SVD/DVD ratio that various factors can affect SCP and DCP differently in healthy eyes and found that age, BCVA, axial length, and OCTA quality of OCTA images were significantly correlated with the SVD/DVD ratio. From these results, we were able to infer that age, BCVA, and OCTA quality were more correlated with the SCP, while the axial length was more correlated with the DCP. Physicians should consider these results when interpreting OCTA images. Our results may also facilitate future OCTA analyses of retinal microvasculature according to the retinal layer in eyes with various diseases.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

FA:

Fluorescein angiography

OCTA:

Optical coherence tomography angiography

VD:

Vessel density

FAZ:

Foveal avascular zone

ILM:

Internal limiting membrane

IPL:

Inner plexiform layer

SCP:

Superficial capillary plexus

OPL:

Outer plexiform layer

DCP:

Deep capillary plexus

DVD:

Vessel density of the deep capillary plexus

SVD:

Vessel density of superficial capillary plexus

BCVA:

Best-corrected visual acuity

RNFL:

Retinal nerve fiber layer

GCL:

Ganglion cell layer

INL:

Inner nuclear layer

References

  1. Lee MW, Nam KY, Lim HB, Koo HM, Shin YI, Kim JY. Long-term repeatability of optical coherence tomography angiography parameters in healthy eyes. Acta Ophthalmol. 2020;98(1):e36–42.

    Article  Google Scholar 

  2. Lee M-W, Kim K-M, Lim H-B, Jo Y-J, Kim J-Y. Repeatability of vessel density measurements using optical coherence tomography angiography in retinal diseases. Br J Ophthalmol. 2019;103(5):704–10.

    Article  Google Scholar 

  3. 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 ophthalmology. 2017;135(10):1092–8.

    Article  Google Scholar 

  4. You QS, Freeman WR, Weinreb RN, et al. Reproducibility of vessel density measurement with optical coherence tomography angiography in eyes with and without retinopathy Retina (Philadelphia, Pa.) 2017;37(8):1475.

  5. Chen Q, Ma Q, Wu C, et al. Macular vascular fractal dimension in the deep capillary layer as an early indicator of microvascular loss for retinopathy in type 2 diabetic patients. Invest Ophthalmol Vis Sci. 2017;58(9):3785–94.

    Article  Google Scholar 

  6. Akhlaghi M, Kianersi F, Radmehr H, Dehghani A, Beni AN, Noorshargh P. Evaluation of optical coherence tomography angiography parameters in patients treated with hydroxychloroquine. BMC Ophthalmol. 2021;21(1):1–8.

    Article  Google Scholar 

  7. Chou Y, Zhang B, Ma J, Zhong Y. Microvascular alterations detected by optical coherence tomography angiography in non-arteritic anterior ischaemic optic neuropathy: a meta-analysis. Acta Ophthalmologica doi: https://doi.org/10.1111/aos.14930 [published Online First: Epub Date]|.

  8. Jo YH, Sung KR, Shin JW. Effects of age on peripapillary and macular vessel density determined using optical coherence tomography angiography in healthy eyes. Invest Ophthalmol Vis Sci. 2019;60(10):3492–8.

    Article  Google Scholar 

  9. You QS, Chan JC, Ng AL, et al. Macular vessel density measured with optical coherence tomography angiography and its associations in a large population-based study. Invest Ophthalmol Vis Sci. 2019;60(14):4830–7.

    Article  Google Scholar 

  10. Kim JT, Jun JH, Lee SC, Lee MW. Retinal microvasculature and choriocapillaris impairments according to the stage of dry age-related macular degeneration. Clin Exp Ophthalmol. 2022.

  11. Bennett AG, Rudnicka AR, Edgar DF. Improvements on Littmann's method of determining the size of retinal features by fundus photography. Graefes Arch Clin Exp Ophthalmol. 1994;232(6):361–7.

    Article  CAS  Google Scholar 

  12. Sampson DM, Gong P, An D, et al. Axial length variation impacts on superficial retinal vessel density and foveal avascular zone area measurements using optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2017;58(7):3065–72.

    Article  Google Scholar 

  13. Demir P, Hovsepian N, Pagels P, Petersson V, Baskaran K, Macedo AF. All retinas are not created equal: fovea-to-macula thickness ratio and foveal microvasculature in healthy young children. Ophthalmic Physiol Opt. 2022;42(3):644–52.

    Article  Google Scholar 

  14. Savastano MC, Lumbroso B, Rispoli M. In vivo characterization of retinal vascularization morphology using optical coherence tomography angiography. Retina. 2015;35(11):2196–203.

    Article  Google Scholar 

  15. Munk MR, Giannakaki-Zimmermann H, Berger L, et al. OCT-angiography: a qualitative and quantitative comparison of 4 OCT-A devices. PLoS One. 2017;12(5):e0177059.

    Article  Google Scholar 

  16. Lu Y, Wang JC, Cui Y, et al. A quantitative comparison of four optical coherence tomography angiography devices in healthy eyes. Graefes Arch Clin Exp Ophthalmol. 2021;259(6):1493–501.

    Article  Google Scholar 

  17. Li M, Yang Y, Jiang H, et al. Retinal microvascular network and microcirculation assessments in high myopia. Am J Ophthalmol. 2017;174:56–67.

    Article  Google Scholar 

  18. Shi Y, Ye L, Chen Q, et al. Macular Vessel Density Changes in Young Adults With High Myopia: A Longitudinal Study. Frontiers in Medicine 2021;8(869) doi: https://doi.org/10.3389/fmed.2021.648644. [published Online First: Epub Date]|.

  19. Yaprak AC, Yaprak L. Retinal microvasculature and optic disc alterations in non-pathological high myopia with optical coherence tomography angiography. Graefes Arch Clin Exp Ophthalmol. 2021:1–7.

  20. Kim TY, Lee MW, Baek SK, Lee YH. Comparison of retinal layer thicknesses of highly myopic eyes and Normal eyes. Kor J Ophthalmol. 2020;34(6):469.

    Article  Google Scholar 

  21. McLenachan S, Magno AL, Ramos D, et al. Angiography reveals novel features of the retinal vasculature in healthy and diabetic mice. Exp Eye Res. 2015;138:6–21.

    Article  CAS  Google Scholar 

  22. Yu J, Jiang C, Wang X, et al. Macular perfusion in healthy Chinese: an optical coherence tomography angiogram study. Invest Ophthalmol Vis Sci. 2015;56(5):3212–7.

    Article  Google Scholar 

  23. Lim HB, Kim YW, Nam KY, Ryu CK, Jo YJ, Kim JY. Signal strength as an important factor in the analysis of peripapillary microvascular density using optical coherence tomography angiography. Sci Rep. 2019;9(1):1–8.

    Article  Google Scholar 

  24. Lee YM, Lee MW, Song YY, Baek SK, Lee YH. Repeatability of optical coherence tomography angiography measurements in patients with retinal vein occlusion. Kor J Ophthalmol. 2021;35(2):159.

    Article  Google Scholar 

  25. Lim HB, Kim YW, Kim JM, Jo YJ, Kim JY. The importance of signal strength in quantitative assessment of retinal vessel density using optical coherence tomography angiography. Sci Rep. 2018;8(1):1–8.

    Article  Google Scholar 

  26. Lee WH, Lee MW, Lim HB, Kim KM, Shin YI, Kim JY. Longitudinal changes in the thickness of the ganglion cell–inner plexiform layer in patients with hypertension: a 4-year prospective observational study. Acta Ophthalmol. 2020;98(4):e479–e86.

    Article  Google Scholar 

  27. Lee M-W, Lee W-H, Park G-S, Lim H-B, Kim J-Y. Longitudinal changes in the peripapillary retinal nerve fiber layer thickness in hypertension: 4-year prospective observational study. Invest Ophthalmol Vis Sci. 2019;60(12):3914–9.

    Article  Google Scholar 

  28. Lee M-W, Kim J-m, Shin Y-I, Jo Y-J, Kim J-Y. Longitudinal changes in peripapillary retinal nerve fiber layer thickness in high myopia: a prospective, observational study. Ophthalmology. 2019;126(4):522–8.

    Article  Google Scholar 

  29. Lee MW, Nam KY, Park HJ, Lim H-B, Kim J-Y. Longitudinal changes in the ganglion cell-inner plexiform layer thickness in high myopia: a prospective observational study. Br J Ophthalmol. 2020;104(5):604–9.

    Article  Google Scholar 

  30. Lim HB, Shin YI, Lee MW, Park GS, Kim JY. Longitudinal changes in the peripapillary retinal nerve fiber layer thickness of patients with type 2 diabetes. JAMA Ophthalmol. 2019;137(10):1125–32.

    Article  Google Scholar 

  31. Lim HB, Shin YI, Lee MW, Koo H, Lee WH, Kim JY. Ganglion Cell–Inner Plexiform Layer Damage in Diabetic Patients: 3-Year Prospective, Observational Study, Longitudinal. Sci Rep. 2020;10(1):1–9.

    Google Scholar 

  32. Lee M-W, Lee W-H, Ryu C-K, Lee Y-M, Lee Y-H, Kim J-Y. Peripapillary retinal nerve Fiber layer and microvasculature in prolonged type 2 diabetes patients without clinical diabetic retinopathy. Invest Ophthalmol Vis Sci. 2021;62(2):9–9.

    Article  CAS  Google Scholar 

  33. Vujosevic S, Muraca A, Gatti V, et al. Peripapillary microvascular and neural changes in diabetes mellitus: an OCT-angiography study. Invest Ophthalmol Vis Sci. 2018;59(12):5074–81.

    Article  Google Scholar 

  34. Lee M-W, Lee W-H, Ryu C-K, et al. Effects of prolonged type 2 diabetes on the inner retinal layer and macular microvasculature: an optical coherence tomography angiography study. J Clin Med. 2020;9(6):1849.

    Article  CAS  Google Scholar 

  35. Lim HB, Lee MW, Park JH, Kim K, Jo YJ, Kim JY. Changes in ganglion cell–inner plexiform layer thickness and retinal microvasculature in hypertension: An optical coherence tomography angiography study. Am J Ophthalmol. 2019;199:167–76.

    Article  Google Scholar 

  36. Wu J-H, Penteado RC, Moghimi S, Zangwill LM, Proudfoot JA, Weinreb RN. Diurnal variation of retinal vessel density in healthy human eyes. J Glaucoma. 2021;30(9):820–6.

    Article  Google Scholar 

  37. Kurtul BE, Çakmak Aİ, Elbeyli A, Karaaslan A, El Ç. Association of childhood obesity with retinal microvasculature and corneal endothelial cell morphology. J Pediatr Endocrinol Metab. 2021;34(2):171–6.

    Article  Google Scholar 

  38. Dogan M, Akdogan M, Gulyesil FF, Sabaner MC, Gobeka HH. Cigarette smoking reduces deep retinal vascular density. Clin Exp Optom. 2020;103(6):838–42.

    Article  Google Scholar 

Download references

Acknowledgments

None.

Funding

None.

Author information

Author notes

  1. MinWoo Lee and Jung-Yeul Kim contributed equally as corresponding authors.

Authors and Affiliations

  1. Department of Ophthalmology, Chungnam National University Sejong Hospital, Daejeon, Republic of Korea

    Ki-Yup Nam

  2. Department of Ophthalmology, Konyang University College of Medicine, #1643 Gwanjeo-dong, Seo-gu, Daejeon, South Korea

    Min-Woo Lee & Kook-Hyung Lee

  3. Department of Ophthalmology, Chungnam National University College of Medicine, #640 Daesa-dong, Jung-gu, Daejeon, 301-721, South Korea

    Jung-Yeul Kim

  4. 1.0 Eye clinic, Daejeon, Republic of Korea

    Jung-Yeul Kim

Authors
  1. Ki-Yup Nam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Min-Woo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kook-Hyung Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jung-Yeul Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Design and conduct of the study (M.W.L., J.Y.K.); Collection of data (M.W.L., K.H.L., J.Y.K.); Analysis and interpretation of data (M.W.L., K.Y.N., K.H.L., J.Y.K.); Writing the article (M.W.L., K.Y.N., J.Y.K.); Critical revision of the article (M.W.L., K.Y.N., K.H.L., J.Y.K.); Final approval of the article (M.W.L., K.Y.N., K.H.L., J.Y.K.); Min-Woo Lee and Jung-Yeul Kim contributed equally as corresponding authors. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Min-Woo Lee or Jung-Yeul Kim.

Ethics declarations

Ethics approval and consent to participate

This study adhered to the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board of Konyang University Hospital, Daejeon, Korea. The retrospective review of participants’ records and the waiver of informed consent were approved by the Institutional Review Board/Ethics committee of Konyang University Hospital.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

MinWoo Lee and Jung-Yeul Kim contributed equally as corresponding authors.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nam, KY., Lee, MW., Lee, KH. et al. Superficial capillary plexus vessel density/deep capillary plexus vessel density ratio in healthy eyes. BMC Ophthalmol 22, 482 (2022). https://doi.org/10.1186/s12886-022-02673-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12886-022-02673-8

Keywords

BMC Ophthalmology

ISSN: 1471-2415

Contact us