Early retinal and choroidal changes in the macula region associated with axial length in myopic children and adolescents based on swept-source OCTA

Purpose: The study aimed to investigate the association between axial length (AL) and early retinal/choroidal structural and hemodynamic changes in the macula of myopic children and adolescents using swept-source optical coherence tomography angiography (ssOCTA).

Methods: This cross-sectional study included 136 eyes from 136 myopic participants aged 4–17 years. The participants underwent a comprehensive ophthalmic examination, including AL measurement and 6×6 mm macular ssOCTA scans. Hemodynamic parameters (vessel density and choroidal vessel/stromal volumes) and thickness metrics across retinal and choroidal layers and Early Treatment of Diabetic Retinopathy Study (ETDRS) subfields were analyzed. The participants were grouped based on AL (<26 mm vs. ≥26 mm). Multivariate linear regression (MLR; adjusted for age and sex) was used to assess correlations between AL and OCTA parameters.

Results: Increased AL was significantly correlated with reduced deep retinal vessel density (DVD) in the majority of macular regions (except for the perifoveal inferior region), as well as decreased choroidal vessel volume (CVV) and choroidal stromal volume (CSV). Superficial retinal vessel density (SVD) and choriocapillaris flow showed no significant correlation with AL. Retinal and choroidal thickness significantly decreased with longer AL in the majority of regions (except for the foveal region of the retina). Regional analysis revealed that the perifoveal nasal area exhibited the greatest reduction in CVV and CSV, while the perifoveal inferior area showed the least reduction in DVD. Foveal retinal thickness also decreased to a lesser extent compared to other regions with AL elongation.

Conclusion: Axial elongation in young individuals with myopia is associated with specific early microvascular and structural alterations that can be detected using ssOCTA. Deep retinal vascular attenuation and choroidal volumetric loss (CVV, CSV) represent the most prominent hemodynamic changes linked to AL, showing regional variations within the macula. These findings highlight early structural and hemodynamic changes associated with myopic progression in pediatric and juvenile populations.

Introduction

Myopia is a common yet complex vision disorder with a rising prevalence, particularly among school-aged children in East Asia, posing significant public health challenges (1). Recent studies have pointed out that the global prevalence of myopia has increased over the past decades, rising from 24.32 to 35.81%. It is projected to reach 39.80% by the year 2050 (2). It is widely acknowledged that high myopia permanently alters ocular structures, leading to a range of eye disorders in adulthood (3). Recent research conducted by Jiang et al. further reported that myopic maculopathy could affect as many as 14.05% of highly myopic adolescents, demonstrating the critical need for early prevention and intervention to hinder disease progression (4, 5).

The high incidence of myopia and the occurrence of myopic retinal changes during childhood and adolescence have drawn considerable attention (6), and the structural changes underlying myopia progression have become a hotspot in research (7). With the advent of advanced technologies, including swept-source optical coherence tomography angiography (ssOCTA), it is now possible to visualize and better understand the structural changes underlying myopia progression. Current evidence from ssOCTA scanning indicates that myopia progression is linked to changes in retinal and choroidal structures, such as reduced choroidal thickness and modified choroidal vascular dynamics (8, 9). However, previous studies have primarily focused on general morphological changes (10), with limited exploration of the specific correlations between axial elongation and detailed hemodynamic and thickness metrics across distinct layers and regions of the retina and choroid, particularly in school-aged children and adolescents (8, 11).

This study aimed to address these issues by investigating the relationship between axial length (AL) and variations in macular retinal and choroidal thickness, as well as blood flow, in children and adolescents. It also sought to identify the specific regions and layers most significantly affected by axial growth. By adjusting for potential confounding variables such as age and sex, this research employed multivariate linear regression to analyze the correlation between axial length and retinal and choroidal parameters. Furthermore, it compared the effect of axial length on different retinal and choroidal regions. The findings help enhance our understanding of early structural and hemodynamic changes in the macula region associated with axial elongation, offering valuable insights into the pathophysiology of myopia progression in children and adolescents.

Participants and methods

Study participants

This cross-sectional, single-center, retrospective study was conducted in Northern Jiangsu People’s Hospital from November 2024 to May 2025. All patients who participated were informed of the purpose of this study before undergoing comprehensive ocular examinations. All patients underwent comprehensive examinations, including the following: (1) Silt lamp examination, (2) scanning laser ophthalmoscopy (SLO), (3) axial length measurement using IOLMaster 500 (Carl Zeiss Meditec AG, Jena, Germany), (4) macular ssOCTA, (5) keratometry analysis, and (6) tropicamide-induced cycloplegic refraction. The exclusion criteria for patients were as follows: (1) Severe fundus diseases, including chorioretinal atrophy associated with high myopia, macular atrophy, lattice peripheral retinal degeneration, primary open-angle glaucoma, and retinal breaks; (2) other ocular diseases, including concomitant strabismus, keratoconus, and keratitis; (3) history of previous ocular surgeries; (4) systematic diseases such as Down syndrome, type 1 diabetes, and hypertension; and (5) ssOCTA scanning quality score of less than 8 out of 10 (Figure 1). All patients were enrolled using their right eye, but when the scan quality of the right eye did not meet the criteria, the patient’s left eye was included for analysis.

Figure 1

Figure 1. Flowchart illustrating the inclusion and exclusion criteria for study participants.

ssOCTA measurements

Measurements using ssOCTA were conducted on 136 participants who met the inclusion criteria. Using the cutting-edge 400 kHz full range OCT scanner (BMizar, TowardPi Technology Co Ltd., Beijing, China), we acquired data regarding all layers of the retina and choroid within a 6*6 mm fovea-centered area. Blood flow metrics included superficial retinal vessel density (SVD), deep retinal vessel density (DVD), full vessel density, choriocapillaris vessel density, choroidal medium and large vessel density [from 31 μm below Bruch’s membrane (BM) to the choroidal–scleral interface (CSI)], choroidal vessel volume (CVV, from 31 μm below BM to the CSI), and choroidal stromal volume (CSV, from 31 μm below BM to the CSI). Thickness data included inner retinal thickness [from the inner limiting membrane (ILM) to the inner plexiform layer (IPL)], outer retinal thickness (from the IPL to BM), full retinal thickness (from the ILM to BM), and choroidal thickness (from the BM to the CSI). Based on the traditional Early Treatment of Diabetic Retinopathy Study (ETDRS) grid (12, 13), the area was divided into the fovea area (diameter = 1 mm), the parafoveal ring (diameter 1 ~ 3 mm), and the perifoveal ring (diameter 3 ~ 6 mm). The parafoveal and perifoveal rings were further divided into four quadrants: superior, inferior, temporal, and nasal (Figure 2). All of the above data were automatically calculated using the BMizar 400 kHz full range OCT scanner, and the algorithms for automatic stratification and calculation have been widely accepted in previous research within this field (14, 15).

Figure 2

Figure 2. Representative ssOCTA images showing the ETDRS grid and all nine subfields. The OCTA plots on the left and in the middle are from the same participant, showing the raw angiography and quantification of retinal vessel density, respectively, with the 6*6 mm ETDRS region marked by white circles. The 6*6 mm ETDRS grid plot on the right shows the nine grids that were analyzed: (1) foveal, (2) parafoveal temporal, (3) parafoveal superior, (4) parafoveal nasal, (5) parafoveal inferior, (6) perifoveal temporal, (7) perifoveal superior, (8) perifoveal nasal, and (9) perifoveal inferior.

Statistical analysis

All data analyses were conducted using R software (version 4.4.2). Data were presented as mean ± SD (standard deviation) that followed a normal distribution and as median (lower quartile, upper quartile) for variables with a non-normal distribution. For normally distributed data, t-tests or one-way ANOVA were employed, whereas for non-normally distributed data, Mann–Whitney U tests or Kruskal–Wallis H tests were applied. The R package CompareGroups (version 4.9.1) was utilized for intergroup comparisons. Multivariate linear regression analyses were performed with the R package stats (version 4.4.0). The non-parametric estimation of b_AL was carried out using the bootstrap method from the R package boot (version 1.3). A p-value of <0.05 was considered statistically significant.

Results

Demographic and clinical statistics of the study participants

Overall, 136 eyes from 136 patients were included in our study (60 male and 76 female individuals). The enrolled study participants were categorized into two groups: one group with an AL ≥ 26 mm and another group with an AL < 26 mm, using 26 mm as the cutoff value. The comparison between these two groups showed significant differences in age and spherical equivalent refraction (SER). The participants in the higher AL group had higher SER and were older (Table 1). Overall, AL showed a significant correlation with SER (Spearman R = −0.85, p < 0.001) (Figure 3). Although a strong correlation between AL and SER was observed, 20 eyes exhibited relatively high axial length values (with AL ≥ 26 mm), despite not being in the HM group.

Table 1

Table 1. Comparison of demographic data, AL, and SER among low, moderate, and high myopia groups.

Figure 3

Figure 3. Scatter plot revealing the correlation between AL and SER in the study participants.

Comparison of ssOCTA hemodynamic data across different AL groups

When comparing retinal and choroidal hemodynamic features between the two groups (AL ≥ 26 mm and AL < 26 mm), three specific parameters showed significant differences, namely deep retinal vessel density (DVD), the luminal volume of the choroidal medium- and large-vessel layers (choroidal vessel volume, CVV), and the stromal volume of the same choroidal medium- and large-vessel layers (choroidal stromal volume, CSV). In contrast, there were no significant differences in superficial retinal vessel density (SVD), choriocapillaris vessel density, or the density of choroidal medium- and large-vessel layers (Table 2).

Table 2

Table 2. Participants were divided into two groups based on an axial length of 26 mm.

Comparison of ssOCTA thickness data across different AL groups

A comparison of thickness between the two groups (AL ≥ 26 mm and AL < 26 mm) revealed only a slight decrease in inner retina thickness in some regions (parafoveal nasal, parafoveal inferior, perifoveal temporal, and perifoveal superior) in the AL ≥ 26 mm group. However, the thickness of almost all regions in the outer retina and choroid was significantly lower in the AL ≥ 26 mm group, except for the fovea region in the outer retina (Table 3).

Table 3

Table 3. Participants were divided into two groups based on an axial length of 26 mm.

Multivariate linear regression of retinal and choroidal vascular metrics

To account for potential confounding factors such as age and sex, a multivariate linear regression (MLR) model was utilized (Table 4). The MLR formula is as follows:

$\text{Vessel metrics}={\mathrm{b}}_{\mathrm{AL}}\times \mathrm{AL}+{\mathrm{b}}_{\mathrm{Age}}\times \mathrm{Age}+{\mathrm{b}}_{\text{Gender}}\times \text{Gender}+{\mathrm{b}}_0$

Table 4

Table 4. Multivariate regression analysis of the influence of AL (all adjusted for age and sex) on different hemodynamic parameters.

In this model, superficial retinal vessel density (SVD) exhibited no significant correlation, while deep retinal vessel density (DVD) demonstrated a significant negative correlation with axial length (AL) across all ETDRS grid areas, except for the perifoveal inferior region. Consistent with the comparison results presented in Table 2, no significant correlation was observed between AL and choriocapillaris vessel density (except in the perifoveal temporal region) or between AL and choroidal medium- and large-vessel density (except in the foveal region). Notably, even after adjusting for potential confounding factors such as age and sex, AL showed a strong negative correlation with choroidal stromal volume (CSV) and choroidal vessel volume (CVV), which contrasted with the findings regarding choroidal vessel density in the MLR analysis.

Multivariate linear regression of retinal and choroidal thickness metrics

A multivariate linear regression (MLR) model was used to adjust for the influence of cofounding factors such as age and sex (Table 5). The MLR formula is as follows:

$\text{Thickness}={\mathrm{b}}_{\mathrm{AL}}\times \mathrm{AL}+{\mathrm{b}}_{\mathrm{Age}}\times \mathrm{Age}+{\mathrm{b}}_{\text{Gender}}\times \text{Gender}+{\mathrm{b}}_0$

Table 5

Table 5. Multivariate regression analysis of the influence of AL (all adjusted for age and sex) on different thickness parameters.

The negative correlation observed between inner and outer retinal thickness and AL reached statistical significance only in some of the ETDRS sections. Not surprisingly, total retinal and choroidal thickness was negatively correlated with AL after adjusting for age and sex, except for retinal thickness in the fovea, which showed no significant correlation.

Comparison of AL’s influence across different ETDRS areas of retinal and choroidal metrics

To compare the influence of AL across different ETDRS areas, the 95% confidence interval (CI) of the partial regression coefficient of AL (b_AL) was estimated using the bootstrap method, and comparisons between different areas were conducted using likelihood ratio tests with FDR adjustments. DVD, CSV, and CVV were selected for analysis because they showed significant associations with AL. The results were presented using a forest plot and a heatmap. We found that, with increasing AL, the perifoveal inferior area showed a significantly smaller decrease in DVD compared to all other regions (Figure 4A). However, the perifoveal nasal area showed substantially greater decreases in CSV and CVV than most of the other regions (fovea, parafoveal temporal, parafoveal nasal, and parafoveal inferior) (Figures 4B,C). A significantly smaller decrease in foveal retinal thickness compared to other regions with increasing AL was also found (Figure 5).

Figure 4

Figure 4. Estimation and comparison of AL’s influence across different ETDRS areas of retinal and choroidal blood flow metrics. Forest plot (showing the estimated value and 95%CI using the bootstrap method) and p-value heatmap comparing the partial regression coefficient for AL with (A) deep retinal vessel density (DVD), (B) choroidal vessel volume (CVV), and (C) choroidal stromal volume (CSV) across the nine subfields. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 5

Figure 5. Estimation and comparison of AL’s influence across different ETDRS areas of retinal and choroidal thickness metrics. Forest plot (showing the estimated value and 95%CI using the bootstrap method) and p-value heatmap comparing the partial regression coefficient for AL with (A) inner retinal thickness, (B) outer retinal thickness, (C) total retinal thickness, and (D) choroidal thickness across the nine subfields. *p < 0.05, **p < 0.01, ***p < 0.001.

Discussion

Research on myopic fundus changes has spanned several decades. In 1970, Curtin et al. first identified five fundus changes related to axial elongation: Chorioretinal atrophy, central pigment spots (Fuchs spots), lacquer cracks, posterior scleral staphyloma, and optic disc abnormalities (16). In 2015, the International META-analysis for Pathologic Myopia Study Group proposed a simplified classification system, categorizing pathological myopia-related macular degeneration into five distinct grades: C0, no myopic retinal degeneration; C1, tigroid fundus; C2, diffuse chorioretinal atrophy; C3, patchy chorioretinal atrophy; and C4, macular atrophy (17). This classification fully revealed the progression of myopic macular degeneration based on fundus photography. Nevertheless, distinct retinal and choroidal changes in the early stages of myopic macular alterations still need further investigation, and ssOCTA has become a valuable tool.

Many studies on retinal and choroidal vascular changes in myopia, based on ssOCTA results have been published, most of which involved participants in adulthood (18–20). Although some exciting discoveries have been made, certain aspects need to be considered when investigating myopic changes in adolescence and childhood. It is widely acknowledged that AL is positively correlated with age in children (21), and sex may potentially influence microvascular metrics (22, 23). Therefore, cofounding factors such as age and sex should be controlled to achieve a convincing result.

In our study, after controlling for the participants’ sex and age using an MLR model, ssOCTA analysis revealed that axial elongation had a more pronounced effect on DVD and choroidal vessel/stromal volume compared to other hemodynamic metrics. This suggests that the microvascular network in the deeper layers of the retina may be more susceptible to the pathophysiological changes associated with axial myopia, which may be attributed to the extension of the retina following AL elongation (24). These findings echo the results obtained by Mu et al., who found that SVD was not associated with axial elongation after adjusting for age and sex, whereas DVD was inversely correlated with axial length (25).

We also found that CSV and CVV were negatively related to AL after controlling for age and sex in the participants aged 4–17 years across all ETDRS sections, and choriocapillaris blood flow remained unaffected by AL elongation. This finding is similar to that of Geng et al., who found a negative relationship between CSV and CVV in myopic individuals aged 4–14 years (26). Moreover, the results support the hypothesis proposed by Jonas et al., who stated that the decrease in choriocapillaris blood flow in previous case–control studies may be due to the inclusion of patients with avascular chorioretinal patchy atrophy (27). Our study further revealed that the perifoveal inferior region showed a stronger decrease in CSV and CVV with increasing AL, highlighting possible regional disparities in choroidal structural changes.

A previous longitudinal study found that distinct retinal layers, such as the ganglion cell layer (GCL), the inner plexiform layer (IPL), and total retinal thickness, showed no significant changes in thickness in myopic adolescents after a 2-year follow-up (28). Nonetheless, we noted that total retinal thickness was negatively correlated with AL, except in the foveal region. This finding is similar to a previous cross-sectional study in young adults (29), suggesting that the possible thinning of the retina in the macular region may begin earlier than expected.

The results also emphasize the value of using advanced imaging techniques such as ssOCTA to elucidate the specific effects of axial elongation on different components of the ocular microvasculature (30). By identifying the areas and layers most affected by axial growth, this study provides insights into potential targets for early intervention strategies aimed at slowing myopia progression in children and adolescents.

This study has a few limitations worth noting. First, due to its cross-sectional design, it is difficult to establish a definitive cause-and-effect relationship. Longitudinal studies are needed to confirm the observed associations and better understand the dynamic changes over time. Furthermore, the hospital-based nature of the study, although adequate for detecting significant differences, may limit the generalizability of the findings to broader populations. Future studies with larger and more diverse cohorts are needed. Finally, the use of a single imaging modality (ssOCTA) may not capture the full spectrum of vascular changes associated with myopia. Combining ssOCTA with other imaging techniques could provide a more comprehensive understanding of structural and hemodynamic alterations.

In conclusion, this study provides a detailed analysis of the relationship between axial length and retinal and choroidal hemodynamic metrics in children and adolescents. The findings indicate that axial elongation is associated with significant changes in specific hemodynamic parameters, particularly deep retinal vessel density and choroidal vessel/stromal volume. These results enhance our understanding of early structural and hemodynamic changes in the macula region associated with axial elongation and offer valuable insights into the pathophysiology of myopia progression in children and adolescents. Future research should focus on longitudinal studies and larger cohorts to further validate these findings and explore their clinical implications.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the Ethics Committee of Northern Jiangsu People’s Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.

Author contributions

YC: Writing – original draft, Supervision, Writing – review & editing, Software, Data curation, Conceptualization, Methodology, Investigation. QG: Writing – original draft, Writing – review & editing. JZ: Writing – original draft, Writing – review & editing. FC: Software, Visualization, Funding acquisition, Data curation, Resources, Project administration, Investigation, Conceptualization, Methodology, Writing – review & editing, Formal analysis, Validation, Supervision.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was generously supported by the Scientific Research Foundation of Northern Jiangsu People’s Hospital (Grant No. SBQN23001), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX24-2345), and the Jiangsu Provincial Research Project of Preventive Medicine (Grant No. Ym2023029).

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Morgan, IG, French, AN, Ashby, RS, Guo, X, Ding, X, He, M, et al. The epidemics of myopia: aetiology and prevention. Prog Retin Eye Res. (2018) 62:134–49. doi: 10.1016/j.preteyeres.2017.09.004,

PubMed Abstract | Crossref Full Text | Google Scholar

2. Liang, J, Pu, Y, Chen, J, Liu, M, Ouyang, B, Jin, Z, et al. Global prevalence, trend and projection of myopia in children and adolescents from 1990 to 2050: a comprehensive systematic review and meta-analysis. Br J Ophthalmol. (2025) 109:362–71. doi: 10.1136/bjo-2024-325427,

PubMed Abstract | Crossref Full Text | Google Scholar

3. Williams, K, and Hammond, C. High myopia and its risks. Community Eye Health. (2019) 32:5–6.

PubMed Abstract | Google Scholar

4. Ohno-Matsui, K. Insights into childhood myopic maculopathy. JAMA Ophthalmol. (2024) 142:186. doi: 10.1001/jamaophthalmol.2023.6490,

PubMed Abstract | Crossref Full Text | Google Scholar

5. Jiang, F, Wang, D, Xiao, O, Guo, X, Yin, Q, Luo, L, et al. Four-year progression of myopic maculopathy in children and adolescents with high myopia. JAMA Ophthalmol. (2024) 142:180. doi: 10.1001/jamaophthalmol.2023.6319,

PubMed Abstract | Crossref Full Text | Google Scholar

6. Zhang, W, Yang, F, Chen, S, and Shi, T. Peripheral and posterior pole retinal changes in highly myopic Chinese children and adolescents: retinal changes in Chinese children and adolescents. BMC Ophthalmol. (2024) 24:65. doi: 10.1186/s12886-024-03328-6,

PubMed Abstract | Crossref Full Text | Google Scholar

7. Kong, K, Liu, X, Fang, Z, Jiang, J, Jiang, J, Wang, D, et al. Axial elongation in nonpathologic high myopia: ocular structural changes and glaucoma diagnostic challenges. Asia Pac J Ophthalmol (Phila). (2024) 13:100123. doi: 10.1016/j.apjo.2024.100123,

PubMed Abstract | Crossref Full Text | Google Scholar

8. Gu, J, Xu, Y, Xiao, D, Wang, Y, Lei, W, Chen, Z, et al. Peripheral superficial retina vascular density and area of radial peripapillary capillaries changes in myopic individuals: a wide-field OCT angiography study. Transl Vis Sci Technol. (2024) 13:21. doi: 10.1167/tvst.13.9.21,

PubMed Abstract | Crossref Full Text | Google Scholar

9. Jiang, Z, Hou, A, Zhang, T, Lai, Y, Huang, L, and Ding, X. Pattern of choroidal thickness in early-onset high myopia. Front Med. (2023) 10:1156259. doi: 10.3389/fmed.2023.1156259,

PubMed Abstract | Crossref Full Text | Google Scholar

10. Zhang, JM, Wu, JF, Chen, JH, Wang, L, Lu, TL, Sun, W, et al. Macular choroidal thickness in children: the Shandong children eye study. Invest Ophthalmol Vis Sci. (2015) 56:7646–52. doi: 10.1167/iovs.15-17137,

PubMed Abstract | Crossref Full Text | Google Scholar

11. Jonas, JB, Spaide, RF, Ostrin, LA, Logan, NS, Flitcroft, I, and Panda-Jonas, S. IMI-nonpathological human ocular tissue changes with axial myopia. Invest Ophthalmol Vis Sci. (2023) 64:5. doi: 10.1167/iovs.64.6.5,

PubMed Abstract | Crossref Full Text | Google Scholar

12. Liu, R, Xuan, M, Wang, D-C, Xiao, O, Guo, X-X, Zhang, J, et al. Using choroidal thickness to detect myopic macular degeneration. Int J Ophthalmol. (2024) 17:317–23. doi: 10.18240/ijo.2024.02.14

Crossref Full Text | Google Scholar

13. Burguera-Giménez, N, Díez-Ajenjo, MA, Burguera, N, Briceno-Lopez, C, and Peris-Martínez, C. Subfoveal and parafoveal choroidal thickening in patients with keratoconus using the ETDRS grid on swept-source OCT. Ophthalmol Ther. (2024) 13:509–27. doi: 10.1007/s40123-023-00858-y,

PubMed Abstract | Crossref Full Text | Google Scholar

14. Zeng, Q, Luo, L, Yao, Y, Tu, S, Yang, Z, and Zhao, M. Three-dimensional choroidal vascularity index in central serous chorioretinopathy using ultra-widefield swept-source optical coherence tomography angiography. Front Med (Lausanne). (2022) 9:967369. doi: 10.3389/fmed.2022.967369,

PubMed Abstract | Crossref Full Text | Google Scholar

15. Zeng, Y, Liu, M, Li, M, Wei, D, Mao, M, Liu, X, et al. Early changes to retinal structure in patients with diabetic retinopathy as determined by ultrawide swept-source optical coherence tomography-angiography. Front Endocrinol (Lausanne). (2023) 14:1143535. doi: 10.3389/fendo.2023.1143535,

PubMed Abstract | Crossref Full Text | Google Scholar

16. Curtin, BJ, and Karlin, DB. Axial length measurements and fundus changes of the myopic eye. I. The posterior fundus. Trans Am Ophthalmol Soc. (1970) 68:312–34.

PubMed Abstract | Google Scholar

17. Ohno-Matsui, K, Kawasaki, R, Jonas, JB, Cheung, CMG, Saw, S-M, Verhoeven, VJM, et al. International photographic classification and grading system for myopic maculopathy. Am J Ophthalmol. (2015) 159:877–883.e7. doi: 10.1016/j.ajo.2015.01.022,

PubMed Abstract | Crossref Full Text | Google Scholar

18. Zhou, F, Yuan, Y, Xu, Y, Huang, Z, Wang, F, Chen, Z, et al. Assessment of choriocapillary flow deficits in myopic children by optical coherence tomography angiography. Sci Rep. (2025) 15:15535. doi: 10.1038/s41598-025-98579-8,

PubMed Abstract | Crossref Full Text | Google Scholar

19. Wang, Q, He, L-B, Li, S, Liu, H-L, and Liu, Y. Evaluating choroidal vascular changes in young adults with high myopia utilizing swept source optical coherence tomography angiography. Photodiagn Photodyn Ther. (2025) 51:104475. doi: 10.1016/j.pdpdt.2025.104475,

PubMed Abstract | Crossref Full Text | Google Scholar

20. Tang, X, Liang, J, Luo, L, Yuan, F, Zhao, K, Zhuo, X, et al. Investigation of choroidal vascular alterations in eyes with myopia using ultrawidefield optical coherence tomography angiography. BMJ Open Ophthalmol. (2024) 9:e001839. doi: 10.1136/bmjophth-2024-001839,

PubMed Abstract | Crossref Full Text | Google Scholar

21. He, X, Sankaridurg, P, Naduvilath, T, Wang, J, Xiong, S, Weng, R, et al. Normative data and percentile curves for axial length and axial length/corneal curvature in Chinese children and adolescents aged 4-18 years. Br J Ophthalmol. (2023) 107:167–75. doi: 10.1136/bjophthalmol-2021-319431,

PubMed Abstract | Crossref Full Text | Google Scholar

22. Benitez-Aguirre, P, Craig, ME, Cass, HG, Sugden, CJ, Jenkins, AJ, Wang, JJ, et al. Sex differences in retinal microvasculature through puberty in type 1 diabetes: are girls at greater risk of diabetic microvascular complications? Invest Ophthalmol Vis Sci. (2014) 56:571–7. doi: 10.1167/iovs.14-15147,

PubMed Abstract | Crossref Full Text | Google Scholar

23. Vujosevic, S, Limoli, C, Piccoli, G, Costanzo, E, Marenzi, E, Torti, E, et al. A gender-based analysis of retinal microvascular alterations in patients with diabetes mellitus using OCT angiography. J Diabetes Complicat. (2024) 38:108852. doi: 10.1016/j.jdiacomp.2024.108852,

PubMed Abstract | Crossref Full Text | Google Scholar

24. Zhang, X, Jiang, J, Kong, K, Li, F, Chen, S, Wang, P, et al. Optic neuropathy in high myopia: Glaucoma or high myopia or both? Prog Retin Eye Res. (2024) 99:101246. doi: 10.1016/j.preteyeres.2024.101246,

PubMed Abstract | Crossref Full Text | Google Scholar

25. Mu, J, Wei, J, Geng, H, Yi, W, Kang, X, Wen, J, et al. Wide-field swept-source optical coherence tomography angiography (SS-OCTA) in the assessment of retinal vessel density and thickness in 4-to 16-year-old myopic children. Photodiagn Photodyn Ther. (2024) 48:104240. doi: 10.1016/j.pdpdt.2024.104240,

PubMed Abstract | Crossref Full Text | Google Scholar

26. Geng, H, Mu, J, Wen, J, Yao, W, Liu, L, Liu, C, et al. Factors affecting choroidal circulation parameters in 4–14-year-old Chinese children measured by SS-OCT/OCTA. Photodiagn Photodyn Ther. (2024) 48:104275. doi: 10.1016/j.pdpdt.2024.104275,

PubMed Abstract | Crossref Full Text | Google Scholar

27. Jonas, JB, Jonas, RA, Bikbov, MM, Wang, YX, and Panda-Jonas, S. Myopia: histology, clinical features, and potential implications for the etiology of axial elongation. Prog Retin Eye Res. (2023) 96:101156. doi: 10.1016/j.preteyeres.2022.101156,

PubMed Abstract | Crossref Full Text | Google Scholar

28. Xu, M, Yu, X, Wan, M, Feng, K, Zhang, J, Shen, M, et al. Two-year longitudinal change in choroidal and retinal thickness in school-aged myopic children: exploratory analysis of clinical trials for myopia progression. Eye Vis (Lond). (2022) 9:5. doi: 10.1186/s40662-022-00276-4,

PubMed Abstract | Crossref Full Text | Google Scholar

29. Wang, X, Chen, Y, Wang, Z, Li, H, He, Q, Rong, H, et al. Assessment of macular structures and vascular characteristics in highly myopic anisometropia using swept-source optical coherence tomography angiography. Front Physiol. (2022) 13:918393. doi: 10.3389/fphys.2022.918393,

PubMed Abstract | Crossref Full Text | Google Scholar

30. Zhang, Y, Wang, D, Lin, F, Song, Y, Chen, Y, Peng, Y, et al. Diagnostic performance of wide-field optical coherence tomography angiography in detecting open-angle glaucoma in high myopia. Acta Ophthalmol. (2024) 102:e168–77. doi: 10.1111/aos.16603,

PubMed Abstract | Crossref Full Text | Google Scholar