Correlation between choroidal thickness and the degree of myopia

Abstract

BACKGROUND:

Myopia is a frequent visual problem, and the relationship between choroidal thickness (CT) and the degree of myopia has been a hot topic in myopia research.

OBJECTIVE:

This work aimed to explore the correlation between CT and the degree of myopia, providing a reference for diagnosing and treating myopia.

METHODS:

A cross-sectional study was conducted from September 2021 to December 2022, collecting data from 95 myopic patients aged between 18 and 50 years in the outpatient department. All subjects’ CT in the macular center (MC), spherical equivalent (SE), and other ocular parameters were measured. Furthermore, the Pearson correlation coefficient (PCC) analyzed relationships between CT and various factors.

RESULTS:

The choroid was thickest in the MC and gradually became thinner towards the periphery, with the thinnest region located nasally in the healthy group. In the mild, moderate, and severe myopia groups, the choroid was thickest at 1,000 $\mu$ m temporal to the fovea, becoming thinner towards the periphery, with the thinnest region located nasally. The MC’s CT was correlated with a family history of myopia, SE, axial length (AL), and intraocular pressure (IOP). Meanwhile, there was a negative linear relationship between AL and CT in the MC (standard coefficient (SC) of $-$ 0.596, $P$ -value of 0.000, tolerance of 0.217, and variance inflation factor (VIF) of 4.467), and a positive linear correlation between SE and CT in the MC (SC of 0.205, $P$ -value of 0.013, tolerance of 0.257, and VIF of 3.792).

CONCLUSION:

This work provided clues for further understanding of the pathogenesis of myopic eyes and served as a scientific basis for early screening and treatment of myopia. Additionally, investigating the correlation between myopia and CT can also yield a reference for developing personalized myopia management strategies, which will help slow down myopia’s progression and prevent related complications.

Keywords

Choroidal thickness in the macular center myopia spherical equivalent axial length linear correlation

1. Introduction

Myopia, also known as nearsightedness or short-sightedness, is a frequent visual problem characterized by blurred or unclear vision of distant objects. It is one of the widely prevalent refractive errors worldwide and has a vital impact on patients’ daily lives and work. Myopia that is left untreated can cause problems daily, eye strain, poor academic performance, affect social relationships, raise the risk of accidents, and get worse with time. Thus, it is essential to get help right away. The development of myopia is closely associated with the biological characteristics of the eyeball, including increased axial length (AL) and abnormalities in the refractive power of the lens [1, 2]. Lens anomalies can significantly impact myopia since they raise the risk of problems, including glaucoma and retinal detachment, and can result in blurry vision at a distance. The outcome of refractive surgery, such as LASIK or PRK, depends on several variables, including corneal thickness, refractive error stability, and other ocular abnormalities, especially lens-related ones. The eye’s axial length elongates, altering the flow of light and leading to refractive defects such as myopia, focusing alterations, and image formation. Vision becomes blurry as axial length rises because the light’s focus point moves.

The etiology of myopia is multifactorial, involving genetic factors, environmental factors, and behavioral habits. Environmental variables modulate genetic predispositions, which in turn contribute significantly to the development of myopia. Myopia risk is influenced by several factors, including extended close employment, decreased outside exposure, poor physical activity, high socioeconomic position, urbanization, and parental behaviors. Genetic factors play a significant role in the occurrence of myopia, as individuals with parents or close relatives affected by myopia have an increased risk of developing myopia themselves. Environmental factors, such as prolonged work, lack of outdoor activities, and excessive use of electronic screens, are also associated with the development of myopia [3, 4].

Also, poor visual habits and practices, such as prolonged reading at close distances and improper eye care, may increase myopia risk. The treatment challenges of myopia primarily stem from its complex etiology, progressive nature, and individual variations in treatment outcomes [5, 6]. Clinical professionals consider long-term results, safety, and efficacy while creating treatment regimens for myopia. They take into account things like the patient’s age, lifestyle, visual requirements, and the degree and course of their myopia. Individual differences impact the choices made by professionals for the treatment of myopia. They evaluate risk factors, customize therapy, and track results. For effective treatment, regular patient contact and education are essential. Although modern medicine and optometry have provided various treatment methods, including glasses, contact lenses, and refractive surgery, controlling and reversing myopia progression still poses specific challenges [7]. Particularly in the pediatric and adolescent populations, the rapid progression of myopia and the development of high myopia can lead to a range of eye health issues, such as retinal detachment, macular degeneration, and early cataracts, thereby increasing the urgency and complexity of treatment [8, 9]. Genetic predispositions, including aberrant development patterns, gene-environment interactions, and anatomical alterations in the eye, can all contribute to myopia. Susceptibility is also influenced by hereditability and family history; lengthy near-work activities, little outside exposure, and demands from school all exacerbate the problem.

Recent research has indicated that choroidal thickness (CT) may be essential in myopia development [10]. The function of photoreceptor cells and vision are significantly impacted by variations in choroidal thickness, which also impacts retinal metabolism. Oxidative stress and damage might result from retinal metabolism being compromised by insufficient choroidal blood flow. The stability of choroidal thickness is affected by several factors, such as daily fluctuation, ocular hemodynamics, neurovascular coupling, autoregulation of blood flow, and structural integrity. Although changes in the choroidal structure might impact stability, thickness is maintained by stable intraocular pressure and ocular perfusion pressure. The macular center (MC) is one of the human retina’s most sensitive and precise regions, playing a crucial role in visual perception and detail discrimination. The macular center (MC), with its high cone density, little signal convergence, Müller cells, and specialized vascular supply, is essential for central vision, visual acuity, and detail discrimination. These properties allow for crisp focus, color discrimination, and acceptable detail identification. Variations in choroidal thickness have been found to affect parameters from optical coherence tomography (OCT), retinal disorders, and retinal metabolism. Thicker choroids may impact retinal function as they may lessen the supply of nutrients and oxygen to the outer retina. The MC encompasses the CT vasculature, which provides the retina with sufficient oxygen and nutrients to maintain normal visual functioning [11, 12]. Greater vascular density and blood flow, optimal oxygen and nutrient supply, improved visual function, and defense against hypoxic stress are all made possible by thicker choroidal thickness in the macular center, which promotes retinal health. CT is a layer of tissue in the eyeball’s posterior part. Under normal circumstances, its thickness remains relatively stable, closely related to the normal functioning of the retina.

However, myopic patients may exhibit specific structural and functional changes in CT. Previous studies have shown [13, 14] that there are significant differences in CT among myopic patients. Some studies have suggested [15, 16] that CT thickness is relatively thin in myopic patients, particularly in the posterior pole region. These CT changes may be associated with the development and progression of myopia. Furthermore, some studies have also found [17, 18] a correlation between myopia and CT, indicating that the more severe the myopia, the thinner the CT may be. Therefore, changes in CT may be related to visual impairment and the development of ocular diseases. Variations in choroidal thickness (CT) are associated with ocular illnesses such as AMD, myopia, and visual impairment. Choroid thinning in myopia and subfoveal thinning in AMD can disrupt retinal blood flow and result in blindness. Alterations in choroidal vascularity also reveal visual results and the course of the illness.

Some studies have suggested [19] a specific correlation between CT in the MC and the eye’s optical properties and structural parameters. Firstly, research has found [20, 21] a negative correlation between CT in the MC and spherical equivalent (SE). SE is an indicator used to describe the eye’s refractive status, taking into account the degree of myopia, hyperopia, and astigmatism. SE provides a comprehensive measurement by comparing a spherical lens’s optical effect with the eye’s refractive state. In clinical practice, spherical equivalents are essential for controlling refractive errors, streamlining representation, directing treatment choices, and assessing visual acuity. They support the selection of appropriate optical adjustments, tracking of alterations, and forecasting surgical results. Positive values indicate hyperopia, while negative values indicate myopia. SE can help doctors and researchers assess the eye’s refractive status and understand myopia’s degree and changes. Higher SE values (indicating higher myopia degrees) are often associated with a decrease in CT in the MC, which may be related to the higher metabolic demand and altered blood flow in the macular region of myopic patients. Secondly, a specific relationship exists between CT in the MC and AL [22]. AL refers to the length of the anterior-posterior axis of the eyes, from the front surface of the cornea to the back surface of the retina. AL is an essential factor in myopia development, with longer ALs often associated with higher degrees of myopia. The increase in AL causes elongation of the anterior-posterior axis of the eyes, resulting in the image focusing in front of the retina instead of precisely on the retina, leading to myopia. Longer ALs are often accompanied by a decrease in CT in the MC, possibly due to stretching and deformation caused by the elongation of the AL, resulting in sparse and thinning of the CT in the MC vasculature [23].

The axial length, age, ethnicity, and degree of myopia all affect the choroidal thickness of myopic individuals. Choroids thin out because of higher myopia; further thinning is caused by advancing age and longer axial lengths. Lower choroids are common in East Asian people. In addition, some studies have also found [24, 25] a correlation between intraocular pressure (IOP) and CT in the MC. IOP refers to the pressure inside the eye, determined by the balance between the production and outflow of aqueous humor. IOP is crucial for maintaining the stability of standard eye shape and eye structure. High IOP is considered a significant risk factor for glaucoma, while low IOP may be associated with other ocular diseases.

Higher IOP is often accompanied by a decrease in CT in the MC, possibly due to the influence of IOP on CT vasculature perfusion and macular region metabolism. Although there are still some controversies and uncertainties regarding the relationship between myopia and CT, research in this field is rapidly increasing. P Sathyaprakash, Poovendran Alagarsundaram and Mohanarangan Veerapperumal Devarajan et al., have analyzed a Licenced Medical Practitioner-Centric Heterogeneous Network Powered Efficient e-Healthcare Risk Prediction for Health Big Data achieves a comprehensive prediction analysis accuracy range of 73.98% by improving execution time from 29.95% to 36.05%, monogenic score to 19%, density accuracy range to 39%, and prediction accuracy to 45.9% [26]. Understanding the association between myopia and CT can provide important clues for a deeper understanding of the mechanisms of myopia development, early diagnosis, and treatment.

2. Materials and methods

2.1 Research objects

A cross-sectional study was conducted in this work, collecting data from patients who visited the Eye and Optometry Center in the local area for outpatient visits and physical examinations from September 2021 to December 2022. Ninety-five cases (190 eyes) were enrolled and aged 18 to 50 (28.57 $\pm$ 3.63 years old on average). Based on the criteria for enrollment, 92 cases (184 eyes) were ultimately designated as the study population (with 46 eyes in each group). Participants were rolled into four groups based on the degree of SE: the healthy group (23 cases, 46 eyes), low myopia group (23 cases, 46 eyes), moderate myopia group (23 cases, 46 eyes), and high myopia group (23 cases, 46 eyes).

The criteria for enrolling the participating objects were as follows: ⟀ age within the range of 18 to 50 years; ⟁ classification based on SE values (SE $=$ spherical lens $+$ 1/2 column lens): healthy group (SE $>-$ 0.5 D), low myopia group ( $-$ 0.5 D $\leqslant$ SE $<$ 3.0 D), moderate myopia group ( $-$ 3.0 D $<$ SE $<$ 6.0 D), and high myopia group (SE $\leqslant-$ 6.00 D), and the visual acuity with best correction needed to be greater than 0.8; ⟂ results from slit lamp biomicroscopy and direct ophthalmoscopy showed average anterior chamber depth, transparent refractive media, cup-to-disc ratio (CDR) less than 0.6, inter-eye CDR difference less than 0.2, well-defined disc margins, absence of bleeding and scars, and non-pathological myopic fundus changes allowed (e.g., tessellated fundus, peripapillary crescent, etc.); ⟃ IOP between 10–21 mmHg. During eye exams, slit lamp biomicroscopy and direct ophthalmoscopy are essential diagnostic methods that offer precise views of the anterior and posterior segments for diseases such as cataracts and corneal ulcers. Accurate diagnosis of these problems requires training and experience.

The criteria for excluding the patients from this work were as follows: ⟀ patients who were unable to cooperate with the examination process; ⟁ patients with an absolute value of cylindrical power greater than 1.0 diopter (DC); ⟂ patients with existing ophthalmic conditions such as eye trauma, amblyopia, glaucoma, cataracts, manifest strabismus, and retinal vascular diseases; ⟃ patients who had previously undergone intraocular surgery; ⟄ patients with systemic diseases such as cranial trauma or lesions, hypertension, and diabetes; ⟅ patients with severe ocular diseases that could affect CT and morphology, such as uveitis, macular holes, choroidal neovascularization, and retinal detachment; ⟆ patients with manifest strabismus or amblyopia; ⟇ patients with corneal abnormalities such as keratoconus and keratoglobus; ⟈ patients for whom clear CT images could not be obtained.

2.2 Major instruments

The following instruments were employed primarily in this work: a computerized autorefractor/ keratometer (Huvitz HRK-7000A, Huvitz, South Korea), an electronic tonometer (CT-8, Topcon, Japan); a slit lamp biomicroscope (KJ900-A2, LIO, China); A/B-scan ultrasonography (MD-2300S, Meda, China), an optical coherence tomography (OCT) (iVue100, Optovue, USA), a AL measurement device (AL-Scan, NIDEK, Japan); and an automatic keratometer (AR-1s/1a/1, NIDEK, Japan).

2.3 Examinations of eyes

Visual acuity examination was performed as follows. The participants were positioned at a standard distance and covered one eye. Standardized charts, near vision tests, pinhole tests, refraction tests, and contrast sensitivity tests are used in visual acuity examinations to evaluate the clarity and sharpness of vision. These techniques identify the need for actions to optimize visual function, track changes in vision, and diagnose refractive problems. The new national standard logarithmic visual acuity chart was used, and the participants were asked to read aloud the letters or symbols they could recognize on each line. The minimum font size at which the participants could correctly identify the characters was recorded as their unaided visual acuity. The same procedure was followed to test the other eye.

Objective computerized refraction was conducted as follows. The participant aligned their eyes with the computerized refractor device, which automatically measured the refractive power of the eyes and recorded the data. By analyzing the results obtained by the computer, the examiner determined the SE power of patients.

Subjective refraction was implemented for all patients. An ophthalmologist used progressively adjusted spherical and cylindrical lenses to optimize the participant’s vision based on their responses. Image analysis software helps ophthalmologists interpret ocular images from diagnostic modalities such as fundus photography, fluorescein angiography, and OCT to support clinical decision-making in managing ocular conditions. It also improves diagnostic accuracy, makes quantitative measurements easier, and allows for detailed annotations of ocular structures. Ophthalmologists use spherical and cylindrical lenses to correct refractive defects such as astigmatism, hyperopia, and myopia to maximize vision. These lenses improve visual performance and patient quality of life by being tailored to each patient’s needs depending on their answers throughout the adjustment process. Meanwhile, the participant observed letters or symbols with different lenses and provided feedback to determine the best visual acuity.

An electronic tonometer was employed to measure IOP. The participant sat or lay down, and the measuring device made contact with the eye to record the IOP data. Electronic tonometers measure intraocular pressure (IOP) using the applanation tip, force sensor, microprocessor, pressure display, calibration mechanism, power supply, alignment system, and data storage. Calibration ensures accuracy, and consistent functioning requires dependable power.

The anterior segment was examined as follows. The participant sat in front of a slit lamp biomicroscope, and an ophthalmologist examined the anterior segment of the eye, including the cornea, iris, lens, and anterior chamber depth.

Fundus examination was implemented using the following operations: After the participant entered a dark room, an ophthalmologist used a direct ophthalmoscope to illuminate the eye and examine the fundus structures. The examination included the evaluation of the retina, choroid, and optic disc.

Ocular motility was examined as follows: The participants were allowed to focus on specific targets or follow instructions to move their eyes, and an ophthalmologist observed the range and coordination of eye movements.

Ocular A/B-scan ultrasound examination was described as follows. The participant was asked to close their eyes, and an ophthalmologist placed an ultrasound probe above the participant’s eye to obtain images of the ocular structures using ultrasound waves. The doctor observed any abnormalities during the examination, such as retinal detachment or vitreous traction.

Furthermore, the CT in the MC was measured. The participant sat in front of an OCT scanner, resting their chin on support to align their eyes with the scanner. OCT scanners utilize a broadband light source, interferometric detection, 2D and 3D scanning mechanisms, high-speed imaging, adaptable optics, customizable depth and clarity applications, sophisticated processing images, and integration with other imaging techniques to diagnose illnesses accurately. An ophthalmologist performed appropriate calibration and focused on the participant’s eyes. During the scan of the macular area, the focus is mainly on the MC and its surrounding region. Using the scanning modes and features of the OCT scanner, specific scan lines or a sector scan area were selected and positioned over the target locations, including the MC and its surrounding area. Ophthalmologists ensure their patients are comfortably positioned, have their pupils dilated, have their alignment and focus adjusted, complete a quality evaluation, are cooperative, and consistently record pertinent data. The scan was initiated, and the OCT scanner generated high-resolution cross-sectional images. The ophthalmologist utilized software for image analysis, employing measurement and annotation tools. Specific positions relative to the MC were selected in the image for CT measurements. This process was repeated to obtain CT values for the MC and distances temporally, nasally, superiorly, and inferiorly from the MC.

In addition, the AL was measured. Firstly, it should ensure that the participant was comfortably seated in the examination chair and kept their head stable. Next, an appropriate amount of topical anesthetic eye drops could be administered to numb the surface of the participant’s eye, minimizing discomfort. Next, the position and angle of the AL measurement device were adjusted to align it with the participant’s eye. Meanwhile, the participant was asked to look straight ahead and maintain a stable gaze. Finally, an optical interferometer was used to measure and record the obtained AL measurement.

The steepest and flattest keratometry readings (K1 and K2) exhibited a similar measurement process to the previous description. Using an automatic keratometer, the corneal curvatures in the steepest and flattest meridians were measured, and the values were recorded.

2.4 Methods for statistics

The obtained data were statistically analyzed using SPSS 20.0. Normally distributed data were presented as mean $\pm$ standard deviation. Bartlett’s test was utilized to verify the homogeneity of variances between groups. To ascertain if a variance is statistically comparable, Bartlett’s test assesses the homogeneity of variance between groups in a dataset. While non-parametric testing or data modifications could be required, parametric tests like ANOVA can be utilized if the data imply homogeneity. In the case of heterogeneous variances, the Wilcoxon rank-sum test was adopted for a two-group comparison, and the Kruskal-Wallis H test was used for multiple-group comparisons.

Additionally, the one-way analysis of variance and LST-t test were utilized for comparison among groups and pairwise comparisons, respectively. PCC analysis was conducted to examine the relationships between CT in the MC and variables such as SE, AL, K1, K2, gender, age, IOP, and family history of myopia, with a significance level of $P<$ 0.05. Besides, the multiple linear regression (MLR) analysis was performed to investigate the relationship between CT in the MC and these factors, with a significance level of $P<$ 0.05. A variance inflation factor (VIF) less than 10 indicated the absence of a linear relationship between the parameters.

3. Results

3.1 Comparison of myopia-related parameters in different groups

Based on Figs 1 and 2, statistically noticeable differences ( $P<$ 0.05) were observed in IOP, SE degree, AL length, and CT in the MC of patients in three myopia groups. The intricate link between myopia and increased axial length is highlighted by the fact that it causes decreased choroidal thickness in the macular center through mechanical stretching, decreased vascular density, compression, flattening, hemodynamic alterations, and effects on the retina and pigment epithelium.

Figure 1.

Comparison of myopia-relevant parameters of patients in various groups. Note: * and # suggested a significant difference with $P<$ 0.05 in the mild and moderate groups, respectively.

Figure 2.

Comparison of myopia-relevant parameters. Note: * and # suggested a significant difference with $P<$ 0.05 in the mild and moderate groups, respectively.

3.2 Comparison of gender and family history of myopia of patients in different groups

According to Table 1, t differences observed in gender and family history of myopia among the groups were not noticeable, showing $P>$ 0.05. However, when comparing the mild and high myopia groups, the gender difference was considerable ( $\chi^{2}=$ 4.966, $P=$ 0.035) and ( $\chi^{2}=$ 5.075, $P=$ 0.022).

Table 1
Gender and family history of myopia of patients in various groups

Group	Number of eyes	Males/females	With/without a family history of myopia
Healthy	46	18/28	14/32
Mild	46	20/26	31/15
Moderate	46	22/24	36/10
Severe	46	25/21	40/6

Figure 3.

Comparison of CT values in diverse sites. Note: F referred to the MC; T1, S1, I1, and N1 presented the sites 1,000 $\mu$ m on the temporal side, above, under, and nasal side, respectively.

Figure 4.

Comparison of CT values in diverse sites. Note: T3, S3, I3, and N3 presented the sites 3,000 $\mu$ m in the temporal, above, under, and nasal sides, respectively.

3.3 Comparison of CT values in diverse sites

Figures 3 and 4 demonstrated that the CT values at different locations were compared among the groups. The results indicated that the healthy group had the thickest CT in the MC, which gradually decreased towards the periphery, with the thinnest measurement observed on the nasal side. High-resolution OCT images are taken and analyzed to measure the choroidal thickness (CT) at the macular center (MC) and the distances from it. The CT at the MC is measured. Additionally, the distances are measured in different directions, the measurements are repeated for accuracy, and statistical relationships are examined. Vision, nutrient exchange, and retinal function are all enhanced in healthy individuals with thicker choroids, particularly in the macular center. It improves vision, acts as a biomarker to evaluate retinal health, and guards against age-related macular degeneration. In the mild, moderate, and severe myopia groups, the thickest CT was observed at 1,000 $\mu$ m from the temporal side, gradually thinning towards the periphery, with the thinnest measurement on the nasal side.

3.4 Correlation between CT in the MC and relevant factors using PCC

The PCC analysis was conducted to analyze the relationship between CT in the MC and relevant factors, as displayed in Table 2. The results revealed that CT in the MC was not associated with age, K1, or K2. However, it showed a specific correlation with a family history of myopia, SE, AL, and IOP.

Table 2
Relevance of CT in the MC with myopia-related parameters

Parameters	$r$ value	$P$ value
Gender	0.181	0.065
Family history of myopia	$-$ 0.245	0.007
Age (years old)	$-$ 0.063	0.259
SE (D)	0.602	0.000
AL (mm)	$-$ 0.647	0.000
IOP (mmHg)	$-$ 0.281	0.003
K1	0.079	0.146
K2	0.142	0.082

3.5 Correlation between CT in the MC and relevant factors using MLR

MLR analysis was employed to examine the relevance between CT in the MC and relevant factors, as presented in Tables 3 and 4 and Figs 5–8. The analysis revealed a negative linear relationship between AL and CT in the MC (SC $=-$ 0.596, $P=$ 0.000, tolerance $=$ 0.217, and VIF $=$ 4.467). It shows a negative linear connection between choroidal thickness and axial length in the macular center, implying that there may be a correlation between the two. Longer axial lengths are linked to high myopia, and this, in turn, causes a linear drop in choroidal thickness. In contrast, SE exhibited a positive linear relationship with CT in the MC (SC $=$ 0.205, $P=$ 0.013, tolerance $=$ 0.257, and VIF $=$ 3.792). However, no considerable linear relationship was observed between CT in the MC and other factors.

Table 3
MLR results for CT in the MC and relevant factors

Parameters	Gender	Family history of myopia	Age (years old)	SE (D)
SC	$-$ 0.041	$-$ 0.079	0.025	0.205
$P$ value	0.575	0.226	0.725	0.013
Tolerance	0.794	0.832	0.868	0.257
VIF	1.251	1.160	1.106	3.792

Table 4

MLR results for CT in the MC and relevant factors

Parameter	AL (mm)	IOP (mmHg)	K1	K2
SC	$-$ 0.596	$-$ 0.117	0.168	$-$ 0.220
$P$ value	0.000	0.089	0.087	0.053
Tolerance	0.217	0.874	0.453	0.349
VIF	4.467	1.125	2.014	2.806

Figure 5.

Relevance of CT in the MC to AL.

Figure 6.

Correlation between CT in the MC and SE.

Figure 7.

Relevance between CT in the MC and K1.

Figure 8.

Relevance between CT in the MC and K2.

4. Discussion

MC, a crucial structure within the eye, is located in the central region of the retina and is one of the most visually sensitive areas. Conversely, CT is a layer of tissue between the retina and the sclera that is responsible for supplying the retina with oxygen and nutrients. Hence, CT in the MC refers to measuring the thickness of the macular choroid tissue beneath the MC. This measurement is typically assessed using the OCT technology [27]. This study explores myopia’s characteristics and its relationship with CT. Myopia is a common ocular condition characterized by an elongated AL or excessive refractive power, causing the light to focus in front of the retina and resulting in blurred distance vision. The severity of myopia can be assessed using the SE, which considers both the spherical and cylindrical refractive powers. In recent years, increasing evidence suggests a close relationship between myopia and CT. CT may play a significant role in the development and progression of myopia. Therefore, the objective of this study is to investigate the correlation between myopia, CT, and the degree of myopia to gain further insights into the relationship between these factors.

In this work, data were collected from 95 subjects, comprising 190 eyes, and were rolled into four groups: a healthy group, a low, moderate, and high myopia group. Initially, the impact of gender and the degree of myopia on CT was explored. The results revealed no visible differences in gender and family history of myopia among the groups, suggesting that these two factors may not have a marked influence on CT. However, when comparing the low, moderate, and high myopia groups, the gender differences were statistically observable, indicating that gender may have some influence on CT under different degrees of myopia. Research on choroidal thickness (CT) in myopic people shows mixed results regarding the impact of gender. Although their exact impact is unknown, variables, including changes in hormone levels and lifestyle choices, could have a role. This finding could be related to the biological differences between genders in eye growth and development. Physiological factors such as sex hormones may affect eye structure and CT development, leading to CT differences under different degrees of myopia [28].

Additionally, behavioral habits and environmental factors may also be gender-related, further affecting AL growth and myopia development. Behavioral patterns that cause eye strain and increased visual stress, such as working close to screens, engaging in inadequate outdoor activities, and so on, can contribute to myopia development. Maintaining visual health and lowering the risk of myopia requires careful adherence to excellent visual ergonomics, balanced behavior promotion, and parental influence. Future research can further explore the relationship between gender and CT, considering additional potential influencing factors to gain a more comprehensive understanding of the mechanisms by which gender influences myopia.

Subsequently, through the analysis, this study concluded that the CT beneath the MC was the thickest, gradually thinning as it moved away from the center, with the thinnest CT observed on the nasal side. When comparing the low, moderate, and high myopia groups, the thickest CT was found at 1,000 $\mu$ m on the temporal side, gradually thinning towards the periphery, and the thinnest CT was observed on the nasal side. These findings are consistent with the research conducted by Zhang et al. [29] and Kim et al. [30], which demonstrated that CT is thickest beneath the MC and gradually thins towards the periphery. The MC is the most visually sensitive area and requires more oxygen and nutrient supply, resulting in a relatively thicker CT in that region. At 1,000 $\mu$ m on the temporal side, the CT was thickest in each degree of myopia group, gradually thinning as it moved away from the center, with the thinnest CT observed on the nasal side. This finding is consistent with existing research and is likely related to the AL length in myopia. Previous studies have shown that myopia is associated with longer AL length, and elongation of AL leads to relatively thinner CT [31]. Therefore, this work suggested that higher degrees of myopia often had longer AL lengths, resulting in the maximum CT at 1,000 $\mu$ m on the temporal side.

This work utilized PCC analysis to explore the relationship between CT in the MC and several relevant factors. The results suggested no apparent associations between CT in the MC and age, K1, and K2. However, CT in the MC exhibited a specific correlation with a family history of myopia, SE, AL, and IOP. The lack of correlation between age and corneal curvature with CT in the MC suggests that these factors have a limited impact on CT changes in the macular region. Knowledge of the non-linear connection among age, corneal curvature, and choroidal thickness is crucial regarding ocular physiology, disease, and clinical practice. Visual acuity, refractive error, and the results of cataract surgery are all impacted by variations in corneal curvature. Different ocular diseases are linked to variations in the thickness of the chordae. This finding is consistent with the research conducted by Lu et al. [32], indicating that age and corneal curvature may not be the primary influencing factors for CT in the MC. The correlation between family history of myopia and CT in the MC suggests a potential role of genetic factors in CT development and myopia formation. Family history may reflect the influence of genetic genes on eye growth and development, which in turn affects CT thickness. The correlation between SE, AL, and CT in the MC is consistent with the mechanisms of myopia development, as myopia is associated with excessive AL length and increased spherical refractive power, while the macular region, as a critical area of the retina, is related to CT and the degree of myopia. The correlation between IOP and CT in the MC may indicate the influence of IOP on CT blood flow perfusion and nutrient supply. Elevated IOP can negatively impact ocular health and visual performance due to vasoconstriction of the choroidal vasculature, which reduces choroidal thickness. This is especially true in situations like glaucoma when there is mechanical compression, poor autoregulation, and hormonal dysregulation. Elevated IOP may lead to vasoconstriction of CT, resulting in reduced CT thickness [33].

In addition, MLR analysis was employed to explore the relationship between CT in the MC and several relevant factors. The results reflected a negative linear relationship between AL and CT in the MC. At the same time, SE possessed a positive linear relationship with CT in the MC, and the linear relationships between CT in the MC and other factors were not apparent. AL length is an essential indicator of myopia development, and our findings indicate a negative correlation between AL length and CT in the MC. This suggests that an increase in AL length may lead to a decrease in CT in the MC. The elongation of the AL may cause stretching and compression of the retina and CT, affecting the blood supply and nutrient delivery to the CT, resulting in a reduction in CT [34].

On the other hand, SE is an essential parameter for evaluating the degree of myopia, and our results showed a positive correlation between SE and CT in the MC, indicating that an increase in the degree of myopia may lead to a rise in CT in the MC. The excessive AL length and increased spherical refractive power in myopia may cause dilation of CT blood vessels and increased blood flow, thereby affecting CT [35]. These results further deepen our understanding of the association between CT in the MC AL and SE. It also highlights the significant role of CT in the development and progression of myopia. However, no significant linear relationships existed between CT in the MC and other factors such as age, K1, and K2. This could be due to several reasons. Firstly, multiple factors may influence CT.

Age and corneal curvature may only be a part of the factors affecting CT. In contrast, other factors such as genetic factors, eye growth and development processes, metabolic status, and retinal blood flow may also influence CT. Therefore, although age and corneal curvature may be associated with CT in specific populations, the overall sample may not exhibit a clear linear relationship. Secondly, there could be non-linear relationships. The relationship between CT in the MC and age and corneal curvature may be non-linear. Significant CT variations may exist within specific age ranges or corneal curvature ranges. However, the entire sample may not observe a clear linear trend.

Additionally, the study sample may have specific limitations, such as a small sample size and diversity within the sample. These factors may prevent the observation of significant linear relationships in the statistical analysis. Moreover, the methods and devices used to measure CT and corneal curvature may have some measurement errors, which could impact the analysis results and obscure the linear relationships. This study’s lack of a clear linear association between age and corneal curvature can be attributed to several reasons, including biological variability, changes associated with aging, cohort effects, methodological issues, biomechanical factors, and interactions among refractive errors. Measurement mistakes substantially impact dependability, statistical outcomes, accuracy, precision, variability, and bias in results analysis. By overestimating or underestimating observed effects, they can hide patterns, increase variability, introduce bias, skew analysis, and lower the dependability of study findings. Therefore, the lack of observable linear relationships between age, K1, K2, and CT in the MC may be attributed to the combined influence of various factors. Further research with larger sample sizes, comprehensive consideration of factors, and precise measurement methods can help investigate the relationship between these factors and CT in greater depth.

5. Conclusion

The CT in the MC was found to be thickest at the fovea and gradually decreased towards the periphery, with the thinnest CT observed nasally. In cases of myopia, the CT was thickest at 1,000 $\mu$ m temporally and gradually decreased towards the periphery, with the thinnest CT observed nasally. Furthermore, MLR analysis revealed a negative correlation between AL and CT in the MC, while a positive correlation was found between SE and CT in the MC. However, this work was subjected to some limitations that needed further exploration and improvement. This work did not consider other potential factors that could influence CT, such as genetic and environmental factors. Future research could incorporate these factors to analyze the influencing factors of CT comprehensively. Besides, this work only compared CT between myopic and healthy eyes, and it would be beneficial to expand the sample size to include participants from different age groups and ethnicities to gain a more comprehensive understanding of CT variations. Regarding the relationship between CT in the MC and SE, AL length, this work only conducted correlation analysis, and future research could further explore causal relationships and possible physiological mechanisms. In conclusion, this work compared and analyzed CT between myopic and healthy eyes, revealing the spatial distribution characteristics of CT in the MC and differences among different degrees of myopia. The findings indicated a correlation between AL length, SE, and CT in the MC, which was crucial for a deeper understanding of the visual system changes and pathological mechanisms associated with myopia.

Funding

The authors did not receive any funding.

Author contributions

Xi Yang and Jianmei Zhang are responsible for designing the framework, analyzing performance, validating the results, and writing the article. Yanyan Liang is responsible for collecting the information required for the framework, providing software, conducting critical reviews, and administering the process.

Data availability

No datasets were generated or analyzed during the current study.

Code availability

Not applicable.

Footnotes

Conflict of interest

Authors do not have any conflicts.

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Correlation between choroidal thickness and the degree of myopia

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 Research objects

2.2 Major instruments

2.3 Examinations of eyes

2.4 Methods for statistics

3. Results

3.1 Comparison of myopia-related parameters in different groups

Table 1 Gender and family history of myopia of patients in various groups

3.4 Correlation between CT in the MC and relevant factors using PCC

Table 2 Relevance of CT in the MC with myopia-related parameters

Table 3 MLR results for CT in the MC and relevant factors

5. Conclusion

Funding

Author contributions

Data availability

Code availability

Footnotes

Conflict of interest

References

Table 1
Gender and family history of myopia of patients in various groups

Table 2
Relevance of CT in the MC with myopia-related parameters

Table 3
MLR results for CT in the MC and relevant factors