Introduction: This study aimed to compare retinal vascular parameters and density in patients with moyamoya disease using the optical coherence tomography angiography. Methods: This clinical trial totally enrolls 78 eyes from 39 participants, and all these patients with moyamoya disease (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). Then all these participants receive optical coherence tomography angiography detection. Participants’ general data are collected and analyzed. Skeleton density (SD) value, vessel density (VD) value, fractal dimension (FD) value, vessel diameter index (VDI) value, foveal avascular zone (FAZ) value are analyzed. Results: A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017). Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, VDI and FAZ values in the experimental group were lower than those in the control group, there was no significant difference in VDI and FAZ values between the two groups. Conclusions: Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with moyamoya disease.

Moyamoya disease (MMD) is a type of occlusive chronic cerebrovascular disease. Symptoms of MMD include transient ischemic attacks, cerebral infarction, and cerebral hemorrhage. These symptoms are often accompanied by headaches, epilepsy, and consciousness disorders. It is caused by progressive stenosis (narrowing) of the blood vessels in the brain. MMD is known for being a rare cause of stroke [1, 2]. At the same time, the brain develops compensatory abnormal vascular networks at the bottom part of the brain [3, 4]. MMD has an incidence of 10.5/100,000, and there is a rising incidence across the world and MMD contributes to high mortality and morbidity, especially in those patients with hypertension and patients with diabetes. A study by Sun [5] has reported that MMD mainly occurs in East Asia, and China has the largest number of incidence of patients with MMD considering that China is the largest nation in Asia [6]. Currently, common therapeutic regimens for MMD include direct revascularization surgery, indirect revascularization surgery, drug treatment, bleeding management for patients with MMD. With therapeutic approaches increasing and improving, therapeutic effect in MMD patients has been improved and these therapeutic approaches have improved the quality of the patient’s life [7]. However, the mortality of MMD is still high because of cerebral infarction in postoperative patients with MMD, and the therapeutic effect for MMD still does not meet the requirement of patients and their family members. It is urgent to prolong patient’s life and improve the quality of the patient’s life, but the detailed mechanism of MMD is still unknown. Interestingly, some studies [8, 9] have reported that microvascular density and morphology in patients with MMD exhibit significant abnormalities. The specific impact of vein occlusions and retinal artery on preventing the progression of MMD in patients is still not clear. Additionally, other studies [10] have suggested that abnormal embryonic development of cerebral arteries plays a role in the development of MMD, specifically involving sprouting angiogenesis and vessel fusion. And pruning is associated with the MMD by regulating the cranial ramus of primitive internal carotid artery in the early mesodermal development [11, 12]. And those results in previous studies [10, 12] have shown that abnormal vessel in patients with MMD can affect the retinal vascular parameters and density. However, precise mechanism of MMD is unknown. Numerous trials [2] have investigated the detailed mechanism of MMD by examining various parameters, such as skeleton density (SD), vessel density (VD), fractal dimension (FD), and vessel diameter index (VDI). These parameters are used to analyze the retinal vascular system and understand its relationship with MMD. Additionally, the foveal avascular zone (FAZ) has also been studied in relation to MMD. Therefore, this paper aimed to investigate the mechanism of MMD by calculating retinal vascular parameters and density in patients with MMD.

Skeleton Density

SD is a parameter commonly employed to assess both the function and structure of blood vessels in the human brain. A study by Kim [2] has investigated the relationship between SD and patients with diabetic retinopathy, but the correlation between SD and patients with MMD has not been investigated. VD, which mainly refers to the length of the blood vessel, is determined by the total length of perfused vasculature in measurement region. VD also has been used to evaluate the microvascular density and morphology in patients with diabetic retinopathy [2]. VD also is utilized to assess the change of choroidal structure and retinal microvasculature in patients with Parkinson disease. However, few studies have investigated the relationship between VD and patients with MMD [13].

Fractal Dimension

FD is a quantitative parameter extensively utilized to assess both the function and structure of blood vessels in the human brain. It is particularly well known for its application in observing patients with high-density electroencephalogram. A study by Ruiz de Miras J [14] has reported that FD can be used to measure the complexity and the brain’s capacity, and another study [2] also pointed out that FD can be used to observe the microvascular density and morphology in patients with diabetic retinopathy, but the study of FD being used to evaluate the microvascular density and morphology in patients with MMD is still limited.

Vessel Diameter Index

VDI, which is also known as blood vessel length, is used to evaluate the microvascular density and morphology. Those results in previous study [2] have reported that VDI is used to evaluate the microvascular density and morphology in patients with diabetic retinopathy.

Foveal Avascular Zone

The FAZ [15], which refers to a single-layered parafoveal capillary arcade, is a round capillary-free zone within the macula. Those results by Khan H M [8] have reported that FAZ can be used to calculate the diameter of blood vessel in patients with MMD, but the detailed relationship between FAZ and MMD patients is elusive. Optical coherence tomography angiography (OCTA) can be used to calculate the SD and VD, FD and VDI, FAZ according to those findings described in previous study [2]. In the existing research on MMD, there is a gap in understanding the relationship between quantitative parameters such as VD, FD, VDI, and FAZ and the microvascular density and morphology in patients with MMD. Our study aimed to address this gap by investigating these parameters in relation to MMD, providing valuable insights into the microvascular changes associated with the disease.

In summary, previous studies have utilized various quantitative parameters such as VD, FD, VDI, and FAZ to assess the microvascular density and morphology in different diseases. However, there is still limited research on the relationship between these parameters and patients with MMD; this study aims to investigate the relationship between quantitative parameters (VD, FD, VDI, FAZ) and MMD and propose the use of OCTA to explore this relationship. In patients with MMD, the study found that retinal vascular parameters and density were decreased, as indicated by significantly lower standard deviation, VD, and FD values in the experimental group compared to the control group. However, there were no significant differences in VDI and FAZ values between the two groups.

Study Design and Participants

We conducted this retrospective cross-sectional study, which totally enrolls 78 eyes from 39 subjects from Peking University International Hospital during January 2021 to May 2023, and all these patients with MMD (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). All subjects used for this retrospective cross-sectional study are willing to receive the detection of swept-source optical coherence tomography (SS-OCTA), which is a non-invasive imaging technique that uses a tunable laser source to rapidly scan the tissue and create cross-sectional images. It provides detailed information about the structure and thickness of retinochoroid layers, allowing for the detection and monitoring of various diseases. Therefore, in our study, a SS-OCT (DRI OCT Triton; Topcon Corporation, Tokyo, Japan) with a central wavelength of 1,050 nm, an acquisition speed of 10,000 A-scans per second, and an axial and transversal resolution of 7 and 20 μm in tissue, respectively. Randomly selecting either the right or left eye is another viable approach. This approach helps minimize any potential bias or differences between the eyes of the cases and controls. Randomly assigning the eye to be included in the analysis ensures an unbiased representation of the patient population and reduces the risk of introducing systematic differences between the groups; 3 × 3 mm2 en face images centered at the fovea were captured and differentiated into superficial retinal layer and deep retinal layer based on the automated layer segmentation performed using the OCT instrument software. The ethic approval was obtained from the Ethic Committee of the Peking University International Hospital (IRB Approval Number: 2023-KY-0087-01) and written informed consent was obtained from all patients.

Inclusion criteria for all MMD patients are as follows: ① Subjects and their families have signed an informed consent form. ② Patients are diagnosed as MMD using digital subtraction angiography. Digital subtraction angiography is a diagnostic imaging technique that allows for the visualization of blood vessels by selectively subtracting the surrounding structures from the image. ③ Clear display of intracranial blood vessels in all subjects can be obtained. This is crucial for accurately diagnosing and assessing conditions such as MMD as it allows for the identification of any abnormalities or narrowing in the intracranial blood vessels. ④ Morphology in posterior endovascular circulation in all subjects is normal; there are no apparent abnormalities or blockages in the blood vessels supplying this region of the brain, which is important for ensuring proper blood flow and function in the brain. Exclusion criteria for all subjects are as follows: ① Eyes for subjects with glaucoma, high refractive error, or patients with other vascular disorders affecting the central nervous system or retina, such as diabetes mellitus and neurodegenerative disorders, and diabetes mellitus is a metabolic disorder that can lead to various systemic complications, including vascular issues that can affect the eye. Neurodegenerative disorders refer to a group of conditions where there is progressive damage or loss of nerve cells in the brain, such as Alzheimer’s disease or Parkinson’s disease. These conditions are likely excluded to ensure that the study focuses on individuals without these additional complications, allowing for a clearer understanding of the specific factors being investigated. ② The patient or patients’ guardians do not sign the written informed consent.

Customized Semiautomated Algorithm

A custom semiautomated algorithm was developed to analyze and quantify retinal vascular density and morphology. This algorithm was designed to process SS-OCTA images. By utilizing this custom semiautomated algorithm and the various image processing techniques, the researchers were able to quantify retinal vascular density and morphology from the SS-OCTA images. The SS-OCTA image used in this study covered an area of 3 × 3 mm2 around the fovea. To facilitate the analysis, the image was converted into an 8-bit format. This conversion allowed for easier manipulation of the pixel values during subsequent processing steps. Each pixel in the converted image represented an area of approximately 9.375 × 9.375 μm2. This pixel size corresponds to the resolution of the SS-OCTA device used in the study. The binary image was obtained using a three-way combined method consisting of a global threshold, Hessian filter, and adaptive threshold in Python (version 3.7.3). The global thresholding was determined based on three circular selections within the FAZ, each with a fixed radius of 25 pixels (Fig. 1). A top-hat filter with a window size of 8 pixels was then applied to process the image (Fig. 2).

Fig. 1.

Original, non-segmented SS-OCTA image of an MMD patient. a Original SS-OCTA image of deep layers in the right eye. b Original SS-OCTA image of superficial layers in the right eye. c Original SS-OCTA image of deep layers in the left eye. d Original SS-OCTA image of superficial layers in the left eye.

Fig. 1.

Original, non-segmented SS-OCTA image of an MMD patient. a Original SS-OCTA image of deep layers in the right eye. b Original SS-OCTA image of superficial layers in the right eye. c Original SS-OCTA image of deep layers in the left eye. d Original SS-OCTA image of superficial layers in the left eye.

Close modal
Fig. 2.

Top-hat filtered image of the same MMD patient. a Top-hat filtered image in deep layers in the right eye. b Top-hat filtered image in superficial layers in the right eye. c Top-hat filtered image in deep layers in the left eye. d Top hat filtered image in superficial layers in the left eye.

Fig. 2.

Top-hat filtered image of the same MMD patient. a Top-hat filtered image in deep layers in the right eye. b Top-hat filtered image in superficial layers in the right eye. c Top-hat filtered image in deep layers in the left eye. d Top hat filtered image in superficial layers in the left eye.

Close modal

VD Detection

Subsequently, two separate binarized images were generated: one is obtained using a Hessian filter and the other is obtained through median adaptive thresholding. The final binarized image (Fig. 3) was obtained using a combination of the two resulting binarized vessel maps, including only the pixels detected in both binarization methods (Hessian filter and adaptive threshold). A similar binarization method has been previously described by Reif et al. [16]. VD represents a proportion of the total image area occupied by the detected OCTA signal (binarized as white pixels), which can be defined by the following:
VD=BX
where B is the number of pixels occupied by blood vessel area and X is the number of all pixels in the binarized image.
Fig. 3.

Binarized images of an MMD patient were obtained by using combined adaptive threshold and Hessian filter. a VD image in deep layers in the right eye. b VD image in superficial layers in the right eye. c VD image in deep layers in the left eye. d VD image in superficial layers in the left eye. VD, vessel density.

Fig. 3.

Binarized images of an MMD patient were obtained by using combined adaptive threshold and Hessian filter. a VD image in deep layers in the right eye. b VD image in superficial layers in the right eye. c VD image in deep layers in the left eye. d VD image in superficial layers in the left eye. VD, vessel density.

Close modal

SD Detection

A skeletonized image (Fig. 4), which was used to calculate the SD value, was obtained by iteratively deleting the pixels in the outer boundary of the binarized image and white-pixelated vasculature until 1 pixel remained along the width direction of the vessels. SD represents the length of blood vessel based on the skeletonized SD-OCTA image, which can be expressed as follows:
SD=LX
where L is the number of pixels occupied by blood vessel length and X is the number of all pixels in the skeletonized image.
Fig. 4.

Skeletonized images were obtained via iteratively deleting the pixels until 1 pixel kept along the width direction of the vessels. a represents a skeletonized image in deep layers in the right eye. b represents a skeletonized image in superficial layers in the right eye. c represents a skeletonized image in deep layers in the left eye. d represents a skeletonized image in superficial layers in the left-eye.

Fig. 4.

Skeletonized images were obtained via iteratively deleting the pixels until 1 pixel kept along the width direction of the vessels. a represents a skeletonized image in deep layers in the right eye. b represents a skeletonized image in superficial layers in the right eye. c represents a skeletonized image in deep layers in the left eye. d represents a skeletonized image in superficial layers in the left-eye.

Close modal

FD Detection

To assess the change of the branching of the capillary in all subjects, FD can be used to calculate the change of the capillary in all subjects, and a box-counting method is utilized to measure the FD value in the skeletonized image from the all subjects as described in a study by Reif [16]. In short, the method consists of dividing a skeletonized image into square boxes of equal sizes, where the number of boxes containing a vessel segment is counted. The process is iteratively repeated with boxes of different sizes. The absolute value of the slope of the curve, which shows the logarithm of the box size plotted against the number of boxes containing a vessel segment, is the FD, calculated as follows:
FD=log10Nllog10l
where l is the box length and N(l) is the number of boxes needed to cover the image.

VDI Detection

VDI refers to the average vessel caliber, which is calculated using the skeleton image and the binary blood vessel image, which can be defined as follows:
VDI=BL
where B is the number of pixels occupied by blood vessel area in the binarized image and L is the number of pixels occupied by blood vessel length in the skeletonized image.

FAZ Detection

FAZ refers to an area inside the central border of the foveal capillary network. Use the Python software to calculate the outlined area in pixels, and then assess the FAZ value based on the 320-pixel width of the images; finally, these images are converted to millimeters based on the scan dimensions (3 × 3 mm scan). The binarized image of the FAZ is presented in Figure 5. Based on those findings reported by Khan [8], FAZ value is determined by the largest non-vessel area that is segmented within a 1 mm diameter from the center.

Fig. 5.

FAZ images created by the Python software. a represents a FAZ image in deep layers in the right eye. b represents a FAZ image in superficial layers in the right eye. c represents a FAZ image in deep layers in the left eye. d represents a FAZ image in superficial layers in the left eye. FAZ, foveal avascular zone.

Fig. 5.

FAZ images created by the Python software. a represents a FAZ image in deep layers in the right eye. b represents a FAZ image in superficial layers in the right eye. c represents a FAZ image in deep layers in the left eye. d represents a FAZ image in superficial layers in the left eye. FAZ, foveal avascular zone.

Close modal

The calculation of VD, SD, FD, and VDI was performed as described in the previous studies [2, 16]. The FAZ area was measured as described in the previous study [17].

Statistical Analysis

The data were processed and statistically analyzed using IBM SPSS Statistics for Mac, v. 26.0 (IBM Corp., Armonk, USA). Descriptive data, which provide a summary of the data collected, were presented in different formats. For categorical variables, the data were reported as n (%), which represents the number of observations in each category and the percentage it represents of the total sample. This allows for a clear understanding of the distribution of categorical variables in the study population. For continuous variables, the descriptive statistics included the mean (average) with the standard deviation or the median with the quartiles (P25, P75). The mean and standard deviation provide information about the central tendency and variability of the data, while the median and quartiles give insights into the distribution and range of the data, especially if it is not normally distributed. To compare continuous variables between different groups, statistical tests such as the Student’s t test or Mann-Whitney U test were used, depending on the distribution of the data. The Student’s t test assumes that the data are normally distributed, while the Mann-Whitney U test is a non-parametric test used when the data do not meet the assumptions of normality. The χ2 test, a statistical test used to determine if there is a significant association between categorical variables, was employed to evaluate categorical variables in this study. This test allows researchers to assess if there is a significant difference in proportions or frequencies between groups or categories. A p value of less than 0.05 was considered to indicate a statistically significant difference. This means that if the p value calculated from the analysis is less than 0.05, the observed difference between groups or categories is unlikely to have occurred by chance alone. It suggests that there is a statistically significant association or difference between the variables being compared.

Participants General Data

The clinical medical data of all participants were summarized and presented in Table 1. This table provided information on various variables, such as the number of subjects, gender, age, disease duration, methods of diagnoses, and methods of treatment. These variables are important for understanding the characteristics and demographics of the study population. One of the key findings from the analysis of Table 1 is that there were no significant differences in gender between the two groups. This suggests that the distribution of males and females was similar in both groups, indicating a balanced representation of genders in the study. Additionally, the analysis of Table 1 also revealed that there were no significant differences in age between the two groups. This implies that the average ages of the participants in both groups were similar, indicating that age did not play a significant role in differentiating the groups. The lack of significant differences in gender and age between the two groups is an important finding as it suggests that any observed differences or associations between other variables (such as disease duration, diagnoses, and treatments) are less likely to be confounded or influenced by differences in gender or age. This strengthens the validity of the subsequent analyses and interpretations of the study results.

Table 1.

Demographic participants general data

VariableControl groupExperimental group
Number of subjects N = 26 N = 13 
Age 45.77±6.4 45.15±7.6 
Gender/male, n (%) 14 (53.8) 7 (53.8) 
Disease duration, years 4.6±0.56 
Methods of diagnoses DSA 
Methods of treatment Surgical treatment 
VariableControl groupExperimental group
Number of subjects N = 26 N = 13 
Age 45.77±6.4 45.15±7.6 
Gender/male, n (%) 14 (53.8) 7 (53.8) 
Disease duration, years 4.6±0.56 
Methods of diagnoses DSA 
Methods of treatment Surgical treatment 

DSA, digital subtraction angiography.

Result of Vascular Density and Retinal Vascular Parameters

The vascular density and retinal vascular parameters of the control group and experimental group were presented in Table 2. A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017]. Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, although the values appeared to be lower in the experimental group, there was no significant difference between the two groups.

Table 2.

VD and retinal vascular parameters of experimental group and control group

VariableControl groupExperimental groupp value
SD 0.184 (0.175, 0.188) 0.175 (0.166, 0.181) 0.017 
VD 0.354 (0.337, 0.364) 0.333 (0.320, 0.350) 0.024 
FD 2.096 (2.090, 2.101) 2.088 (2.083, 2.094) 0.022 
VDI 1.924 (1.903, 1.941) 1.916 (1.884, 1.946) 0.905 
FAZ, mm2 0.448±0.124 0.412±0.091 0.358 
VariableControl groupExperimental groupp value
SD 0.184 (0.175, 0.188) 0.175 (0.166, 0.181) 0.017 
VD 0.354 (0.337, 0.364) 0.333 (0.320, 0.350) 0.024 
FD 2.096 (2.090, 2.101) 2.088 (2.083, 2.094) 0.022 
VDI 1.924 (1.903, 1.941) 1.916 (1.884, 1.946) 0.905 
FAZ, mm2 0.448±0.124 0.412±0.091 0.358 

SD, skeleton density; VD, vessel density; FD, fractal dimension; VDI, vessel diameter index; FAZ, foveal avascular zone.

Previous studies have used quantitative parameters such as VD, FD, VDI, and FAZ to evaluate microvascular density and morphology in different diseases, but there is limited research on their relationship with MMD. The study included a total of 39 participants and found that there were no significant differences in gender and age between the two groups, indicating a balanced representation of genders and similar average ages. The key findings indicate that the SD, VD, and FD values were significantly lower in the experimental group compared to the control group, suggesting differences in retinal vascular parameters. However, there were no significant differences in VDI and FAZ between the two groups. Overall, these findings suggest that there are significant differences in some retinal vascular parameters between patients with MMD and healthy controls, but further research is needed to fully understand the relationship between these parameters and the disease. MMD patients receiving surgical treatment are still at a high risk of life loss. To improve effect of MMD patients undergoing surgical treatment, it is urgent to find better treatment method for MMD patients, and the main reason leading to low treatment effect is that the detailed mechanism of MMD is still unclear. Numerous trials have showed that vascularization has association with the process and development of MMD, and the study of retinal vascular density and morphology can provide clinical material for the density and morphology in MMD patients. We conducted this study to investigate the changes in retinal vascular parameters and density in patients with MMD in order to clarify the relationship between vascularization and MMD. We analyzed the subjects’ general clinical data, SD value, VD value, and FD value of MMD group is significantly smaller than the control group (p = 0.017, 0.024, 0.022, respectively). Besides, we found a trend toward smaller VDI value and FAZ value of MMD group compared to the control (p = 0.905, 0.358, respectively). Our outcomes demonstrated the poorer microvascular parameters, which indicates retinal microvascular involvement in the MMD patients. The novelty of this study lies in its focus on analyzing retinal vascular parameters in patients with MMD. While previous research [10, 11] has primarily focused on cerebral vascular abnormalities in MMD, this study expands the scope to examine retinal microvascular changes. By investigating retinal vascular parameters, the study provides new insights into the potential involvement of the retinal vasculature in MMD.

SD, which refers to the structural and the function of blood vessel, also is utilized to measure the density of blood vessel and investigate the systemic determinants of health in cardiovascular diseases. A cross-sectional study by Kushner-Lenhoff [18] has reported that SD can be used to evaluate the systemic determinants of health in diabetes status, and these results in this previous study have suggested that SD is a promising index to detect diabetes status via the blood density. In addition, this trial by Khan [8] reporting SD of 6 × 6 mm centered images in MMD patients revealed a poorer trend despite no significant difference, indicating SD in retinal microvasculature can be used for detection for MMD patients. Our study results show that the SD in retinal microvasculature of MMD patients is significantly decreased than the healthy subjects (p = 0.017). VD mainly is used to assess the microvascular density and morphology [19‒21]. Those results by Khan also reported the association between MMD patients and VD, which is the same in our outcomes (p = 0.024). FD can be used to assess the function and structure of the blood vessel [14, 22]. Some studies [8, 23] have pointed out associations of FD between MMD patients and healthy subjects. And these results showed that FD value between MMD patients and healthy subjects has no significant difference. On the contrary, our study demonstrates a significant difference between MMD and healthy subjects (p = 0.022).

Previous research assumed that MMD is associated with dysregulation of matrix metalloproteinases, which affected vessels in genetically predisposed individuals [24]. MMD is characterized by stenosis or occlusion of the terminal portions of bilateral internal carotid arteries and abnormal vascular network in the vicinity of the arterial occlusion [25]. Hence, we assumed the vascular density at the level of retina in MMD patients changes because the vascular network is mainly supplied by the ophthalmic artery, the first branch of internal carotid arteries as it. These results by our trial give strong evidence for the MMD retinal microvascular involvement.

VDI is used to evaluate the length of the blood vessel [26, 27]. A study [8] has investigated the relationship between diabetic retinopathy patients and VDI, and these results suggested that VDI value between diabetic retinopathy patients and healthy subjects has no significant differences [2]. The association of VDI between MMD patients and healthy subjects is still elusive. FAZ has been widely used to assess the retinal vascular changes in patients with systemic diseases and patients with ocular pathologies [28‒30]. A trial [8] has reported that the association of FAZ between MMD patients and healthy subjects and FAZ value between MMD patients and healthy subjects is not significantly different, and those results are similar to these results in our study.

OCTA is an innovative method to measure the retinal vascular density and morphology, which objectively and quantitatively present the SD value, VD value, FD value, VDI, and FAZ. OCTA in numerous studies have been utilized to observe the retinal vascular density and morphology, showing that OCTA is a promising and non-invasive technology to investigate the mechanism of MMD patients. However, the detailed mechanism of MMD is still unclear. Most of the retinal vascular parameters and density between the two groups revealed significant differences in our study, and all quantitative data show that microvasculature of fovea in patients with MMD tends to decrease compared to those in healthy subjects. The study has limitations, including a small sample size, and further research with a larger sample size is needed: one of the main limitations of this study is the small sample size. While the study provides valuable insights into the retinal microvascular parameters in MMD patients, the limited number of participants may affect the generalizability of the findings. Therefore, conducting further research with a larger sample size is necessary to validate and strengthen the present results. Additionally, expanding the sample size would allow for the exploration of additional factors that may influence retinal microvascular parameters in MMD, such as disease severity, duration, and treatment history. Such investigations would enhance our understanding of the relationship between MMD and retinal microvasculature.

Potential clinical implications of significant differences in retinal vascular parameters: the finding that most of the retinal vascular parameters showed significant differences between MMD patients and healthy subjects has important clinical implications. These differences could potentially serve as diagnostic or prognostic markers for MMD. By examining retinal vascular parameters, clinicians may be able to identify early signs of MMD or monitor disease progression. Additionally, these parameters may be useful in assessing the effectiveness of therapeutic interventions and evaluating disease outcomes.

Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with MMD. Most of the retinal vascular parameters and density showed significant differences between MMD patients and healthy subjects, and the findings provide valuable insights into the relationship between MMD and retinal microvasculature, shedding light on the potential impact of MMD on visual function. Addressing these limitations and conducting additional research will contribute to a better understanding of MMD and its implications for diagnosis, management, and prognosis.

We would like to acknowledge everyone for their helpful contributions on this paper.

The ethic approval was obtained from the Ethic Committee of the Peking University International Hospital (IRB Approval Number: 2023-KY-0087-01) and written informed consent was obtained from all patients. All of the authors have consented to publish this research.

All authors declare no conflict of interest.

This research received no external funding.

Xijuan Wang and Ying Meng conceived and designed experiments; Dan Song, Cunxin Tan, Guanzheng Wang, Bin Lv, Yuan Ni, Guotong Xie, Ting Cui, Yan Zhang, Yaqian Niu, Chengxia Zhang, and Guangfeng Liu performed experiments and data analysis and provided technical support and data collection and analysis; and Xijuan Wang and Ying Men wrote the manuscript. All authors provided final approval for submitted and published version.

Additional Information

Xijuan Wang and Ying Meng contributed equally to this work.

The data that support the findings of this study are not publicly available due to privacy reasons but are available from the corresponding author upon reasonable request.

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