
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39232012
71286
10.1038/s41598-024-71286-6
Article
Macular vascular and photoreceptor changes for diabetic macular edema at early stage
Gu Qinyuan 1
Pan Ting 1
Cheng Ruiwen 1
Huang Junlong 1
Zhang Kang 1
Zhang Junyan 2
Yang Yang carlayangyang@whu.edu.cn

3
Cheng Peng cphh@sohu.com

4
Liu Qinghuai liuqh@njmu.edu.cn

1
Shen Han shenhan@njmu.edu.cn

1
1 grid.412676.0 0000 0004 1799 0784 Department of Ophthalmology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029 China
2 grid.470966.a Department of Clinical Epidemiology and Evidence-Based Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032 China
3 https://ror.org/03ekhbz91 grid.412632.0 0000 0004 1758 2270 Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei China
4 grid.412676.0 0000 0004 1799 0784 Department of Gerontology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029 China
4 9 2024
4 9 2024
2024
14 205443 6 2024
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
This study was intended to investigate the macular vascular and photoreceptor changes for diabetic macular edema (DME) at the early stage. A total of 255 eyes of 134 diabetes mellitus patients were enrolled and underwent an ophthalmological and systemic evaluation in this cross-sectional study. Early DME was characterized by central subfoveal thickness (CST) value between 250 and 325 μm, intact ellipsoid zone, and an external limiting membrane. While non-DME was characterized by CST < 250 μm with normal retinal morphology and structure. Foveal avascular zone (FAZ) area ≤ 0.3 mm2 (P < 0.001, OR = 0.41, 95% CI 0.26–0.67 in the multivariate analysis) and HbA1c level ≤ 8% (P = 0.005, OR = 0.37, 95% CI 0.19–0.74 in multivariate analysis) were significantly associated with a higher risk of early DME. Meanwhile, no significant differences exist in cone parameters between non-DME and early DME eyes. Compared with non-DME eyes, vessel diameter, vessel wall thickness, wall-to-lumen ratio, the cross-sectional area of the vascular wall in the upper side were significantly decreased in the early DME eyes (P = 0.001, P < 0.001, P = 0.005, P = 0.003 respectively). This study suggested a vasospasm or vasoconstriction with limited further photoreceptor impairment at the early stage of DME formation. CST ≥ 250 μm and FAZ ≤ 0.3 mm2 may be the indicator for early DME detection.

Keywords

Foveal avascular zone
Optical coherence tomography angiography
Adaptive optics scanning laser ophthalmoscope
Diabetic macular edema
Subject terms

Diseases
Risk factors
Signs and symptoms
http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China 82271100 82101151 Liu Qinghuai Shen Han http://dx.doi.org/10.13039/501100004608 Natural Science Foundation of Jiangsu Province BK20210972 Shen Han issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

The global population with diabetes mellitus (DM) was estimated to be 463 million in 2019 and 700 million in 20451. Among which, 34.6% individuals suffered from diabetic retinopathy (DR) and 6.8% experienced diabetic macular edema (DME)2. DR has been the leading cause of preventable blindness in adult population at working age3,4. DME is one of the major causes of vision impairment in DR patients5. Therefore, timely detection and early intervention of DME is of great importance.

Optical coherence tomography (OCT) is a safe, non-invasive, convenient method for DME screening. Central subfoveal thickness (CST), provided by OCT, is suggested as the most reliable objective measure of DME6. Recently, a grading system was established to show the progression and severity of DME. Based on spectral domain optical coherence tomography (SD-OCT) results, DME is classified into four stages: early DME (small intraretinal cysts, well-recognizable and detectable inner retinal layers, intact ellipsoid zone and external limiting membrane, and increase in CST ≤ 30% of upper normal values), advanced DME (macrocysts and/or multiple intraretinal cystoid spaces and CST > 30% of maximum normal values), severe DME (advanced DME characteristics with mostly undetactable inner retinal segmentation and/or ellipsoid zone and/or the external limiting membrane), and atrophic maculopathy (complete disruption of the outermost retinal layers and disorganization of the inner retinal layers)7.

Previous studies indicated that retinal thickness values are different using different OCT devices8,9. Using Zeiss stratus OCT (Carl Zeiss Meditec, Dublin, California, USA), mean CST was 209 ± 18 μm for man and 194 ± 23 μm for women10. Previous studies frequently defined CST values over 250 μm as an indicative of macular edema8,10–12. Using Heidelberg Spectralis OCT (Heidelberg Engineering, Inc., Heidelberg, Germany), averaged CST was 278 ± 23 μm for man and 262 ± 22 μm for women. CST values ≥ 320 μm for man and 305 μm for women are proposed as DME13. Therefore, early DME could be defined as CST value between 250 and 325 μm on Zeiss stratus OCT; 320–415 μm for men and 305–397 μm for women on Heidelberg Spectralis OCT8,10,11,14.

Optical coherence tomography angiography (OCTA) is an objective, non-invasive, convenient method to visualize microvasculature without intravenous dye injection. It provides depth-resolved information about morphology, structure, vessel density, perfusion, microangiopathy of retinal and capillary vessels. Multiple details can be quantified using OCTA images, including vessel density (VD), the size of foveal avascular zone (FAZ), number of microaneurysms and intraretinal hyperreflective foci (iHRF), integrity of retinal pigment epithelium (RPE) and ellipsoid zone (EZ). Previous studies used these quantitative OCTA metrics to indicate the severity of DR and prognosticate the development of DME6,15–19. Recent studies laid emphasis on OCTA metric changes in clinically significant macular edema (CSME) patients post anti-VEGF treatment20,21. Most researchers focused on advanced and severe DME with retinal thickness exceeding 300 μm, rather than early DME, because early DME typically presents with small or no observable cysts, and early DME patients show no obvious clinical symptoms22.

The adaptive optics (AO) scanning laser ophthalmoscope (AOSLO) is an advanced non-invasive method to visualize microcirculation and retinal structures like cone cells. In 2023, Kupis et al.23 demonstrated significant differences in cone density, mosaic arrangement, and vascular morphology between healthy and diabetic patients. Zaleska-Żmijewska et al.24 used AOSLO imaging to identify decreased cone regularity and density in non-proliferative diabetic retinopathy (NPDR) patients and arteriolar dysfunction in DR patients. MONA II (Robotrak Techologies, China) was used to visualize and assess photoreceptors in laser-induced retinopathy25. It improves the quality of obtained images through real-time human eye-tracking technology26,27. The maximum field of view is 5° × 5°, which allows the imaging of blood velocity and flow across a broader range of vessel diameters28,29. The results of AO imaging may detect the pathological changes of the retina in advance30,31. To our knowledge, there are no studies assessing cones and vascular changes with the MONA II AO device in DME patients. This study was a cross-sectional observational study to investigate the macular vascular and photoreceptor changes for early DME. The association between risk factors and early DME was also investigated to indicate the possible pathogenesis at the onset of DME.

Methods

Study design

From November 2021 to August 2022, a cross-sectional observational study was performed at the First affiliated hospital with Nanjing Medical University. This research was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital with Nanjing Medical University (NO. 2021-SE-406).

Early DME was defined as CST value between 250 and 325 μm; small (highest vertical size < 200 µm) or less obvious intraretinal cysts; well-recognizable and detectable inner retinal layers; intact EZ and external limiting membrane (ELM). Non-DME was defined as CST < 250 μm, normal inner retinal structure, intact RPE layer, EZ, and ELM32.

A total of 255 eyes of 134 DM patients were enrolled and informed consents were written. When comparing demographic variables and systematic evaluation results, such as sex, age and HbA1c levels among patients, we categorized 134 patients into two groups: early diabetic macular edema patients (early DME group, 69 subjects) and patients without DME (non-DME group, 65 subjects). A patient was assigned to the early DME group upon diagnosis in at least one eye. For the comparison of ophthalmological examination results, including OCT, OCTA, and AOSLO outcomes, a total of 255 eyes were classified into two groups: early DME (114 eyes with CST ≥ 250 μm and < 325 μm) and non-DME eyes (141 eyes with CST < 250 μm). The correlation of CST of two groups was implemented with intraclass correlation coefficient (ICC, Supplementary Table S14)33. Generalized estimating equations (GEE) model was applied to account for the inter-eye correlation in both-eyes data34.

Criteria for inclusion included patients aged 18 years old or older; type I or II diabetes; CST value ≤ 325 μm by Zeiss stratus OCT. Exclusion criteria were proliferative diabetic retinopathy (PDR) according to the ETDRS Retinopathy Severity Scale, media opacity including vitreous hemorrhage and cataract; poor-quality OCTA images with signal strength index < 6/10; a recent history of intraocular surgery (< 4 months), such as vitreous hemorrhage or cataract; a history of focal macular laser or panrentinal photocoagulation; a history of intravitreal therapy including anti-VEGF and steroids; the presence of any other retinal disorder that leads to macular edema including uveitis, high myopia, epiretinal membrane, vitreomacular traction syndrome, ocular trauma, systemic disorders such as chronic renal insufficiency.

Study protocol

All participants underwent an ophthalmological evaluation, including best-correlated visual acuity (BCVA; logMAR visual acuity), axis length, intraocular pressure (IOP; non-contact tonometer), slit-lamp biomicroscopy, color fundus photography, OCT, OCTA and AOSLO. OCT was performed using Zeiss stratus OCT (Carl Zeiss Meditec, Dublin, California, USA) with a scanning area of 6 mm × 6 mm (512 A-scans × 128 B-scans, 68,000 A-scans per second) centered on the fovea, generating a macular thickness map of 6 × 6 mm213. CST values in the 1-mm-diameter ring were collected using a manually assisted technique of the program contained within the system software (Cirrus™ HD-OCT 5000, version 9.5.2.19038, http://www.zeiss.com). OCTA (Optovue RTVueXR, Fremont, CA, USA) was conducted using the 6mm × 6mm (400 × 400 A-scans, 70,000 A-scans per second) Amgio Retina model centered at fovea, and a series of quantitative OCTA metrics were analyzed using XR Avanti software (version 2018.1.1.63, http://www.optovue.com)35. We used 6mm × 6mm OCTA images to observe continuous high-reflective lines on the first and second high-reflective bands of the four outermost layers, and to assess the integrity of the EZ, and ELM, respectively. The software automatically separated capillary plexuses into superior capillary plexus (SCP), which is embedded in the ganglion cell layer and nerve fiber layer, the deep capillary plexus (DCP) in the inner nuclear layer, the outer retina (OR) in the RPE layer, and the choriocapillaris. The vessel density and FAZ area were measured automatically by software. Data including glycated hemoglobin A1c (HbA1c), total cholesterol, triglycerides, blood urea, blood pressure, proteinuria, serum creatinine, and estimated glomerular filtration rate (eGFR) was collected. Age, sex, diabetes duration, body mass index (BMI), history of medication, and insulin dosage were recorded.

AO camera-MONA II (Robotrak Technologies, China) was used to acquire images of cone and vascular characteristics from the fovea center. A total of 28 patients followed macular cone detection (21 patients had both eyes detected and 7 patients had one eye detected), and 11 patients followed vascular detection (8 patients had both eyes detected and 3 patients had one eye detected) using AOSLO. Retinal artery parameters were collected from 11 non-DME eyes and 8 early DME eyes. Cone parameters were collected from 28 non-DME eyes and 22 early DME eyes. Non-DME and early DME patients required 1% tropicamide to dilate the pupil before examination. For detecting photoreceptors, each MONA II examination captured scans of the four perifoveal areas of the retina, 3° off the center of the fovea, with a standardized sampling window size of 2.4° × 2.4°. Using the in-built software (Robotrak Mona II a, version 1.00.01.230714, https://www.robotrak.cn/#/home/zh), the data of cone density (the number of cones per square millimeter), cone spacing (the average distance between a cell and its nearest neighbor cell), cone dispersion (the ratio of the mean inter-cell distance to the variance of inter-cell distances), cone regularity ratio (the mean percentage of hexagonal cones), and hexagonal cones ratio (the mean percentage of cones showing optimal hexagonal) were automatically calculated and collected. For detecting arteies, images were taken from the upper side (4° superior, 3° nasal) and lower side (4° inferior, 3° nasal) of fovea. In order to achieve the highest quality results, we performed 3–4 scans on cone regions and arterioles for our research, then selected the highest quality data. By manually drawing a line perpendicular to the labeled vessel wall, and accurately positioning the inner and outer edges of the vessel wall, we obtained the numerical values for vessel diameter (VeD), vessel wall thickness (WT), lumen diameter (LD). The wall-to-lumen ratio (WLR) is calculated as WT/LD, and the cross-sectional area of the vascular wall (WCSA) is calculated as π(VeD/2)2 − π(LD/2)2. Each retinal arteriole with a size between 70 and 130 μm was measured at least three times, and the average of these measurements was recorded36,37.

Statistical analysis

The analysis presented continuous variables as the mean accompanied by the standard deviation (SD) or as the median with an interquartile range (Q1-Q3), depending on their distribution. The Student t-test was applied for normally distributed data, while the Mann–Whitney test was employed for data with non-normal distributions. Categorical variables were represented as counts and percentages. The statistical significance of categorical variables was assessed using Pearson's chi-square test or Fisher's exact test.

A GEE multivariate logistic regression was used to test the relationship between clinical variables and the presence of diabetic macular edema in the patient. The model was adjusted for variates with a P value of 0.10 or less. In addition, variates that were clinically relevant to the primary endpoint were included in the model regardless of their P value.

The outcomes were presented as adjusted odds ratios (ORs) accompanied by 95% confidence intervals (95% CIs). All hypothesis tests were two-sided, and statistical significance was defined as a P value < 0.05. Stata SE (version 13, Serial number 401306302851, https://www.stata.com/), R software (version 3.6.1, http://cran.r-project.org/), EmpowerStats (version 2.0, www.empowerstats.com), and GraphPad Prism (version 8.0.2, https://www.graphpad.com/scientific-software/prism/) were applied for the data analysis.

Results

Patient characteristics

The mean age of the 134 DM patients was 51.34 ± 14.4 (18–87) without significant age difference between groups (P = 0.998 as shown in Supplementary Table S1). As shown in Table 1, the mean best correlated visual acuity (BCVA) in the LogMAR scale was 0.16 ± 0.17 for right eyes (oculus dexter, OD) and 0.18 ± 0.24 for left eyes (oculus sinister, OS). The mean BCVA of the early DME group and the non-DME group showed no significant difference between groups (P = 0.363). Besides, IOP (P = 0.606) and axis length (P = 0.406) were not significantly different between groups. These results indicated that there was limited vision loss or no obvious clinical symptom in early DME patients. Table 1 OCTA parameter feature of early DME and non-DME eyes.

	ALL	Non-DME	Early DME	Wald χ2	P value	
OD (n = 127)	OS (n = 128)	OD (n = 61)	OS (n = 80)	OD (n = 66)	OS (n = 48)	
BCVA (log MAR)	0.16 (0.17)	0.18 (0.24)	0.17 (0.19)	0.19 (0.27)	0.15 (0.15)	0.16 (0.19)	0.83	0.363	
IOP (mmHg)	15.72 (3.17)	15.49 (2.65)	15.71 (2.82)	15.61 (2.78)	15.72 (3.49)	15.28 (2.43)	0.27	0.606	
Axis length (mm)	23.54 (0.59)	23.46 (0.64)	23.49 (0.57)	23.44 (0.65)	23.58 (0.61)	23.5 (0.62)	0.69	0.406	
CST (μm)	249.39 (21.93)	244.38 (24.34)	230.98 (12.69)	230.55 (18.09)	266.41 (13.1)	267.44 (13.5)	206.85	 < 0.001	
CCT (μm)	69.35 (8.83)	69.66 (9.05)	70.23 (8.37)	69.81 (9.12)	68.53 (9.23)	69.41 (9.02)	0.71	0.399	
FAZ area (mm2)	0.31 (0.12)	0.32 (0.12)	0.36 (0.11)	0.36 (0.11)	0.27 (0.11)	0.26 (0.11)	28.88	 < 0.001	
Superficial VD (%)	48.22 (4.51)	48.87 (4.77)	48.27 (4.13)	48.99 (4.53)	48.18 (4.86)	48.67 (5.19)	0.13	0.714	
Superficial parafovea VD (%)	49.9 (5.89)	50.36 (6.10)	50.24 (5.29)	50.5 (6.05)	49.59 (6.42)	50.13 (6.24)	0.45	0.504	
Superficial perifovea VD (%)	48.98 (4.60)	49.66 (5.06)	49.05 (4.25)	49.72 (4.84)	48.92 (4.93)	49.57 (5.46)	0.05	0.821	
Deep VD (%)	47.36 (6.83)	48.85 (7.53)	47.97 (6.77)	49.12 (7.68)	46.79 (6.89)	48.39 (7.32)	0.65	0.419	
Deep parafovea VD (%)	52.09 (5.61)	52.98 (6.15)	52.5 (5.83)	53.38 (6.41)	51.71 (5.40)	52.31 (5.69)	0.49	0.483	
Deep perifovea VD (%)	48.32 (7.57)	49.48 (8.39)	49.1 (7.44)	49.69 (8.77)	47.6 (7.66)	49.15 (7.80)	0.48	0.489	
CST, Central subfoveal thickness; FAZ, Foveal avascular zone; eGFR; Estimated glomerular filtration rate; VD, Vessel density.

In this study, 69.40% of the participants were male. Compared to non-DME patients, early DME patients were more likely to have lower HbA1c levels (P = 0.007). The treatment method (P = 0.902), cumulative insulin dosage (P = 0.722), and diabetes duration (P = 0.382) were not significantly different between groups. Besides, there was no significant difference between groups in their serum creatinine (P = 0.272), systolic blood pressure (SBP; P = 0.517), diastolic blood pressure (DBP; P = 0.614), BMI (P = 0.530), total cholesterol (P = 0.472), triglycerides (P = 0.529), blood urea (P = 0.728), eGFR (P = 0.387), proteinuria (P = 0.205), as shown in Supplementary Table S1. Comparison of characteristics among different types of DM are presented in Supplementary Table S2.

OCTA parameter feature of early DME and non-DME patients

The mean CST was 266.41 ± 13.1 μm (OD) and 267.44 ± 13.5 μm (OS) in the early DME group, 230.98 ± 12.69 μm (OD), and 230.55 ± 18.09 μm (OS) in the non-DME group. FAZ area was significantly decreased in the early DME group than in the non-DME group (P < 0.001). Superficial vessel density (P = 0.714 for whole superficial VD, P = 0.504 for superficial parafovea VD, P = 0.821 for superficial perifovea VD), deep vessel density (P = 0.419 for whole deep VD, P = 0.483 for deep parafovea VD, P = 0.489 for deep perifovea VD) were not significantly different between groups (Table 1 and Fig. 1). The averaged data of both eyes and OCTA features among different types of DM are presented in Supplementary Tables S3 and S4.Fig. 1 OCTA images of a non-DME and an early DME eyes. In this figure, the eye with early DME showed increased central subfoveal thickness (CST, 321 μm), small intraretinal cysts, well-recognizable inner retinal layers, intact ellipsoid zone (EZ), and external limiting membrane (ELM). In the early DME eye, the whole vessel density of superficial capillary plexus (SCP) and deep capillary plexus (DCP) was 40.2% and 52.0%, and the foveal avascular zone (FAZ) area was 0.295 mm2. The eye with non-DME showed normal CST (235 μm), retinal morphology and structure. In the non-DME eye, the whole vessel density of SCP and DCP was 43.9% and 47.9%, and the FAZ area was 0.394 mm2.

Associations between risk factors and the presence of early DME in DM patients

Table 2 presents the relationships between DME-related risk factors and early DME development. In the univariate analysis, HbA1c level ≤ 8% (P = 0.005; odds ratio [OR] = 0.39; 95% confidence interval [95% CI] 0.21–0.75), FAZ area ≤ 0.3 mm2 (P = 0.001; OR = 0.41; 95% CI 0.27–0.65) were significantly associated with a higher risk of early DME. The associations remained significant for HbA1c level (P = 0.005; OR = 0.37; 95% CI 0.19–0.74) and FAZ area (P < 0.001; OR = 0.41; 95% CI 0.26–0.67) in the multivariate analysis. Table 2 Associations between risk factors, OCTA metrics, and the presence of DME.

	Statistics	Univariate analysis	Multivariate analysis	
OR (95%CI)	P value	OR (95%CI)	P value	
Treatment		1.04 (0.70, 1.57)	0.833			
Age (≥ 55years)	121 (47.45%)	0.86 (0.46, 1.62)	0.639			
Sex (female)	81 (31.76%)	0.50 (0.25, 0.99)	0.047	0.66 (0.28, 1.55)	0.338	
Cumulative insulin dosage (≥ 30,000U)	64 (25.10%)	1.76 (0.87, 3.57)	0.116			
HbA1c (> 8%)	133 (52.16%)	0.39 (0.21, 0.75)	0.005	0.37 (0.19, 0.74)	0.005	
Total cholesterol (> 5.7mmol/L)	39 (15.29%)	0.72 (0.29, 1.77)	0.478			
Triglycerides (> 2.25 mmol/L)	44 (17.25%)	1.21 (0.54, 2.76)	0.642			
Blood urea (> 8.2 mmol/L)	24 (9.41%)	1.02 (0.40, 2.61)	0.971			
Diabetes duration (> 6 years)	119 (46.67%)	1.06 (0.57, 1.99)	0.852			
SBP (> 140 mmHg)	41 (16.08%)	1.05 (0.46, 2.40)	0.901			
DBP (> 90 mmHg)	23 (9.02%)	1.31 (0.40, 4.27)	0.650			
BMI (> 24)	151 (59.22%)	0.92 (0.49, 1.74)	0.804			
eGFR (> 90mL/min/1.73 m2)	206 (80.78%)	0.62 (0.28, 1.36)	0.229			
Proteinuria (> 100 mg/L)	111 (43.53%)	0.89 (0.47, 1.68)	0.724			
Serum creatinine (> 60 μmol/L)	149 (58.43%)	1.91 (1.00, 3.64)	0.051	1.37 (0.64, 2.92)	0.418	
FAZ area (> 0.3 mm2)	141 (55.29%)	0.41 (0.27, 0.65)	0.001	0.41 (0.26, 0.67)	 < 0.001	
Superficial VD (> 49.2%)	126 (49.41%)	0.97 (0.59, 1.60)	0.903			
Superficial parafovea VD (> 50%)	150 (58.82%)	0.93 (0.60, 1.47)	0.767			
Superficial perifovea VD (> 50%)	125 (49.02%)	0.96 (0.57, 1.62)	0.890			
Deep VD (> 48%)	131 (51.37%)	0.94 (0.58, 1.51)	0.800			
Deep parafovea VD (> 53%)	130 (50.98%)	0.82 (0.55, 1.24)	0.3494			
Deep perifovea VD (> 50%)	115 (45.10%)	0.97 (0.59, 1.60)	0.9150			
SBP, Systolic blood pressure; DBP, Diastolic blood pressure; BM, Body mass index; SCP, Superficial capillary plexus; DCP, Deep capillary plexus; CST, Central subfoveal thickness; FAZ, Foveal avascular zone; eGFR, Estimated glomerular filtration rate; VD, Vessel density; OD, Odds ratio; 95% CI, 95% Confidence interval.

GEE linear regression of FAZ area

GEE linear regression analysis results showed that FAZ area was correlated with sex (P = 0.047; coefficient 0.0399; 95% CI 0.0005–0.0793) but was not correlated with cumulative insulin dosage (P = 0.653), age (P = 0.421), HbA1c level (P = 0.095), as shown in Table 3. Table 3 GEE linear regression of FAZ area.

	Coefficient	SE	z	P value	95% CI	
Insulin dosage group	0.0084	0.0187	0.45	0.653	 − 0.0283, 0.0452	
Age (≥ 55years)	0.0151	0.0187	0.81	0.421	 − 0.0216, 0.0518	
Sex (female)	0.0399	0.0201	1.98	0.047	0.0005, 0.0793	
Hba1c (> 8%)	0.0312	0.0186	1.67	0.095	 − 0.0054, 0.0677	
FAZ, Foveal avascular zone; Hba1c, Glycated haemoglobin A1c; SE, Standard error; 95% CI, 95% Confidence interval.

Cone parameters among early DME and non-DME patients

There was no significant difference in the average cone density in all four retinal locations between early DME and non-DME patients: 11,676.21 ± 2899.8 vs. 14,194.64 ± 2625.05 cells/mm2 (OD) and 14,630.62 ± 4909.16 vs. 13,385.44 ± 2206.45 cells/mm2 (OS) in the inferior (P = 0.481), 12,602.57 ± 3012.96 vs. 12,849.5 ± 2164.08 cells/mm2 (OD) and 14,172.88 ± 3468.95 vs. 13,471.56 ± 3231.61 cells/mm2 (OS) in the superior (P = 0.294), 14,628.36 ± 3077.04 vs. 14,934.83 ± 2379.2 cells/mm2 (OD) and 15,459.38 ± 5907.4 vs. 15,986.94 ± 3206.94 cells/mm2 (OS) in the temporal (P = 0.792), 13,457.14 ± 4322.94 vs. 15,379.00 ± 3503.42 cells/mm2 (OD) and 15,624.75 ± 2766.39 vs. 15,660.5 ± 3114.64 cells/mm2 (OS) in the nasal quadrant (P = 0.346). In addition, The cone regularity, spacing, dispersion, and hexagonal cone ratio were additionally assessed with no significant results in the temporal, nasal, inferior, and superior quadrants in the two groups (Supplementary Table S5 and Fig. 2).Fig. 2 OCTA and AOSLO images of a non-DME and an early DME eyes. In the OCTA images of the macula from both non-DME and early DME eyes, intact external limiting membrane (ELM, red arrow) and ellipsoid zone (EZ, blue arrow) can be observed. Besides, the foveal avascular zone (FAZ) area of the early DME eye (0.287 mm2) is smaller than the FAZ area of the non-DME eye (0.372 mm2). Retinal artery images were taken from the upper side (4°superior, 3°nasal) and lower side (4°inferior, 3°nasal) of fovea (green dotted squares). The vessel diameter (VeD, 78.74 μm), wall thickness (WT, 49.40 μm), wall-to-lumen ratio (WLR, 0.39), and the cross-sectional area of the vascular wall (WCSA, 1794.40 mm2) in the upper side of the early DME eye was decreased than the non-DME eye (VeD, 79.02 μm; WT, 60.14 μm; WLR, 3.18; WCSA, 4624.46 mm2). Lumen diameter (LD) are labeled in this figure. Photoreceptor images were captured at 3°offset from the center of the fovea (indicated by the red dotted circle) in the nasal, superior, temporal and inferior quadrants (blue dotted squares).

Retinal artery parameters among early DME and non-DME patients

As shown in Table 4 and Fig. 2, the mean vessel diameter in the upper side was significantly decreased in the early DME group than in the non-DME group (82.31 ± 23.22 vs. 93.12 ± 20.46 μm in OD, 78.74 vs. 88.60 ± 16.28 μm in OS, P = 0.001). Meanwhile, the WT, WLR, and WCSA in the upper side were also significantly decreased in the early DME group than in the non-DME group (for WT 32.36 ± 26.95 vs. 59.17 ± 10.18 μm in OD, 19.34 vs. 24.31 ± 5.95 μm in OS, P < 0.001; for WLR 0.76 ± 0.83 vs. 1.94 ± 0.83 in OD, 0.39 vs. 0.38 ± 0.05 in OS, P = 0.005; for WCSA 3552.06 ± 3208.31 vs. 6054.01 ± 2609.92 μm2 in OD, 1794.4 vs. 3011.77 ± 1283.76 μm2 in OS, P = 0.003). However, there were no significant differences in the total vessel diameter, wall thickness, or wall-to-lumen ratio between the two groups on the lower side. The mean lumen diameter was not significantly different between both groups in the upper side (P = 0.071) and lower side (P = 0.871). Table 4 Retinal artery parameters among early DME and non-DME eyes.

	ALL	Non-DME	Early DME	Wald χ2	Norminal P value	
OD	OS	OD	OS	OD	OS	
Vessel wall thickness on the upper side (μm)	
 N	8	6	4	5	4	1			
 Mean (SD)	45.76 (23.69)	23.48 (5.69)	59.17 (10.18)	24.31 (5.95)	32.36 (26.95)	19.34 ()	16.83	 < 0.001	
Lumen diameter on the upper side (μm)	
 N	8	6	4	5	4	1			
 Mean (SD)	41.95 (15.38)	61.80 (11.47)	33.95 (12.89)	64.28 (10.88)	49.95 (14.68)	49.4 ()	0.14	0.071	
Vessel diameter on the upper side(μm)	
 N	8	6	4	5	4	1			
 Mean (SD)	87.71 (21.07)	85.29 (16.67)	93.12 (20.46)	88.6 (16.28)	82.31 (23.22)	78.74 ()	11.37	0.001	
Wall-to-lumen ratio on the upper side	
 N	8	6	4	5	4	1			
 Mean (SD)	1.35 (0.99)	0.38 (0.05)	1.94 (0.83)	0.38 (0.05)	0.76 (0.83)	0.39 ()	7.81	0.005	
Cross-sectional area of the vascular wall on the upper side (μm2)	
 N	8	6	4	5	4	1			
 Mean (SD)	4803.03 (3019.8)	2808.88 (1251.18)	6054.01 (2609.92)	3011.77 (1283.76)	3552.06 (3208.31)	1794.4 ()	9.08	0.003	
Blood flow rate in the upper side (mm/s)	
 N	7	6	3	5	4	1			
 Mean (SD)	34.42 (3.66)	28.69 (7.54)	33.10 (3.52)	30.09 (7.51)	35.42 (3.93)	21.72 ()	0.59	0.441	
Vessel wall thickness on the lower side (μm)	
 N	8	9	4	6	4	3			
 Mean (SD)	36.51 (27.36)	33.24 (13.8)	46.71 (35.97)	35.63 (14.4)	26.31 (13.26)	28.45 (13.84)	2.08	0.150	
Lumen diameter on the lower side (μm)	
 N	8	9	4	6	4	3			
 Mean (SD)	59.73 (22.66)	55.16 (16.21)	56.75 (22.47)	49.91 (16.68)	62.71 (25.87)	65.67 (10.3)	0.03	0.871	
Vessel diameter on the lower side (μm)	
 N	8	9	4	6	4	3			
 Mean (SD)	96.13 (20.48)	88.40 (15.77)	103.24 (14.28)	85.54 (14.16)	89.02 (25.3)	94.12 (20.5)	0.00	0.949	
Wall-to-lumen ratio on the lower side	
 N	8	9	4	6	4	3			
 Mean (SD)	0.93 (1.32)	0.76 (0.68)	1.37 (1.84)	0.93 (0.79)	0.49 (0.38)	0.43 (0.18)	3.60	0.058	
Cross-sectional area of the vascular wall on the lower side (μm2)	
 N	8	9	4	6	4	3			
 Mean (SD)	4407.71 (3122.93)	3738.03 (1746.94)	5697.6 (3969.62)	3739.66 (1663.88)	3117.82 (1600.5)	3734.77 (2299.1)	0.95	0.331	
Blood flow rate in the lower side (mm/s)	
 N	8	9	4	6	4	3			
 Mean (SD)	39.24 (27.86)	32 (9.39)	30.69 (4.64)	33.35 (10.83)	47.8 (39.93)	29.3 (6.6)	0.59	0.444	
SD, Standard deviation.

Correlation between cone and artery parameters and associated factors

The relationships between changes in cone and artery parameters and factors, including Hba1c, BCVA, sex, superficial and deep vessel density were determined with Spearman correlation analysis (Supplementary Tables S6–S13). Our results showed that the cone density in the superior quadrant was weekly correlated with HbA1c level (r = 0.317, P = 0.025). The vessel wall thickness on the upper side was correlated with superficial parafovea VD (r = 0.543, P = 0.048), deep VD (r = 0.556, P = 0.042), deep perifovea VD (r = 0.565, P = 0.038). The wall-to-lumen ratio on the upper side was correlated with superficial parafovea VD (r = 0.541, P = 0.046) and deep VD (r = 0.616, P = 0.019).

Discussion

While most researchers laid focus on CSME and DME at advanced and severe stages6,16,17,19–21, this study unveiled the macular vascular change and cone features at the beginning of DME formation, with no obvious clinical symptom.

The vessel density of the SCP, DCP, and FAZ areas indicate macular perfusion. Hyperreflective foci or dots within retinal layers (iHRF/iHRD) are complex mixture containing migrating RPE and lipid material that indicate the breakdown of the inner blood-retinal barrier (BRB) and microvascular damage6,38. Microaneurysms in the inner nuclear layer indicate microvascular lesions and microaneurysms leakage. Among the above OCTA metrics, only FAZ area and microaneurysm numbers were found to be significantly different between early DME and non-DME patients. What’s more, FAZ area ≤ 0.3 mm2 was found to be associated with a higher risk of early DME. Firstly, early DME patients showed intact ELM, EZ, and RPE in OCT and OCTA images, and there was no significant iHRF/iHRD difference when compared with non-DME patients. So, BRB was supposed to be intact in early DME participants. Secondly, it has been widely accepted that the FAZ area in DR and DME patients was larger in comparison with non-DME patients35,39–41. However, these studies focused on advanced and severe DME in CSME. Our findings suggest that although there are no obvious clinical symptoms at the onset of DME, there may be a compensatory increase of macular perfusion, which manifests as FAZ area reduction. As DME progresses, the FAZ area increases, and macular perfusion reduces. Our results also suggested that CST ≥ 250 μm and < 325 μm and FAZ ≤ 0.3 mm2 may be an indicator for early DME detection during DR screening.

Our data showed no correlation between FAZ area and cumulative insulin dosage, age, sex, HbA1c level, and diabetes duration. This result is supported by a previous study showing no correlation between FAZ area and age, diabetic duration, HbA1c level, BCVA, CST, and DR severity in DR patients42. Another study reported a significant correlation between the FAZ area and diabetic duration in DR patients18. In normal eyes, the FAZ area was found to correlate with age43. Further prospective studies with large samples are needed to investigate the factors associated with FAZ area reduction.

It has been reported that an increase in HbA1c level was associated with a higher risk of CSME44,45. What’s more, lower glycosylated hemoglobin at baseline was associated with retinopathy improvement46. A previous study showed that in DM patients with minimum or no diabetic retinopathy, no significant CST difference was found between patients with HbA1c < 8% and HbA1c ≥ 8%10. In this study, an inverse relation was found between HbA1c level and early DME development: DM patients with HbA1c ≤ 8% were more likely to have early DME than those with HbA1c > 8%. The first interpretation is that hyperglycemia, as measured by HbA1c, might show a relative “protective” effect at the onset of DME development by increasing plasma osmolarity and inducing dehydration. The second possible reason is that this result may be influenced by sample size and study design.

In this study, we analyzed retinal photoreceptor (cone) features and vascular change with AOSLO in early DME patients, which has not been previously investigated37,47,48. Previous researches reported a significant decreased cone density in DM, moderate and severe NPDR, PDR patients when compared with healthy participants49–51. In adolescents, no significant difference in cone density was observed between DM patients and healthy participants52. What’s more, cone density was not significantly different between prediabetic and healthy participants37. Our findings revealed no significant differences in cone parameters between early DME and non-DME patients. Also, we found that cone density in the superior quadrant was correlated with HbA1c level. This result indicates that at the early stage of DME formation, high glucose-induced photoreceptor impairment at the macula did not progress further.

However, our results showed obvious signs of vascular anatomical changes that may lead to functional alterations of vessels in the early DME group with significantly decreased vessel diameter, WT, WLR, and WCSA in the upper side (superotemporal region). Previous studies showed that WT, WLR and WCSA in DM patients with and without DR was significantly higher than healthy people53,54. Narrowing of arterioles lumen was observed in prediabetes and DM patients, which indicates smooth muscle cell proliferation and vascular fibrosis55. In this study, no significant differences in vessel parameters were observed in the lower sides (inferotemporal region) of early DME and non-DME eyes. The retinal arteries in the upper side were branches of superotemporal retinal artery. A previous study indicated that the vessel diameter was slightly lower and the average velocity was slightly higher in the arteries of the superotemporal region of retina compared to the inferotemporal region in healthy human subjects56. At the onset of DME, hyperglycemia induces excessive production of mitochondrial reactive oxygen species (ROS), leading to the production of angiotensin, which causes vasoconstriction and promotes inflammation57,58. With a smaller vessel diameter, constriction and dysregulation of the superotemporal retinal arteries may cause more sever ischemic and hypoxic condition than the inferotemporal retinal arteries. In addition, we cannot exclude that this result is due to the small sample size. Obtaining high-quality AOSLO images is challenging in patients with DME and DR, because of the requirement for patients to have good fixation ability and prolonged cooperation during examinations. Our study suggested a vascular spasm or vasoconstriction in the superotemporal region of the macula at the early stage of DME formation, which was consistent with FAZ area results.

There are some limitations of this study. Central subfovea is nourished by diffusion of choroidal circulation. So, it would be better if chorioidal parameters were investigated. However, current automated and manual segmentation methods of choriocapillaris layer were still inaccurate and unconvincing59–61. Other limitations include a relatively small sample size and the cross-sectional study design.

Part of this manuscript has been preprinted62. After being made public through a preprint server, comments from specialists in ophthalmology and endocrinology were received. Compliments were made to find the characterized OCTA metrics as non-invasive and convenient indicators for early DME detection. Suggestions were given for using the GEE model in statistical analysis, according to which we revised this manuscript.

In summary, this study indicated that the primary macular vascular change at the onset of DME formation was vascular spasm or vasoconstriction with FAZ area and vessel diameter reduction. Glucose-associated photoreceptor damage was limited at the onset of DME formation. CST ≥ 250 μm and FAZ ≤ 0.3 mm2 may be the indicators for early DME detection and could be applied in DR screening.

Supplementary Information

Supplementary Tables.

Abbreviations

DM Diabetes mellitus

DR Diabetic retinopathy

DME Diabetic macular edema

CSME Clinically significant macular edema

OCT Optical coherence tomography

SD-OCT Spectral domain optical coherence tomography

OCTA Optical coherence tomography angiography

AO Adaptive optics

AOSLO Adaptive optics scanning laser ophthalmoscope

SBP Systolic blood pressure

DBP Diastolic blood pressure

BMI Body mass index

HbA1c Glycated hemoglobin A1c

eGFR Estimated glomerular filtration rate

BCVA Best-correlated visual acuity

SCP Superficial capillary plexus

DCP Deep capillary plexus

CST Central subfoveal thickness

iHRF/iHRD Intraretinal hyperreflective foci or dots

FAZ Foveal avascular zone

VD Vessel density

RPE Retinal pigment epithelium

EZ Ellipsoid zone

ELM External limiting membrane

BRB Blood-retinal barrier

VeD Vessel diameter

WT Vessel wall thickness

LD Lumen diameter

WLR Wall-to-lumen ratio

WCSA Cross-sectional area of the vascular wall

OD Oculus dexter

OS Oculus sinister

GEE Generalized estimating equations

OR Odds ratio

SD Standard deviation

95% CI 95% Confidence intervals

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71286-6.

Acknowledgements

This research was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital with Nanjing Medical University (NO. 2021-SE-406) on 24th November 2021. All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects and/or their legal guardian(s).We thank colleagues from the Ethics Committee of Jiangsu Provincial People’s Hospital for their support and supervision. We appreciate Advanced Ophthalmology Laboratory (AOL), Robotrak Technologies, Nanjing, China, for generously providing AOSLO instruments free of charge and assisting with the analysis.

Author contributions

Conceptualization and methodology were carried out by H.S., Q.H.L., and P.C.; investigation was performed by H.S., Q.Y.G., T.P., J.L.H., and K.Z.; original draft writing and formal analysis were conducted by H.S. and R.W.C.; manuscript review and editing were performed by H.S. and Y.Y.; statistical analysis was conducted by Y.Y. and J.Y.Z.; funding was acquired by H.S. and Q.H.L. All authors have seen and approved the final version of the manuscript for publication. All authors reviewed the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (82101151, 82271100); Natural Science Foundation of Jiangsu Province (BK20210972).

Data availability

The raw data of this study is available to access upon reasonable request.

Competing interests

The authors declare no competing interests.

Publisher's note

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

These authors contributed equally: Qinyuan Gu and Ting Pan.
==== Refs
References

1. Teo Z Global prevalence of diabetic retinopathy and projection of burden through 2045: Systematic review and meta-analysis Ophthalmology 2021 128 1580 1591 10.1016/j.ophtha.2021.04.027 33940045
Teo, Z. et al. Global prevalence of diabetic retinopathy and projection of burden through 2045: Systematic review and meta-analysis. Ophthalmology 128, 1580–1591 (2021).33940045 10.1016/j.ophtha.2021.04.027
2. Yau J Global prevalence and major risk factors of diabetic retinopathy Diabet. Care 2012 35 556 564 10.2337/dc11-1909
Yau, J. et al. Global prevalence and major risk factors of diabetic retinopathy. Diabet. Care 35, 556–564 (2012).10.2337/dc11-1909
3. Bourne R Causes of vision loss worldwide, 1990–2010: A systematic analysis Lancet Glob. Health 2013 1 e339 349 10.1016/S2214-109X(13)70113-X 25104599
Bourne, R. et al. Causes of vision loss worldwide, 1990–2010: A systematic analysis. Lancet Glob. Health 1, e339-349 (2013).25104599 10.1016/S2214-109X(13)70113-X
4. Leasher J Global estimates on the number of people blind or visually impaired by diabetic retinopathy: A meta-analysis from 1990 to 2010 Diabet. Care 2016 39 1643 1649 10.2337/dc15-2171
Leasher, J. et al. Global estimates on the number of people blind or visually impaired by diabetic retinopathy: A meta-analysis from 1990 to 2010. Diabet. Care 39, 1643–1649 (2016).10.2337/dc15-2171
5. Cheung N Mitchell P Wong T Diabetic retinopathy Lancet (London, England). 2010 376 124 136 10.1016/S0140-6736(09)62124-3 20580421
Cheung, N., Mitchell, P. & Wong, T. Diabetic retinopathy. Lancet (London, England). 376, 124–136 (2010).20580421 10.1016/S0140-6736(09)62124-3
6. Sen S Ramasamy K Sivaprasad S Indicators of visual prognosis in diabetic macular oedema J. Pers. Med. 2021 11 449 10.3390/jpm11060449 34067442
Sen, S., Ramasamy, K. & Sivaprasad, S. Indicators of visual prognosis in diabetic macular oedema. J. Pers. Med. 11, 449 (2021).34067442 10.3390/jpm11060449
7. Panozzo G An optical coherence tomography-based grading of diabetic maculopathy proposed by an international expert panel: The European School for Advanced Studies in Ophthalmology classification Eur. J. Ophthalmol. 2020 30 8 18 10.1177/1120672119880394 31718271
Panozzo, G. et al. An optical coherence tomography-based grading of diabetic maculopathy proposed by an international expert panel: The European School for Advanced Studies in Ophthalmology classification. Eur. J. Ophthalmol. 30, 8–18 (2020).31718271 10.1177/1120672119880394
8. Hanumunthadu D Agreement between spectral-domain and swept-source optical coherence tomography retinal thickness measurements in macular and retinal disease Ophthalmol. Ther. 2021 10 913 922 10.1007/s40123-021-00377-8 34324166
Hanumunthadu, D. et al. Agreement between spectral-domain and swept-source optical coherence tomography retinal thickness measurements in macular and retinal disease. Ophthalmol. Ther. 10, 913–922 (2021).34324166 10.1007/s40123-021-00377-8
9. Friedman S Topical nepafenec in eyes with noncentral diabetic macular edema Retina. 2015 35 944 956 10.1097/IAE.0000000000000403 25602634
Friedman, S. et al. Topical nepafenec in eyes with noncentral diabetic macular edema. Retina. 35, 944–956 (2015).25602634 10.1097/IAE.0000000000000403
10. Bressler N Retinal thickness on Stratus optical coherence tomography in people with diabetes and minimal or no diabetic retinopathy Am. J. Ophthalmol. 2008 145 894 901 10.1016/j.ajo.2007.12.025 18294608
Bressler, N. et al. Retinal thickness on Stratus optical coherence tomography in people with diabetes and minimal or no diabetic retinopathy. Am. J. Ophthalmol. 145, 894–901 (2008).18294608 10.1016/j.ajo.2007.12.025
11. Mahajan V Management of sympathetic ophthalmia with the fluocinolone acetonide implant Ophthalmology. 2009 116 552 557.e551 10.1016/j.ophtha.2008.10.024 19147232
Mahajan, V. et al. Management of sympathetic ophthalmia with the fluocinolone acetonide implant. Ophthalmology. 116, 552-557.e551 (2009).19147232 10.1016/j.ophtha.2008.10.024
12. Konstantina S Comparison of SDOCT scan types for grading disorganization of retinal inner layers and other morphologic features of diabetic macular edema Transl. Vis. Sci. Technol. 2020 9 45 10.1167/tvst.9.8.45
Konstantina, S. et al. Comparison of SDOCT scan types for grading disorganization of retinal inner layers and other morphologic features of diabetic macular edema. Transl. Vis. Sci. Technol. 9, 45 (2020).10.1167/tvst.9.8.45
13. Chalam K Retinal thickness in people with diabetes and minimal or no diabetic retinopathy: Heidelberg Spectralis optical coherence tomography Investig. Ophthalmol. Vis. Sci. 2012 53 8154 8161 10.1167/iovs.12-10290 23132803
Chalam, K. et al. Retinal thickness in people with diabetes and minimal or no diabetic retinopathy: Heidelberg Spectralis optical coherence tomography. Investig. Ophthalmol. Vis. Sci. 53, 8154–8161 (2012).23132803 10.1167/iovs.12-10290
14. Sampani K Comparison of SDOCT scan types for grading disorganization of retinal inner layers and other morphologic features of diabetic macular edema Transl. Vis. Sci. Technol. 2020 9 45 10.1167/tvst.9.8.45 32855891
Sampani, K. et al. Comparison of SDOCT scan types for grading disorganization of retinal inner layers and other morphologic features of diabetic macular edema. Transl. Vis. Sci. Technol. 9, 45 (2020).32855891 10.1167/tvst.9.8.45
15. Dimitrova G Chihara E Takahashi H Amano H Okazaki K Quantitative retinal optical coherence tomography angiography in patients with diabetes without diabetic retinopathy Investig. Ophthalmol. Vis. Sci. 2017 58 190 196 10.1167/iovs.16-20531 28114579
Dimitrova, G., Chihara, E., Takahashi, H., Amano, H. & Okazaki, K. Quantitative retinal optical coherence tomography angiography in patients with diabetes without diabetic retinopathy. Investig. Ophthalmol. Vis. Sci. 58, 190–196 (2017).28114579 10.1167/iovs.16-20531
16. Sun Z OCT angiography metrics predict progression of diabetic retinopathy and development of diabetic macular edema: A prospective study Ophthalmology. 2019 126 1675 1684 10.1016/j.ophtha.2019.06.016 31358386
Sun, Z. et al. OCT angiography metrics predict progression of diabetic retinopathy and development of diabetic macular edema: A prospective study. Ophthalmology. 126, 1675–1684 (2019).31358386 10.1016/j.ophtha.2019.06.016
17. Han R Gong R Liu WXuG Optical coherence tomography angiography metrics in different stages of diabetic macular edema Eye Vis. 2022 9 14 10.1186/s40662-022-00286-2
Han, R., Gong, R. & Liu, WXu. G. Optical coherence tomography angiography metrics in different stages of diabetic macular edema. Eye Vis. 9, 14 (2022).10.1186/s40662-022-00286-2
18. Fernández-Espinosa G Retinal vascularization abnormalities studied by optical coherence tomography angiography (OCTA) in type 2 diabetic patients with moderate diabetic retinopathy Diagnostics 2022 12 379 10.3390/diagnostics12020379 35204470
Fernández-Espinosa, G. et al. Retinal vascularization abnormalities studied by optical coherence tomography angiography (OCTA) in type 2 diabetic patients with moderate diabetic retinopathy. Diagnostics 12, 379 (2022).35204470 10.3390/diagnostics12020379
19. Mirshahi R Differentiating features of OCT angiography in diabetic macular edema Sci. Rep. 2021 11 23398 10.1038/s41598-021-02859-y 34862410
Mirshahi, R. et al. Differentiating features of OCT angiography in diabetic macular edema. Sci. Rep. 11, 23398 (2021).34862410 10.1038/s41598-021-02859-y
20. Ayman GE Alia MN Ahmed AA-K Osama AS David JR Optical coherence tomography angiography biomarkers predict anatomical response to bevacizumab in diabetic macular edema Diabet. Metab. Syndr. Obes. 2022 15 395 405 10.2147/DMSO.S351618
Ayman, G. E., Alia, M. N., Ahmed, A.A.-K., Osama, A. S. & David, J. R. Optical coherence tomography angiography biomarkers predict anatomical response to bevacizumab in diabetic macular edema. Diabet. Metab. Syndr. Obes. 15, 395–405 (2022).10.2147/DMSO.S351618
21. Wei L Microvascular changes after conbercept intravitreal injection of PDR with or without center-involved diabetic macular edema analyzed by OCTA Front. Med. 2022 9 797087 10.3389/fmed.2022.797087
Wei, L. et al. Microvascular changes after conbercept intravitreal injection of PDR with or without center-involved diabetic macular edema analyzed by OCTA. Front. Med. 9, 797087 (2022).10.3389/fmed.2022.797087
22. Neelakshi B Ruben AG Arthur T Marco AZ Diabetic macular edema: Pathogenesis and treatment Surv. Ophthalmol. 2009 54 1 32 10.1016/j.survophthal.2008.10.001 19171208
Neelakshi, B., Ruben, A. G., Arthur, T. & Marco, A. Z. Diabetic macular edema: Pathogenesis and treatment. Surv. Ophthalmol. 54, 1–32 (2009).19171208 10.1016/j.survophthal.2008.10.001
23. Kupis M Wawrzyniak ZM Szaflik JP Zaleska-Zmijewska A Retinal photoreceptors and microvascular changes in the assessment of diabetic retinopathy progression: A two-year follow-up study Diagnostics 2023 13 2513 10.3390/diagnostics13152513 37568876
Kupis, M., Wawrzyniak, Z. M., Szaflik, J. P. & Zaleska-Zmijewska, A. Retinal photoreceptors and microvascular changes in the assessment of diabetic retinopathy progression: A two-year follow-up study. Diagnostics 13, 2513 (2023).37568876 10.3390/diagnostics13152513
24. Zaleska-Zmijewska A Wawrzyniak ZM Dabrowska A Szaflik JP Adaptive optics (rtx1) high-resolution imaging of photoreceptors and retinal arteries in patients with diabetic retinopathy J. Diabet. Res. 2019 2019 9548324 10.1155/2019/9548324
Zaleska-Zmijewska, A., Wawrzyniak, Z. M., Dabrowska, A. & Szaflik, J. P. Adaptive optics (rtx1) high-resolution imaging of photoreceptors and retinal arteries in patients with diabetic retinopathy. J. Diabet. Res. 2019, 9548324 (2019).10.1155/2019/9548324
25. Fang D Morphologic and functional assessment of photoreceptors in laser-induced retinopathy using adaptive optics scanning laser ophthalmoscopy and microperimetry Am. J. Ophthalmol. 2024 265 61 72 10.1016/j.ajo.2024.03.021 38555010
Fang, D. et al. Morphologic and functional assessment of photoreceptors in laser-induced retinopathy using adaptive optics scanning laser ophthalmoscopy and microperimetry. Am. J. Ophthalmol. 265, 61–72 (2024).38555010 10.1016/j.ajo.2024.03.021
26. Chui TYP Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy Int. J. Retina Vitreous 2016 2 11 10.1186/s40942-016-0037-8 27847629
Chui, T. Y. P. et al. Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy. Int. J. Retina Vitreous 2, 11 (2016).27847629 10.1186/s40942-016-0037-8
27. Karst SG Characterization of in vivo retinal lesions of diabetic retinopathy using adaptive optics scanning laser ophthalmoscopy Int. J. Endocrinol. 2018 2018 7492946 10.1155/2018/7492946 29853882
Karst, S. G. et al. Characterization of in vivo retinal lesions of diabetic retinopathy using adaptive optics scanning laser ophthalmoscopy. Int. J. Endocrinol. 2018, 7492946 (2018).29853882 10.1155/2018/7492946
28. Burns SA Elsner AE Sapoznik KA Warner RL Gast TJ Adaptive optics imaging of the human retina Prog. Retin. Eye Res. 2019 68 1 30 10.1016/j.preteyeres.2018.08.002 30165239
Burns, S. A., Elsner, A. E., Sapoznik, K. A., Warner, R. L. & Gast, T. J. Adaptive optics imaging of the human retina. Prog. Retin. Eye Res. 68, 1–30 (2019).30165239 10.1016/j.preteyeres.2018.08.002
29. Chui TY Gast TJ Burns SA Imaging of vascular wall fine structure in the human retina using adaptive optics scanning laser ophthalmoscopy Investig. Ophthalmol. Vis. Sci. 2013 54 7115 7124 10.1167/iovs.13-13027 24071955
Chui, T. Y., Gast, T. J. & Burns, S. A. Imaging of vascular wall fine structure in the human retina using adaptive optics scanning laser ophthalmoscopy. Investig. Ophthalmol. Vis. Sci. 54, 7115–7124 (2013).24071955 10.1167/iovs.13-13027
30. Nesper PL Scarinci F Fawzi AA Adaptive optics reveals photoreceptor abnormalities in diabetic macular ischemia PLoS One. 2017 12 e0169926 10.1371/journal.pone.0169926 28068435
Nesper, P. L., Scarinci, F. & Fawzi, A. A. Adaptive optics reveals photoreceptor abnormalities in diabetic macular ischemia. PLoS One. 12, e0169926 (2017).28068435 10.1371/journal.pone.0169926
31. Torm MEW Detection of capillary abnormalities in early diabetic retinopathy using scanning laser ophthalmoscopy and optical coherence tomography combined with adaptive optics Sci. Rep. 2024 14 13450 10.1038/s41598-024-63749-7 38862584
Torm, M. E. W. et al. Detection of capillary abnormalities in early diabetic retinopathy using scanning laser ophthalmoscopy and optical coherence tomography combined with adaptive optics. Sci. Rep. 14, 13450 (2024).38862584 10.1038/s41598-024-63749-7
32. Giacomo P An optical coherence tomography-based grading of diabetic maculopathy proposed by an international expert panel: The European School for Advanced Studies in Ophthalmology classification Eur. J. Ophthalmol. 2019 30 8 18 31718271
Giacomo, P. et al. An optical coherence tomography-based grading of diabetic maculopathy proposed by an international expert panel: The European School for Advanced Studies in Ophthalmology classification. Eur. J. Ophthalmol. 30, 8–18 (2019).31718271
33. Richard AA Statistical guidelines for the analysis of data obtained from one or both eyes Ophthalmic Physiol. Opt. 2012 33 7 14
Richard, A. A. Statistical guidelines for the analysis of data obtained from one or both eyes. Ophthalmic Physiol. Opt. 33, 7–14 (2012).
34. Ying G Maguire M Glynn R Rosner B Tutorial on biostatistics: Longitudinal analysis of correlated continuous eye data Ophthalmic Epidemiol. 2021 28 3 20 10.1080/09286586.2020.1786590 32744149
Ying, G., Maguire, M., Glynn, R. & Rosner, B. Tutorial on biostatistics: Longitudinal analysis of correlated continuous eye data. Ophthalmic Epidemiol. 28, 3–20 (2021).32744149 10.1080/09286586.2020.1786590
35. Samara W Quantification of diabetic macular ischemia using optical coherence tomography angiography and its relationship with visual acuity Ophthalmology. 2017 124 235 244 10.1016/j.ophtha.2016.10.008 27887743
Samara, W. et al. Quantification of diabetic macular ischemia using optical coherence tomography angiography and its relationship with visual acuity. Ophthalmology. 124, 235–244 (2017).27887743 10.1016/j.ophtha.2016.10.008
36. Anna Z-Ż Zbigniew MW Anna D Jacek PS Adaptive optics (rtx1) high-resolution imaging of photoreceptors and retinal arteries in patients with diabetic retinopathy J Diabetes Res. 2019 2019 9548324 31008115
Anna, Z. -Ż, Zbigniew, M. W., Anna, D. & Jacek, P. S. Adaptive optics (rtx1) high-resolution imaging of photoreceptors and retinal arteries in patients with diabetic retinopathy. J Diabetes Res. 2019, 9548324 (2019).31008115
37. Anna Z-Ż Retinal photoreceptors and microvascular changes in prediabetes measured with adaptive optics (rtx1™): A case-control study J. Diabet. Res. 2017 2017 4174292
Anna, Z. -Ż et al. Retinal photoreceptors and microvascular changes in prediabetes measured with adaptive optics (rtx1™): A case-control study. J. Diabet. Res. 2017, 4174292 (2017).
38. Serena F Significance of hyperreflective foci as an optical coherence tomography biomarker in retinal diseases: Characterization and clinical implications J. Ophthalmol. 2021 2021 6096017 34956669
Serena, F. et al. Significance of hyperreflective foci as an optical coherence tomography biomarker in retinal diseases: Characterization and clinical implications. J. Ophthalmol. 2021, 6096017 (2021).34956669
39. Bhanushali D Linking retinal microvasculature features with severity of diabetic retinopathy using optical coherence tomography angiography Investig. Ophthalmol. Vis. Sci. 2016 57 OCT519 OCT525 10.1167/iovs.15-18901 27472275
Bhanushali, D. et al. Linking retinal microvasculature features with severity of diabetic retinopathy using optical coherence tomography angiography. Investig. Ophthalmol. Vis. Sci. 57, OCT519–OCT525 (2016).27472275 10.1167/iovs.15-18901
40. AttaAllah H Mohamed A Ali M Macular vessels density in diabetic retinopathy: Quantitative assessment using optical coherence tomography angiography Int. Ophthalmol. 2019 39 1845 1859 10.1007/s10792-018-1013-0 30194547
AttaAllah, H., Mohamed, A. & Ali, M. Macular vessels density in diabetic retinopathy: Quantitative assessment using optical coherence tomography angiography. Int. Ophthalmol. 39, 1845–1859 (2019).30194547 10.1007/s10792-018-1013-0
41. Hsieh Y OCT angiography biomarkers for predicting visual outcomes after ranibizumab treatment for diabetic macular edema Ophthalmol. Retina 2019 3 826 834 10.1016/j.oret.2019.04.027 31227330
Hsieh, Y. et al. OCT angiography biomarkers for predicting visual outcomes after ranibizumab treatment for diabetic macular edema. Ophthalmol. Retina 3, 826–834 (2019).31227330 10.1016/j.oret.2019.04.027
42. Durbin M Quantification of retinal microvascular density in optical coherence tomographic angiography images in diabetic retinopathy JAMA Ophthalmol. 2017 135 370 376 10.1001/jamaophthalmol.2017.0080 28301651
Durbin, M. et al. Quantification of retinal microvascular density in optical coherence tomographic angiography images in diabetic retinopathy. JAMA Ophthalmol. 135, 370–376 (2017).28301651 10.1001/jamaophthalmol.2017.0080
43. Iafe N Phasukkijwatana N Chen X Sarraf D Retinal capillary density and foveal avascular zone area are age-dependent: Quantitative analysis using optical coherence tomography angiography Investig Ophthalmol. Vis. Sci. 2016 57 5780 5787 10.1167/iovs.16-20045 27792812
Iafe, N., Phasukkijwatana, N., Chen, X. & Sarraf, D. Retinal capillary density and foveal avascular zone area are age-dependent: Quantitative analysis using optical coherence tomography angiography. Investig Ophthalmol. Vis. Sci. 57, 5780–5787 (2016).27792812 10.1167/iovs.16-20045
44. Tan G Cheung N Simó R Cheung G Wong T Diabetic macular oedema Lancet. Diabet. Endocrinol. 2017 5 143 155 10.1016/S2213-8587(16)30052-3
Tan, G., Cheung, N., Simó, R., Cheung, G. & Wong, T. Diabetic macular oedema. Lancet. Diabet. Endocrinol. 5, 143–155 (2017).10.1016/S2213-8587(16)30052-3
45. Lachin J Effect of intensive diabetes therapy on the progression of diabetic retinopathy in patients with type 1 diabetes: 18 years of follow-up in the DCCT/EDIC Diabetes. 2015 64 631 642 10.2337/db14-0930 25204977
Lachin, J. et al. Effect of intensive diabetes therapy on the progression of diabetic retinopathy in patients with type 1 diabetes: 18 years of follow-up in the DCCT/EDIC. Diabetes. 64, 631–642 (2015).25204977 10.2337/db14-0930
46. Klein R Klein B Moss S Cruickshanks K The Wisconsin Epidemiologic Study of Diabetic Retinopathy: XVII. The 14-year incidence and progression of diabetic retinopathy and associated risk factors in type 1 diabetes Ophthalmology. 1998 105 1801 1815 10.1016/S0161-6420(98)91020-X 9787347
Klein, R., Klein, B., Moss, S. & Cruickshanks, K. The Wisconsin Epidemiologic Study of Diabetic Retinopathy: XVII. The 14-year incidence and progression of diabetic retinopathy and associated risk factors in type 1 diabetes. Ophthalmology. 105, 1801–1815 (1998).9787347 10.1016/S0161-6420(98)91020-X
47. Marco L Sebastiano S Nicholas D Mariacristina P Giuseppe L Adaptive optics technology for high-resolution retinal imaging Sensors 2012 13 334 366 10.3390/s130100334 23271600
Marco, L., Sebastiano, S., Nicholas, D., Mariacristina, P. & Giuseppe, L. Adaptive optics technology for high-resolution retinal imaging. Sensors 13, 334–366 (2012).23271600 10.3390/s130100334
48. Marco L Analysis of retinal capillaries in patients with type 1 diabetes and nonproliferative diabetic retinopathy using adaptive optics imaging Retina. 2013 33 1630 1639 10.1097/IAE.0b013e3182899326 23492950
Marco, L. et al. Analysis of retinal capillaries in patients with type 1 diabetes and nonproliferative diabetic retinopathy using adaptive optics imaging. Retina. 33, 1630–1639 (2013).23492950 10.1097/IAE.0b013e3182899326
49. Mohamed Kamel S High-resolution imaging of parafoveal cones in different stages of diabetic retinopathy using adaptive optics fundus camera PLoS One 2016 11 e0152788 10.1371/journal.pone.0152788 27057752
Mohamed Kamel, S. et al. High-resolution imaging of parafoveal cones in different stages of diabetic retinopathy using adaptive optics fundus camera. PLoS One 11, e0152788 (2016).27057752 10.1371/journal.pone.0152788
50. Marco L Investigation of adaptive optics imaging biomarkers for detecting pathological changes of the cone mosaic in patients with type 1 diabetes mellitus PLoS One. 2016 11 e0151380 10.1371/journal.pone.0151380 26963392
Marco, L. et al. Investigation of adaptive optics imaging biomarkers for detecting pathological changes of the cone mosaic in patients with type 1 diabetes mellitus. PLoS One. 11, e0151380 (2016).26963392 10.1371/journal.pone.0151380
51. Marco L Adaptive optics imaging of parafoveal cones in type 1 diabetes Retina. 2013 34 546 557
Marco, L. et al. Adaptive optics imaging of parafoveal cones in type 1 diabetes. Retina. 34, 546–557 (2013).
52. Wylie T Cone-photoreceptor density in adolescents with type 1 diabetes Investig. Ophthalmol. Vis. Sci. 2015 56 6339 6343 10.1167/iovs.15-16817 26517403
Wylie, T. et al. Cone-photoreceptor density in adolescents with type 1 diabetes. Investig. Ophthalmol. Vis. Sci. 56, 6339–6343 (2015).26517403 10.1167/iovs.15-16817
53. Arichika S Correlation of retinal arterial wall thickness with atherosclerosis predictors in type 2 diabetes without clinical retinopathy Br. J. Ophthalmol. 2017 101 69 74 10.1136/bjophthalmol-2016-309612 27913444
Arichika, S. et al. Correlation of retinal arterial wall thickness with atherosclerosis predictors in type 2 diabetes without clinical retinopathy. Br. J. Ophthalmol. 101, 69–74 (2017).27913444 10.1136/bjophthalmol-2016-309612
54. Wojciech M Katarzyna G-N Joanna MH Elżbieta B-S Evaluation of morphological changes in retinal vessels in type 1 diabetes mellitus patients with the use of adaptive optics Biomedicines. 2022 10 1926 10.3390/biomedicines10081926 36009472
Wojciech, M., Katarzyna, G.-N., Joanna, M. H. & Elżbieta, B.-S. Evaluation of morphological changes in retinal vessels in type 1 diabetes mellitus patients with the use of adaptive optics. Biomedicines. 10, 1926 (2022).36009472 10.3390/biomedicines10081926
55. Allen CC Sven-Erik B Retinal blood flow in diabetes Microcirculation. 2007 14 49 61 10.1080/10739680601072164 17365661
Allen, C. C. & Sven-Erik, B. Retinal blood flow in diabetes. Microcirculation. 14, 49–61 (2007).17365661 10.1080/10739680601072164
56. Otero-Marquez O Retinal blood flow biomarkers in healthy human subjects measured with clinical doppler optical coherence tomography Investig. Ophthalmol. Vis. Sci. 2022 63 3323-F0132
Otero-Marquez, O. et al. Retinal blood flow biomarkers in healthy human subjects measured with clinical doppler optical coherence tomography. Investig. Ophthalmol. Vis. Sci. 63, 3323-F0132 (2022).
57. Tomomi M Masamitsu S Hideaki H Retinal diseases associated with oxidative stress and the effects of a free radical scavenger (Edaravone) Oxid. Med. Cell Longev. 2017 2017 9208489 10.1155/2017/9208489 28194256
Tomomi, M., Masamitsu, S. & Hideaki, H. Retinal diseases associated with oxidative stress and the effects of a free radical scavenger (Edaravone). Oxid. Med. Cell Longev. 2017, 9208489 (2017).28194256 10.1155/2017/9208489
58. Stefan S Janna K Albert JA Pathophysiology of macular edema Ophthalmologica 2010 224 8 15 10.1159/000315155 20714176
Stefan, S., Janna, K. & Albert, J. A. Pathophysiology of macular edema. Ophthalmologica 224, 8–15 (2010).20714176 10.1159/000315155
59. Devarajan K Optical coherence tomography angiography for the assessment of choroidal vasculature in high myopia Br. J. Ophthalmol. 2020 104 917 923 10.1136/bjophthalmol-2019-314769 31585963
Devarajan, K. et al. Optical coherence tomography angiography for the assessment of choroidal vasculature in high myopia. Br. J. Ophthalmol. 104, 917–923 (2020).31585963 10.1136/bjophthalmol-2019-314769
60. Ang M Imaging in myopia: Potential biomarkers, current challenges and future developments Br. J. Ophthalmol. 2019 103 855 862 10.1136/bjophthalmol-2018-312866 30636210
Ang, M. et al. Imaging in myopia: Potential biomarkers, current challenges and future developments. Br. J. Ophthalmol. 103, 855–862 (2019).30636210 10.1136/bjophthalmol-2018-312866
61. Zhang L Automated segmentation of the choroid from clinical SD-OCT Investig. Ophthalmol. Vis. Sci. 2012 53 7510 7519 10.1167/iovs.12-10311 23060139
Zhang, L. et al. Automated segmentation of the choroid from clinical SD-OCT. Investig. Ophthalmol. Vis. Sci. 53, 7510–7519 (2012).23060139 10.1167/iovs.12-10311
62. Shen, H., Gu, Q., Cheng, R., Cheng, P. & Liu, Q. Associated factors and macular vascular perfusion change for diabetic macular edema at early stage: A cross-sectional observational study. (2023).
