Quantitative Analysis of the Changes of Retinal Blood Flow Density and Retinal Thickness in Patients with Diabetic Retinopathy by OCTA

Quantitative Analysis of the Changes of Retinal Blood Flow Density and Retinal Thickness in Patients with Diabetic Retinopathy by OCTA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantitative Analysis of the Changes of Retinal Blood Flow Density and Retinal Thickness in Patients with Diabetic Retinopathy by OCTA Yue Wang, Ruibin Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4103894/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In our current study, we aim to quantitatively analyze the alterations in retinal BFD and retinal thickness in patients with diabetic retinopathy using optical coherence tomography angiography (OCTA). We analyzed retinal blood flow density (BFD) and thickness in 60 diabetic retinopathy patients using OCTA, comparing them with 60 healthy individuals. Results showed significant lower retinal BFD in the observation group in both superficial and deep capillaries. The retinal thickness of the patients in the observation group was greater. the overall and paracentric concave of the BFD in the superficial capillary layer, the overall and paracentric concave, and subcentral concave of BFD in deep capillary layer, and the overall, central concave, paracentric concave, and subcentral concave of retinal thickness had a certain correlation with diabetic retinopathy. The overall, central concave, paracentric concave, and subcentral concave of the BFD in superficial and deep capillary layer and retinal thickness all had certain predictive values for diabetic retinopathy, and predictive values for the disease were indicated by AUC values ranging from 0.616 to 0.990 (p < 0.05). OCTA examination revealed a notable decrease in retinal BFD and increase in retinal thickness, suggesting its potential as a diagnostic tool for diabetic retinopathy. OCTA diabetic retinopathy retinal blood flow density retinal thickness Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Diabetes is a common clinical chronic illness. The global prevalence of diabetes is approximate 9%. It is estimated 1 out of 10 adults will suffer from diabetes by 2040 [ 1 – 2 ] . Diabetic retinopathy, a common complication of diabetes, stands as the leading cause of vision impairment and potential blindness in individuals during their most productive years [ 3 – 4 ] . As China's economy expands and the duration of diabetes cases extends, the incidence of diabetic retinopathy continues to rise annually, accompanied by an increasing rate of blindness associated with this condition. [ 5 – 6 ] . As the disease progresses, patients may encounter a range of symptoms including different levels of vision loss, floaters, and other issues such as palpitations, fainting, diarrhea, and constipation. These symptoms present a significant risk to both physical and mental well-being. [ 7 – 8 ] . Therefore, early diagnosis and appropriate intervention are crucial in effectively reducing the rate of blindness caused by this disease. Several clinical diagnostic techniques are available for early diagnosis, yet they often come with drawbacks like invasive procedures and potential allergies to contrast agents. Consequently, the use of optical coherence tomography angiography (OCTA) has gained popularity in recent years due to its higher resolution. OCTA excels in vividly depicting the retina and choroid images, allowing for precise detection of vascular abnormalities in the patient's retina. Moreover, it can quickly and significantly ascertain vascular damage [ 9 – 10 ] . In addition, it can also quantitatively analyze the blood flow density, with good repeatability and consistency [ 11 – 12 ] . OCTA offers an effective approach for early monitoring and tracking the progress of diabetes and related complications. Substantial amount of qualitative and quantitative research has been conducted on the retinal and choroidal blood flow systems in various eye diseases [ 13 – 14 ] . Yet, quantitative analysis of changes in retinal blood flow density (BFD) and retinal thickness in individuals affected by diabetic retinopathy has not been reported. Hence, this study aims to quantitatively analyze the alterations in retinal BFD and retinal thickness in patients with diabetic retinopathy using OCTA, thus deepen our comprehension of the disease. Data and methods General data All of 60 patients with diabetic retinopathy received in our hospital from May 2020 to September 2022 were included as subjects in the observation group. Inclusion criteria were 1) individuals met the diagnostic criteria for type 2 diabetes [ 15 ] ; 2) individuals matched the diagnostic criteria for diabetic retinopathy [ 16 ] ; 3) individuals who were > 18 years old. Exclusion criteria included 1) patients with retinopathy caused by other reasons except diabetes; 2) patients exhibiting solely optic neuropathy with no apparent systemic diseases; 3) patients who received treatment (e.g., retinal laser photocoagulation) in the past. A total of 60 healthy physical examiners who were matched in age and gender with the patients were included as the control group. Inclusion criteria were 1) individuals who were > 18 years old; 2) individuals without obvious abnormal eye lesions. Exclusion criteria included 1) individuals with eye diseases in the past; 2) individuals with eye surgery in the past; 3) individuals with hypertension, cardiovascular or cerebrovascular illnesses. This research was approved by the Ethics Committee of our hospital, and the participants and their families gave informed consent. Methods Inspection method Angio retina mode (3 mm × 3 mm) was used to scan the macular area during OCTA examination, and then the images with SQI ≥ 6 was saved. During the operation, the objective factors that affected image quality, such as severe jitter and unstable tear film should try to be avoided. All inspections were completed by the same ophthalmologist with rich experience in operation. The two measurement results were collected, and the average value was taken as the final result for subsequent comparison. The software automatically took the central fovea of the macula as the center, divided the area within the diameter of 1 mm into the central concave area, and divided the area within the diameter of 1–3 mm into the paracentric concave area. The system's own software was used to analyze the overall, central concave, paracentric concave, and subcentral concave blood flow density of the superficial retinal capillary layer and the deep retinal capillary layer, as well as the overall, central concave, paracentric concave, and subcentral concave retinal thickness (Fig. 1 ). Observation indicators The common data for example age and gender of the 2 groups of research objects were observed; the retinal BFD of the 2 groups of research objects was observed; the changes in retinal thickness of the two groups of research objects were observed; the correlation between OCTA inspection parameters and retinopathy in sufferers with diabetic retinopathy was analyzed; analyze the diagnostic values of OCTA inspection parameters on retinopathy in sufferers with diabetic retinopathy were analyzed. Statistical methods SPSS 22.0 statistical software was used to process and statistically analyze the experimental data. The measurement data were represented by mean ± standard deviation (‾χ ± s), and independent sample t-test was used for comparison between two groups; count data were represented by rate (%), and conducted with χ 2 -test, and Pearson was used for correlation analysis; ROC was used for predictive value diagnosis, and p < 0.05 was considered as a statistically obvious distinction. Results Clinical characteristics of participants indicated no statistically obvious difference between the control and observation group ( p > 0.05) (Table 1 ). Table 1 The clinical characteristics of subjects Group Number of eyes Age (Mean ± SD) Gender: (Male/Female) BMI (kg/m 2 ) Eyes (Left/Right) observation group 60 57.60 ± 10.50 33/27 24.55 ± 2.96 35/25 control group 60 55.60 ± 13.50 31/29 23.98 ± 3.05 29/31 t 0.906 0.134 0.004 1.205 P 0.367 0.714 0.997 0.272 We next measured BFD for the participants. BFD in the superficial retinal capillary layer in the observation group was significantly lower than those of the control group (Table 2 ). Specifically, the overall BFD in the superficial retinal capillary layer in the observation group was lower than the control group (44.05 ± 4.05 vs 49.56 ± 2.30, p < 0.001). Similarly, BFD of the central concave (13.05 ± 3.95 vs 15.85 ± 5.95, p < 0.003), aracentric concave (44.05 ± 4.52 vs 51.70 ± 2.86, p < 0.001), and suncentral concave (44.80 ± 4.69 vs 50.40 ± 5.74, p < 0.001) in the observation group was significantly lower than those in the observation group. Table 2 The BFD in the superficial retinal capillary layer ( x̅ ± s, %) group Number of eyes overall Central concave Aracentric concave Subcentral concave Observation group 60 44.05 ± 4.05 13.05 ± 3.95 44.05 ± 4.52 44.80 ± 4.69 Control group 60 49.56 ± 2.30 15.85 ± 5.95 51.70 ± 2.86 50.40 ± 5.74 t 9.164 3.037 11.093 5.847 P < 0.001 0.003 < 0.001 < 0.001 We also investigated BFD for the participant in the deep retinal capillary layer. The results indicated that BFD in the deep capillaries in the observation group was statistically significantly lower than those of the control group (Table 3 ). Specifically, the overall BFD in the superficial retinal capillary layer in the observation group (42.20 ± 3.85) was lower than the control group (61.58 ± 8.55) Similarly, BFD of the central concave (26.05 ± 6.53 vs 28.41 ± 5.96, p = 0.041), aracentric concave (45.10 ± 5.96 vs 53.10 ± 3.52, p < 0.001), and suncentral concave (42.09 ± 4.35 vs 49.52 ± 5.10, p < 0.001) in the observation group was significantly lower than those in the observation group. Table 3 The BFD in the deep retinal capillary layer ( x̅ ± s, %) Group Number of eyes Overall Central concave Aracentric concave Subcentral concave Observation group 60 42.20 ± 3.85 26.05 ± 6.53 45.10 ± 5.96 42.09 ± 4.35 Control group 60 61.58 ± 8.55 28.41 ± 5.96 53.10 ± 3.52 49.52 ± 5.10 t 16.001 2.064 8.955 8.594 P < 0.001 0.041 < 0.001 < 0.001 Next, we measured retinal thickness of the 2 groups. In comparison of the control group, the retinal thickness of the observation group was greater (315.50 ± 13.50 vs 285.30 ± 9.50, p < 0.001) ( Table. 4 ). We observed similar trends in the central concave, aracentric concave, and subcentral concave ( Table. 4 ). Table 4 Retinal thickness (x̅± s, µm) Group Number of eyes Overall Central concave Aracentric concave Subcentral concave Observation group 60 315.50 ± 13.50 280.80 ± 10.50 340.20 ± 15.90 340.25 ± 30.40 Control group 60 285.30 ± 9.50 235.80 ± 15.60 315.20 ± 12.30 288.50 ± 26.60 t 14.173 18.541 9.634 9.923 P < 0.001 < 0.001 < 0.001 < 0.001 We performed a correlation analysis of BFD and retinal thickness with diabetic retinopathy. The results indicated that BFD in superficial capillary layer was negatively correlated with diabetic retinopathy (Table 5 a). Overall BFD in deep capillary layer was negatively associated with diabetic retinopathy ( p < 0.001), as well as the central concave and aracentric concave. However, the subcentral concave BFD in deep capillary layer was positively associated with diabetic retinopathy (Table 5 b). Retinal thickness was positively correlated with diabetic retinopathy (Table 5 c). Table 5 a. Correlation analysis of BFD in superficial capillary layer with diabetic retinopathy Statistics BFD in superficial capillary layer Overall Central concave Aracentric concave Subcentral concave r -0.645 -0.269 -0.714 -0.474 p < 0.001 0.003 < 0.001 < 0.001 Table 5 b. Correlation analysis of BFD in deep capillary layer with diabetic retinopathy Statistics BFD in deep capillary layer Overall Central concave Aracentric concave Subcentral concave r -0.827 -0.187 -0.636 0.620 p < 0.001 0.041 < 0.001 < 0.001 Table 5 c. Correlation analysis of retinal thickness with diabetic retinopathy Statistics Retinal thickness Overall Central concave Aracentric concave Subcentral concave r 0.794 0.863 0.664 0.674 p < 0.001 < 0.001 < 0.001 < 0.001 At last, we calculated the ROC to evaluate the predictive power of the variables for diabetic retinopathy. The overall BFD in superficial capillary layer showed a ROC of 0.888, with central concave, aracentric concave, and subcentral concave of 0.627, 0.923, and 0.771, respectively (Table 6 and Fig. 2 ). The overall, central concave, aracentric concave, and subcentral concave of BFD in deep capillary layer exhibited a ROC value of 0.983, 0.616, 0.882, 0.862, respectively (Table 7 and Fig. 3 ). Retinal thickness also displayed high predictive value for diabetic retinopathy of 0.960, 0.990, 0.897, 0.899 for overall, central concave, aracentric concave, and subcentral concave (Table 8 and Fig. 4 ). Table 6 ROC of BFD-related variables in superficial capillary layer Variables AUC Best cut-off value Youden index SE 95% CI p Sensitivity (%) Specificity (%) Overall 0.888 46.57 0.667 0.031 0.818–0.939 < 0.001 75.00 91.67 Central concave 0.627 16.62 0.267 0.051 0.534–0.714 0.013 83.33 43.33 Aracentric concave 0.923 48.14 0.750 0.027 0.860–0.964 < 0.001 83.33 91.67 Subcentral concave 0.771 47.39 0.433 0.042 0.686–0.843 < 0.001 73.33 70.00 Table 7 ROC of BFD-related variables in deep capillary layer Variables AUC Best cut-off value Youden index SE 95% CI p Sensitivity (%) Specificity (%) Overall 0.983 48.65 0.900 0.012 0.940–0.998 < 0.001 96.67 93.33 Central concave 0.616 25.96 0.233 0.052 0.523–0.703 0.025 55.00 68.33 Aracentric concave 0.882 48.75 0.717 0.033 0.811–0.934 < 0.001 78.33 93.33 Subcentral concave 0.862 46.56 0.600 0.033 0.787–0.918 < 0.001 88.33 71.67 Table 8 ROC of retinal thickness-related variables Variables AUC Best cut-off value Youden index SE 95% CI p Sensitivity (%) Specificity (%) Overall 0.960 299 0.833 0.016 0.908–0.988 < 0.001 86.67 96.67 Central concave 0.990 261 0.933 0.007 0.951-1.000 < 0.001 98.33 95.00 Aracentric concave 0.897 326 0.667 0.028 0.828–0.945 < 0.001 85.00 81.67 Subcentral concave 0.899 319 0.683 0.027 0.830–0.946 < 0.001 78.33 90.00 Discussion Diabetic retinopathy is a prevalent fundus vascular disorder, characterized as a progressively visual impairment, primarily marked by damage to the microvasculature of the retina. In patients with a long history of the disease, nearly all will experience varying degrees of retinal microvascular complications, often accompanied by retinopathy. This condition significantly impacts vision, particularly in younger patients, who not only tend to experience a more rapid onset of the disease but also face a higher recurrence rate post-treatment [ 17 – 18 ] . As a new diagnostic technique, OCTA achieves the purpose of visualizing retinal and choroid capillaries through layered vascular reconstruction, and uses new algorithms to generate high-resolution images. Compared with other diagnostic techniques, it has the advantages of non-invasiveness, no mydriasis, and no time window limitation, and can quantitatively analyze the blood flow in each layer of blood vessels, so it has been widely used in ophthalmology at home and abroad [ 19 – 20 ] . This technology can not only detect the retinopathy in patients, accurately diagnose diabetic eyes with higher risk, but even screen out diabetes before systematic diagnosis, which has a good predictive effect. However, no research has done a clear quantitative analysis on the changes of retinal BFD and retinal thickness in sufferers with diabetic retinopathy, and no diagnostic prediction has been made. Therefore, this study conducted quantitative analysis through OTCA and observed its predictive values on the disease. In this study, the clinical characteristics of the objects were first observed, and the outcomes showing that the clinical data of the 2 groups of research objects had no significant statistical significance, which indicates that the baseline data of all the research objects are evenly distributed and comparable, also proves that the randomness characteristics of the study subjects' enrollment and means that the final results of this study are more reliable. In addition, the outcomes of the blood flow density experiment in this research showed that in comparison of the control one, the BFD of the superficial and deep capillaries in the observation one was less, which indicates that the BFD in the superficial retina after retinopathy in diabetic patients begins to be significantly decreased, and it is possible that as the disease progresses, the blood flow density may continue to be decreased, but this study did not conduct such analysis. Some studies suggest that there is a significant difference in paracentric concave, and subcentral concave BFD, and the BFD in the deep part is decreased more obviously with the increasing severity of the disease, and the BFD in the whole paracentric concave is decreased more obviously [ 21 – 22 ] . This is also somewhat similar to the outcomes of this research. In addition, the outcomes in the experiment of the retinal thickness showing that in comparison of the control one, the retinal thickness of the sufferers in the observation one was greater. The study showed that the comparative difference in the thickness of the central concave was the most significant, which is due to the reduction of retinal blood flow density, resulting in retinal tissue ischemia and hypoxia, secondary edema, and central concave traction. Because of the lower thickness of central concave itself, the change scope is more pronounced. In addition, the cone cells of central concave have powerful metabolic functions and are extremely sensitive to hypoxia. When there is circulatory disturbance, due to insufficient oxygen supply, the cone cells will accumulate a large number of metabolites, resulting in edema that is more pronounced than the surrounding area [ 23 – 24 ] . In order to verify the correlation between OCTA and diabetic retinopathy, this study conducted a correlation analysis, and the results showed that: the overall and paracentric concave of the blood flow density in the superficial capillary layer, the overall and paracentric concave, and subcentral concave of BFD in deep capillary layer, and the overall, central concave, paracentric concave, and subcentral concave of retinal thickness had a certain correlation with diabetic retinopathy (r=-0.645, -0.714, -0.827, -0.636, -0.620, 0.794, 0.863, 0.664, 0.674, P < 0.05). This shows that OCTA examination may be able to predict the disease; it shows that OCTA examination does have a high diagnostic value for retinopathy in patients with diabetic retinopathy. Early studies have found that OCTA image analysis has an exact diagnostic value for macular microvascular lesions in patients with diabetic retinopathy. OCTA subdivides the detection range with the center of the macular fovea, which can accurately reflect the hemorrhage in macular region in patients with diabetic retinopathy. Retinal surface capillaries can reveal the border of the avascular area of macular fovea. Due to the high definition and high measurement accuracy, the area, perimeter and shape indices of the macular foveal avascular zone can be understood. Analyzing the severity of capillary arch damage in the macular area facilitates the targeted scientific intervention [ 25 – 26 ] . Not only that, OCTA is a tool that can detect microvascular changes in diabetic retinopathy, including microvascular tumors, non-perfused areas, retinal edema, vascular rings, and intraretinal microvascular changes [ 27 – 28 ] . In addition, OCTA can also provide measurement and quantification of foveal avascular area, vessel density, perfusion density, etc. Changes in these measures of vascular function have almost universally been shown to be associated with increased severity of diabetic retinopathy and worsening vision [ 28 – 30 ] . These indicators may serve as potential biomarkers of diabetic retinopathy in different courses of disease, and are crucial for predicting the grade of diabetic retinopathy, identifying patients at risk, selecting treatment methods, and observing the effects of follow-up treatment. Therefore, based on this, the ROC curve was also drawn in this study to analyze the predictive values of OCTA for the disease. The results showed that the overall, central concave, paracentric concave, and subcentral concave of the BFD in superficial and deep capillary layer and retinal thickness all have certain predictive values for diabetic retinopathy, and AUC were: 0.888, 0.627, 0.923, 0.771, 0.983, 0.616, 0.882, 0.862, 960, 0.990, 0.897, 0.899, respectively, with good predictive values, indicating that is has a good clinical application value. In summary, OCTA examination can clarify the changes of retinal BFD and retinal thickness, and the retinal BFD of the patients is decreased significantly, while the retinal thickness is increased, which may be able to monitor the severity of the patients' conditions, and OCTA examination can be used to predict the disease to a certain extent. It has a significant clinical application value, and it is recommended to be popularized and applied. However, this research is a retrospective analysis with a small sample size, so more samples need to be accumulated to analyze more detailed results, and the correlation between OCTA examination and the severity of the disease has not been analyzed, which needs to be further explored. Declarations Author Contribution guarantor of integrity of the entire study： R.L. study concepts： R.L.study design： R.L.,Y.W.definition of intellectual content： R.L.literature research：Y.W.experimental studies：Y.W.manuscript preparation：Y.W.manuscript review： R.L.All authors reviewed the manuscript. References Magliano DJ, Boyko EJ. IDF Diabetes Atlas 10th edition scientific committee. IDF DIABETES ATLAS [Internet]. 10th ed. Brussels: International Diabetes Federation; 2021. PMID: 35914061. Liu N, Wang G, Liu C, Liu J, Huang S, Zhou Y, Xiao E. Non-alcoholic fatty liver disease and complications in type 1 and type 2 diabetes: A Mendelian randomization study. 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PMID: 35966243; PMCID: PMC9371870. Xiong K, Wang W, Gong X, Ji Y, Guo X, Yuan M, Li W, Liang X, Huang W, Wen F. INFLUENCE OF HIGH MYOPIA ON CHORIOCAPILLARIS PERFUSION AND CHOROIDAL THICKNESS IN DIABETIC PATIENTS WITHOUT DIABETIC RETINOPATHY. Retina. 2022;42(6):1077–1084. doi: 10.1097/IAE.0000000000003427 . PMID: 35174807. Kaizu Y, Nakao S, Yoshida S, Hayami T, Arima M, Yamaguchi M, Wada I, Hisatomi T, Ikeda Y, Ishibashi T, Sonoda KH. Optical Coherence Tomography Angiography Reveals Spatial Bias of Macular Capillary Dropout in Diabetic Retinopathy. Invest Ophthalmol Vis Sci. 2017;58(11):4889–4897. doi: 10.1167/iovs.17-22306 . PMID: 28973335. Yasin Alibhai A, Moult EM, Shahzad R, Rebhun CB, Moreira-Neto C, McGowan M, Lee D, Lee B, Baumal CR, Witkin AJ, Reichel E, Duker JS, Fujimoto JG, Waheed NK. Quantifying Microvascular Changes Using OCT Angiography in Diabetic Eyes without Clinical Evidence of Retinopathy. Ophthalmol Retina. 2018;2(5):418–427. doi: 10.1016/j.oret.2017.09.011. Epub 2017 Nov 7. PMID: 30820483; PMCID: PMC6391050. de Carlo TE, Chin AT, Bonini Filho MA, Adhi M, Branchini L, Salz DA, Baumal CR, Crawford C, Reichel E, Witkin AJ, Duker JS, Waheed NK. DETECTION OF MICROVASCULAR CHANGES IN EYES OF PATIENTS WITH DIABETES BUT NOT CLINICAL DIABETIC RETINOPATHY USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY. Retina. 2015;35(11):2364-70. doi: 10.1097/IAE.0000000000000882 . PMID: 26469537. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4103894","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281095127,"identity":"310d3d07-bc17-43ef-9462-9f0d86f03269","order_by":0,"name":"Yue Wang","email":"","orcid":"","institution":"The Fourth Affiliated Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Wang","suffix":""},{"id":281095130,"identity":"900d99c2-0094-4d54-9cf4-5ecc1ddebf87","order_by":1,"name":"Ruibin Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYLCCBwwHePiZmQ8/IF5LAsMBGcl2tjQDkrTYGJznUZAgSrX8jOTHHxL33OExPszDYMBQYxNNUIvBmWMGBgnPnvGYHeY98IDhWFpuA0Et7D0MCQkHDgO18CUYMDYcJqxFvpmH4QBIi3Ezj4EEUVoYjvcwNoC0GDATqwXoF2OGhAPPeCQOAwM5gRi/gEPsw4E79vz9hw8/+FBjQ4TDUEACacpHwSgYBaNgFOACAFW2QGGCoxWfAAAAAElFTkSuQmCC","orcid":"","institution":"ShanXi Bethune Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ruibin","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-03-15 00:59:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4103894/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4103894/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53009623,"identity":"747b507c-9168-455f-90e4-98af15d47a5f","added_by":"auto","created_at":"2024-03-19 15:23:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":198026,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRetinal blood flow diagram of each group. \u003c/strong\u003eThe diameter of the concentric circle shown in the rectangle is 3-6 mm, that of the circle is 1-3 mm, and that of the triangle is 1 mm.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4103894/v1/6455325d40f1d1d0c0a94b6c.png"},{"id":53009620,"identity":"7887fd56-1a25-4076-87a4-243379fbb22b","added_by":"auto","created_at":"2024-03-19 15:23:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16291,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC of BFD-related variables in superficial capillary layer\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4103894/v1/992d5c4393f8900578f6a249.png"},{"id":53009619,"identity":"982f8a92-42ce-4b31-a126-22a7733810ec","added_by":"auto","created_at":"2024-03-19 15:23:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":14989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC of BFD-related variables in the deep capillary\u003c/strong\u003e \u003cstrong\u003elayer\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4103894/v1/1b5c63f674b651f48b1e0ad7.png"},{"id":53009621,"identity":"4f2121fc-6d4c-401a-a489-747052c537b6","added_by":"auto","created_at":"2024-03-19 15:23:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17922,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC retinal thickness-related variables\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4103894/v1/09054c56311aad905efecfa3.png"},{"id":53333393,"identity":"42afa292-2c4a-4341-8ed0-8a483410aa35","added_by":"auto","created_at":"2024-03-24 12:22:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":669255,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4103894/v1/b0153d8e-d30b-4b62-9a31-9bdcd1dcc712.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative Analysis of the Changes of Retinal Blood Flow Density and Retinal Thickness in Patients with Diabetic Retinopathy by OCTA","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes is a common clinical chronic illness. The global prevalence of diabetes is approximate 9%. It is estimated 1 out of 10 adults will suffer from diabetes by 2040 \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Diabetic retinopathy, a common complication of diabetes, stands as the leading cause of vision impairment and potential blindness in individuals during their most productive years \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. As China's economy expands and the duration of diabetes cases extends, the incidence of diabetic retinopathy continues to rise annually, accompanied by an increasing rate of blindness associated with this condition. \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. As the disease progresses, patients may encounter a range of symptoms including different levels of vision loss, floaters, and other issues such as palpitations, fainting, diarrhea, and constipation. These symptoms present a significant risk to both physical and mental well-being. \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Therefore, early diagnosis and appropriate intervention are crucial in effectively reducing the rate of blindness caused by this disease.\u003c/p\u003e \u003cp\u003eSeveral clinical diagnostic techniques are available for early diagnosis, yet they often come with drawbacks like invasive procedures and potential allergies to contrast agents. Consequently, the use of optical coherence tomography angiography (OCTA) has gained popularity in recent years due to its higher resolution. OCTA excels in vividly depicting the retina and choroid images, allowing for precise detection of vascular abnormalities in the patient's retina. Moreover, it can quickly and significantly ascertain vascular damage \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. In addition, it can also quantitatively analyze the blood flow density, with good repeatability and consistency \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. OCTA offers an effective approach for early monitoring and tracking the progress of diabetes and related complications. Substantial amount of qualitative and quantitative research has been conducted on the retinal and choroidal blood flow systems in various eye diseases \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Yet, quantitative analysis of changes in retinal blood flow density (BFD) and retinal thickness in individuals affected by diabetic retinopathy has not been reported. Hence, this study aims to quantitatively analyze the alterations in retinal BFD and retinal thickness in patients with diabetic retinopathy using OCTA, thus deepen our comprehension of the disease.\u003c/p\u003e"},{"header":"Data and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGeneral data\u003c/h2\u003e \u003cp\u003eAll of 60 patients with diabetic retinopathy received in our hospital from May 2020 to September 2022 were included as subjects in the observation group. Inclusion criteria were 1) individuals met the diagnostic criteria for type 2 diabetes \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e; 2) individuals matched the diagnostic criteria for diabetic retinopathy \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e; 3) individuals who were \u0026gt;\u0026thinsp;18 years old. Exclusion criteria included 1) patients with retinopathy caused by other reasons except diabetes; 2) patients exhibiting solely optic neuropathy with no apparent systemic diseases; 3) patients who received treatment (e.g., retinal laser photocoagulation) in the past. A total of 60 healthy physical examiners who were matched in age and gender with the patients were included as the control group. Inclusion criteria were 1) individuals who were \u0026gt;\u0026thinsp;18 years old; 2) individuals without obvious abnormal eye lesions. Exclusion criteria included 1) individuals with eye diseases in the past; 2) individuals with eye surgery in the past; 3) individuals with hypertension, cardiovascular or cerebrovascular illnesses. This research was approved by the Ethics Committee of our hospital, and the participants and their families gave informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eInspection method\u003c/h2\u003e \u003cp\u003eAngio retina mode (3 mm \u0026times; 3 mm) was used to scan the macular area during OCTA examination, and then the images with SQI\u0026thinsp;\u0026ge;\u0026thinsp;6 was saved. During the operation, the objective factors that affected image quality, such as severe jitter and unstable tear film should try to be avoided. All inspections were completed by the same ophthalmologist with rich experience in operation. The two measurement results were collected, and the average value was taken as the final result for subsequent comparison. The software automatically took the central fovea of the macula as the center, divided the area within the diameter of 1 mm into the central concave area, and divided the area within the diameter of 1\u0026ndash;3 mm into the paracentric concave area. The system's own software was used to analyze the overall, central concave, paracentric concave, and subcentral concave blood flow density of the superficial retinal capillary layer and the deep retinal capillary layer, as well as the overall, central concave, paracentric concave, and subcentral concave retinal thickness (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eObservation indicators\u003c/h2\u003e \u003cp\u003eThe common data for example age and gender of the 2 groups of research objects were observed; the retinal BFD of the 2 groups of research objects was observed; the changes in retinal thickness of the two groups of research objects were observed; the correlation between OCTA inspection parameters and retinopathy in sufferers with diabetic retinopathy was analyzed; analyze the diagnostic values of OCTA inspection parameters on retinopathy in sufferers with diabetic retinopathy were analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eSPSS 22.0 statistical software was used to process and statistically analyze the experimental data. The measurement data were represented by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u0026oline;χ\u0026thinsp;\u0026plusmn;\u0026thinsp;s), and independent sample t-test was used for comparison between two groups; count data were represented by rate (%), and conducted with χ\u003csup\u003e2\u003c/sup\u003e-test, and Pearson was used for correlation analysis; ROC was used for predictive value diagnosis, and \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e was considered as a statistically obvious distinction.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eClinical characteristics of participants indicated no statistically obvious difference between the control and observation group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe clinical characteristics of subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of eyes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGender: (Male/Female)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e )\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEyes (Left/Right)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eobservation group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.60\u0026thinsp;\u0026plusmn;\u0026thinsp;10.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35/25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003econtrol group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.60\u0026thinsp;\u0026plusmn;\u0026thinsp;13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31/29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29/31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe next measured BFD for the participants. BFD in the superficial retinal capillary layer in the observation group was significantly lower than those of the control group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Specifically, the overall BFD in the superficial retinal capillary layer in the observation group was lower than the control group (44.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05 vs 49.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, BFD of the central concave (13.05\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95 vs 15.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.003), aracentric concave (44.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52 vs 51.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86, \u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001), and suncentral concave (44.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69 vs 50.40\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the observation group was significantly lower than those in the observation group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe BFD in the superficial retinal capillary layer ( x̅\u0026thinsp;\u0026plusmn;\u0026thinsp;s, %)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of eyes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eoverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.05\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.40\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe also investigated BFD for the participant in the deep retinal capillary layer. The results indicated that BFD in the deep capillaries in the observation group was statistically significantly lower than those of the control group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Specifically, the overall BFD in the superficial retinal capillary layer in the observation group (42.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85) was lower than the control group (61.58\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55) Similarly, BFD of the central concave (26.05\u0026thinsp;\u0026plusmn;\u0026thinsp;6.53 vs 28.41\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041), aracentric concave (45.10\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96 vs 53.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.52, \u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001), and suncentral concave (42.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35 vs 49.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the observation group was significantly lower than those in the observation group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eThe BFD in the deep retinal capillary layer\u003c/b\u003e ( x̅\u0026thinsp;\u0026plusmn;\u0026thinsp;s, %)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of eyes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.05\u0026thinsp;\u0026plusmn;\u0026thinsp;6.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.10\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.58\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.41\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.594\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNext, we measured retinal thickness of the 2 groups. In comparison of the control group, the retinal thickness of the observation group was greater (315.50\u0026thinsp;\u0026plusmn;\u0026thinsp;13.50 vs 285.30\u0026thinsp;\u0026plusmn;\u0026thinsp;9.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eTable. 4\u003c/b\u003e). We observed similar trends in the central concave, aracentric concave, and subcentral concave (\u003cb\u003eTable. 4\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRetinal thickness (x̅\u0026plusmn; s, \u0026micro;m)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of eyes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315.50\u0026thinsp;\u0026plusmn;\u0026thinsp;13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280.80\u0026thinsp;\u0026plusmn;\u0026thinsp;10.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e340.20\u0026thinsp;\u0026plusmn;\u0026thinsp;15.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e340.25\u0026thinsp;\u0026plusmn;\u0026thinsp;30.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e285.30\u0026thinsp;\u0026plusmn;\u0026thinsp;9.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e235.80\u0026thinsp;\u0026plusmn;\u0026thinsp;15.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e315.20\u0026thinsp;\u0026plusmn;\u0026thinsp;12.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e288.50\u0026thinsp;\u0026plusmn;\u0026thinsp;26.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe performed a correlation analysis of BFD and retinal thickness with diabetic retinopathy. The results indicated that BFD in superficial capillary layer was negatively correlated with diabetic retinopathy (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Overall BFD in deep capillary layer was negatively associated with diabetic retinopathy (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as the central concave and aracentric concave. However, the subcentral concave BFD in deep capillary layer was positively associated with diabetic retinopathy (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Retinal thickness was positively correlated with diabetic retinopathy (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ea. Correlation analysis of BFD in superficial capillary layer with diabetic retinopathy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBFD in superficial capillary layer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.474\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eb. Correlation analysis of BFD in deep capillary layer with diabetic retinopathy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBFD in deep capillary layer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ec. Correlation analysis of retinal thickness with diabetic retinopathy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eRetinal thickness\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt last, we calculated the ROC to evaluate the predictive power of the variables for diabetic retinopathy. The overall BFD in superficial capillary layer showed a ROC of 0.888, with central concave, aracentric concave, and subcentral concave of 0.627, 0.923, and 0.771, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The overall, central concave, aracentric concave, and subcentral concave of BFD in deep capillary layer exhibited a ROC value of 0.983, 0.616, 0.882, 0.862, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e7\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Retinal thickness also displayed high predictive value for diabetic retinopathy of 0.960, 0.990, 0.897, 0.899 for overall, central concave, aracentric concave, and subcentral concave (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e8\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC of BFD-related variables in superficial capillary layer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBest cut-off value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.818\u0026ndash;0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e91.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.534\u0026ndash;0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e43.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.860\u0026ndash;0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e91.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.686\u0026ndash;0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e73.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e70.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC of BFD-related variables in deep capillary layer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBest cut-off value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.940\u0026ndash;0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e93.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.523\u0026ndash;0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e68.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.811\u0026ndash;0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e78.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e93.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.787\u0026ndash;0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e88.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e71.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC of retinal thickness-related variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBest cut-off value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.908\u0026ndash;0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e86.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e96.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.951-1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e98.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e95.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAracentric concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.828\u0026ndash;0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e85.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e81.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubcentral concave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.830\u0026ndash;0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e78.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e90.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDiabetic retinopathy is a prevalent fundus vascular disorder, characterized as a progressively visual impairment, primarily marked by damage to the microvasculature of the retina. In patients with a long history of the disease, nearly all will experience varying degrees of retinal microvascular complications, often accompanied by retinopathy. This condition significantly impacts vision, particularly in younger patients, who not only tend to experience a more rapid onset of the disease but also face a higher recurrence rate post-treatment \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. As a new diagnostic technique, OCTA achieves the purpose of visualizing retinal and choroid capillaries through layered vascular reconstruction, and uses new algorithms to generate high-resolution images. Compared with other diagnostic techniques, it has the advantages of non-invasiveness, no mydriasis, and no time window limitation, and can quantitatively analyze the blood flow in each layer of blood vessels, so it has been widely used in ophthalmology at home and abroad \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. This technology can not only detect the retinopathy in patients, accurately diagnose diabetic eyes with higher risk, but even screen out diabetes before systematic diagnosis, which has a good predictive effect. However, no research has done a clear quantitative analysis on the changes of retinal BFD and retinal thickness in sufferers with diabetic retinopathy, and no diagnostic prediction has been made. Therefore, this study conducted quantitative analysis through OTCA and observed its predictive values on the disease.\u003c/p\u003e \u003cp\u003eIn this study, the clinical characteristics of the objects were first observed, and the outcomes showing that the clinical data of the 2 groups of research objects had no significant statistical significance, which indicates that the baseline data of all the research objects are evenly distributed and comparable, also proves that the randomness characteristics of the study subjects' enrollment and means that the final results of this study are more reliable. In addition, the outcomes of the blood flow density experiment in this research showed that in comparison of the control one, the BFD of the superficial and deep capillaries in the observation one was less, which indicates that the BFD in the superficial retina after retinopathy in diabetic patients begins to be significantly decreased, and it is possible that as the disease progresses, the blood flow density may continue to be decreased, but this study did not conduct such analysis. Some studies suggest that there is a significant difference in paracentric concave, and subcentral concave BFD, and the BFD in the deep part is decreased more obviously with the increasing severity of the disease, and the BFD in the whole paracentric concave is decreased more obviously \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. This is also somewhat similar to the outcomes of this research. In addition, the outcomes in the experiment of the retinal thickness showing that in comparison of the control one, the retinal thickness of the sufferers in the observation one was greater. The study showed that the comparative difference in the thickness of the central concave was the most significant, which is due to the reduction of retinal blood flow density, resulting in retinal tissue ischemia and hypoxia, secondary edema, and central concave traction. Because of the lower thickness of central concave itself, the change scope is more pronounced. In addition, the cone cells of central concave have powerful metabolic functions and are extremely sensitive to hypoxia. When there is circulatory disturbance, due to insufficient oxygen supply, the cone cells will accumulate a large number of metabolites, resulting in edema that is more pronounced than the surrounding area \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. In order to verify the correlation between OCTA and diabetic retinopathy, this study conducted a correlation analysis, and the results showed that: the overall and paracentric concave of the blood flow density in the superficial capillary layer, the overall and paracentric concave, and subcentral concave of BFD in deep capillary layer, and the overall, central concave, paracentric concave, and subcentral concave of retinal thickness had a certain correlation with diabetic retinopathy (r=-0.645, -0.714, -0.827, -0.636, -0.620, 0.794, 0.863, 0.664, 0.674, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This shows that OCTA examination may be able to predict the disease; it shows that OCTA examination does have a high diagnostic value for retinopathy in patients with diabetic retinopathy. Early studies have found that OCTA image analysis has an exact diagnostic value for macular microvascular lesions in patients with diabetic retinopathy. OCTA subdivides the detection range with the center of the macular fovea, which can accurately reflect the hemorrhage in macular region in patients with diabetic retinopathy. Retinal surface capillaries can reveal the border of the avascular area of macular fovea. Due to the high definition and high measurement accuracy, the area, perimeter and shape indices of the macular foveal avascular zone can be understood. Analyzing the severity of capillary arch damage in the macular area facilitates the targeted scientific intervention \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Not only that, OCTA is a tool that can detect microvascular changes in diabetic retinopathy, including microvascular tumors, non-perfused areas, retinal edema, vascular rings, and intraretinal microvascular changes \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. In addition, OCTA can also provide measurement and quantification of foveal avascular area, vessel density, perfusion density, etc. Changes in these measures of vascular function have almost universally been shown to be associated with increased severity of diabetic retinopathy and worsening vision \u003csup\u003e[\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. These indicators may serve as potential biomarkers of diabetic retinopathy in different courses of disease, and are crucial for predicting the grade of diabetic retinopathy, identifying patients at risk, selecting treatment methods, and observing the effects of follow-up treatment. Therefore, based on this, the ROC curve was also drawn in this study to analyze the predictive values of OCTA for the disease. The results showed that the overall, central concave, paracentric concave, and subcentral concave of the BFD in superficial and deep capillary layer and retinal thickness all have certain predictive values for diabetic retinopathy, and AUC were: 0.888, 0.627, 0.923, 0.771, 0.983, 0.616, 0.882, 0.862, 960, 0.990, 0.897, 0.899, respectively, with good predictive values, indicating that is has a good clinical application value.\u003c/p\u003e \u003cp\u003eIn summary, OCTA examination can clarify the changes of retinal BFD and retinal thickness, and the retinal BFD of the patients is decreased significantly, while the retinal thickness is increased, which may be able to monitor the severity of the patients' conditions, and OCTA examination can be used to predict the disease to a certain extent. It has a significant clinical application value, and it is recommended to be popularized and applied. However, this research is a retrospective analysis with a small sample size, so more samples need to be accumulated to analyze more detailed results, and the correlation between OCTA examination and the severity of the disease has not been analyzed, which needs to be further explored.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eguarantor of integrity of the entire study： R.L. study concepts： R.L.study design： R.L.,Y.W.definition of intellectual content： R.L.literature research：Y.W.experimental studies：Y.W.manuscript preparation：Y.W.manuscript review： R.L.All authors reviewed the manuscript.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMagliano DJ, Boyko EJ. IDF Diabetes Atlas 10th edition scientific committee. IDF DIABETES ATLAS [Internet]. 10th ed. Brussels: International Diabetes Federation; 2021. 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PMID: 26469537.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"OCTA, diabetic retinopathy, retinal blood flow density, retinal thickness","lastPublishedDoi":"10.21203/rs.3.rs-4103894/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4103894/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn our current study, we aim to quantitatively analyze the alterations in retinal BFD and retinal thickness in patients with diabetic retinopathy using optical coherence tomography angiography (OCTA). We analyzed retinal blood flow density (BFD) and thickness in 60 diabetic retinopathy patients using OCTA, comparing them with 60 healthy individuals. Results showed significant lower retinal BFD in the observation group in both superficial and deep capillaries. The retinal thickness of the patients in the observation group was greater. the overall and paracentric concave of the BFD in the superficial capillary layer, the overall and paracentric concave, and subcentral concave of BFD in deep capillary layer, and the overall, central concave, paracentric concave, and subcentral concave of retinal thickness had a certain correlation with diabetic retinopathy. The overall, central concave, paracentric concave, and subcentral concave of the BFD in superficial and deep capillary layer and retinal thickness all had certain predictive values for diabetic retinopathy, and predictive values for the disease were indicated by AUC values ranging from 0.616 to 0.990 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). OCTA examination revealed a notable decrease in retinal BFD and increase in retinal thickness, suggesting its potential as a diagnostic tool for diabetic retinopathy.\u003c/p\u003e","manuscriptTitle":"Quantitative Analysis of the Changes of Retinal Blood Flow Density and Retinal Thickness in Patients with Diabetic Retinopathy by OCTA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-19 15:23:16","doi":"10.21203/rs.3.rs-4103894/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5cce2633-9c3f-46fc-9bc7-781fb8f256f9","owner":[],"postedDate":"March 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-24T12:14:46+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-19 15:23:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4103894","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4103894","identity":"rs-4103894","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}