Correlation between baseline optical coherence tomography angiography quantitative biomarkers and visual outcome in treatment naïve patients with neovascular age-related macular degeneration

Correlation between baseline optical coherence tomography angiography quantitative biomarkers and visual outcome in treatment naïve patients with neovascular age-related macular degeneration | 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 Article Correlation between baseline optical coherence tomography angiography quantitative biomarkers and visual outcome in treatment naïve patients with neovascular age-related macular degeneration Shahin Faghihi, Hooshang Faghihi, Fatemeh Bazvand, Mohammadreza Mehrabi Bahar, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4498944/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract The study aimed to assess different choroidal neovascular network characteristics in relation to changes in best corrected visual acuity (BCVA) over 3 and 12 months following treatment. Using optical coherence tomography angiography, the choroidal neovascular complexes of 46 treatment naïve patients with neovascular age-related macular degeneration (nAMD) were evaluated. The change in BCVA from baseline to 3 months and 12 months after treatment was recorded. The mean vessels percentage area, junctions density, lacunarity, and fractal dimension were significantly correlated with the change of BCVA from baseline to month 3 (P = 0.003, 0.046, 0.007, and 0.005 respectively). FD and vessels percentage area were correlated with the change of BCVA from baseline to month 12 (P = 0.023 and 0.023 respectively). The findings suggest that baseline characteristics of choroidal neovascular complexes may serve as predictors for BCVA changes following treatment with aflibercept in nAMD patients. age-related macular degeneration choroidal neovascularization anti-vascular endothelial growth factor optical coherence tomography angiography Figures Figure 1 Figure 2 Figure 3 Introduction Choroidal neovascularization (CNV) in the context of neovascular age-related macular degeneration (nAMD) is among the leading causes of blindness in the world resulting in significant disabilities despite treatment. 1 The cornerstone of treatment of the disease is intravitreal anti-vascular endothelial growth factor (Anti-VEGF) injection. There are several types of Anti-VEGFs and various kinds of treatment regimens, however, every person could have a different treatment response that may dependent on patient demographics, basic characteristics, genetics background, etc. 2 Generally, the activity of the disease is defined by optical coherence tomography (OCT) as the presence of subretinal fluid (SRF), intraretinal fluid (IRF), and subretinal hyperreflective material(SHRM). 2 This imaging modality has a crucial role in planning treatment and modifying regimens. In addition, several studies have attempted to develop some OCT biomarkers to estimate the treatment response. 1 , 3 With the advent of optical coherence tomography angiography (OCTA) as a fast-none invasive imaging modality, it has garnered a lot of attention from investigators as a useful diagnostic tool for retinal diseases. 4 Today, advanced machines with robust imaging algorithms are able to provide a depth-resolved high-quality image of CNVs architecture in detail. Some previous studies have shown that OCTA outperforms fluorescein angiography (FA) and indocyanine green angiography (ICGA) in demonstrating a CNV network. 5 , 6 Several studies tried to describe CNV appearance based on OCTA images to develop criteria for disease activity and treatment response estimation. 7 , 8 some of these studies are qualitative and others just used a limited number of measures for quantitative analysis. 9 , 10 Moreover, the presence of contradictory findings could be attributed to varying inclusion criteria, such as distinguishing between previously treated eyes and treatment-naïve eyes, or it might be related to differences in interobserver variability when describing the shape of choroidal neovascularization (CNV) or assessing qualitative indices.. 9 , 11 – 15 In this study, our objective was to quantitatively evaluate the OCTA characteristics of treatment-naïve eyes with nAMD. We aimed to investigate any potential correlation between these OCTA features at baseline and the visual recovery observed after administering anti-VEGF treatments. Methods This study is a retrospective case series conducted at the Retina Clinic of Farabi Eye Hospital in Tehran, Iran, involving patients diagnosed with neovascular age-related macular degeneration (nAMD) who received intravitreal aflibercept injections and followed for at least 12 months. Informed consent was obtained from all subjects or their legal guardians. The study was approved by the institutional review board of Tehran University of Medical Sciences (IR.TUMS.FARABIH.REC.1401.014) and complies with tenets of the Declaration of Helsinki. Inclusion criteria were treatment-naïve patients with active nAMD confirmed by two retina specialists (H.R. and E.K.) based on funduscopy, subretinal and/or intraretinal fluid on macular OCT (Spectralis SDOCT, Heidelberg Engineering, Germany), and dye leakage on FA (Spectralis HRA + OCT; Heidelberg Engineering, Heidelberg, Germany) or presence of CNV complex in OCTA (RTVue-XR; Optovue, Inc., Freemont, CA). Pachychoroid spectrum diseases and other causes of CNV were excluded based on a fundus examination, OCT, OCTA, and FA. When the diagnosis was uncertain, Enhanced depth imaging optical coherence tomography (EDI-OCT) and Indocyanine green angiography (ICGA) were performed. Best corrected visual acuity (BCVA) was measured based on early treatment diabetic retinopathy study (ETDRS) charts. Patients with diabetes mellitus, occlusive vascular disorders, refractive error exceeding ± 3 diopters of spherical equivalent, a history of intraocular surgery (except cataract surgery), CNV originating from causes other than AMD, image quality score below 6/10, and CNV complexes located outside the 3 × 3 mm scanning area were excluded from the study. Patients received monthly intravitreal injections of either aflibercept (Eylea, Regeneron, US) or its biosimilar, Tyalia (CinnaGen Company, Iran), for three doses. The previously published investigation demonstrated the non-inferiority of this biosimilar to the reference drug 16 Subsequently, injections were continued every two months for up to 12 months. Patient evaluations were conducted at three time points: baseline, month 3, and the end of 12 months. These evaluations included dilated fundus examination, macular OCT, and measurement of BCVA. All patients underwent macular OCTA at baseline (RTVue-XR; Optovue, Inc., Freemont, CA) with 3 × 3 mm and 6 × 6 mm scan sizes at the central macular area. Removal of the projection artifacts is done using the device's built-in software. The presence of CNV was evaluated on the outer retina and choriocapillaris slabs. Segmentation error was manually corrected to include the entire lesion then images were loaded in the FIJI software (Rasband, W.S., ImageJ, U.S. National Institutes of Health, Bethesda, Maryland, USA, https://imagej.nih.gov/ij ). In the FIJI software, the image type was converted to "8-bit," and subsequently, the "mean threshold" was applied. After manually extracting CNV complexes using the "polygon selection" tool, the images were binarized and skeletonized. (Fig. 1 ) Vascular dispersion (VD) and fractal dimension (FD) were then calculated using the "directionality" and "fractal box count" functions, respectively. 17 The explant area, vessels area, vessels percentage area, total number of junctions, junctions density, total vessels length, average vessels length, total number of endpoints, and mean lacunarity were calculated using AngioTool software version 0.6 (National Institutes of Health®, Bethesda, Maryland, United States). 17 The image analysis was reviewed by two independent retina specialists. Any disagreements existed between interpretations were adjudicated by a third senior retina specialist. To present data we used mean, standard deviation, minimum and maximum, frequency and percentage. To assess the relation of different parameter on VA and its changes during the follow up we used Pearson correlation coefficient as well as scatter plot which demonstrate the simple linear regression equation. To adjust for the effect of age and sex, we used partial correlation coefficient and multiple logistic regression analysis. All statistical analysis performed by SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp).P-value less than 0.05 considered statistically significant. Results We recruited 46 eyes of 46 patients with nAMD to the study. Thirty-two patients (69.6%) were male and 14 were female (30.4%). The mean age of participants was 68.41 ± 5.8 years (range: 55–80). All the patients completed the 12 months follow-up period. The mean baseline BCVA was 55.7 ± 11.03 EDTRS letters which increased to 63.04 ± 12.89 and 62.65 ± 16.53 ETDRS letters at the months three and twelve after treatment, respectively. The mean change in BCVA from baseline to months 3 and 12 were 7.35 ± 9.94 and 6.96 ± 14.74 ETDRS letters, respectively. Among the baseline parameters, The mean vessels percentage area was 56.15 ± 9.98 and its correlation with BCVA changes in month 3 and 12 was statistically significant (P = 0.003, r = 0.442, and P = 0.023, r = 0.345, respectively) (Figs. 2 and 3 ). The correlation between junctions density and BCVA changes was only statistically significant in month 3 (P = 0.046, r = 0.306) (Fig. 2 ). The correlation between mean lacunarity (0.157 ± 0.078) and BCVA changes was statistically significant in month 3 (P = 0.007, r = -0.403) (Fig. 2 ), However, This effect was not seen in month 12 (P = 0.155). The mean of FD was 1.508 ± 0.091 at baseline, and the correlation between baseline FD and BCVA changes in both months 3 and 12 was statistically significant (P = 0.005, r = 0.413, and P = 0.023, r = 0.343, respectively) (Figs. 2 and 3 ). The mean explant area, vessels area, total number of junctions, total vessels length, average vessels length, total number of end points, and vascular dispersion were not significantly correlated with BCVA changes from baseline to both months three and twelve (Table 1 ). Table 1 The bassline quantitative features of CNV tufts. Variable Mean ± SD Pearson correlation and P value† BCVA change in month 3 BCVA change in month 12 Explant area (mm²) 1.704 ± 0.001 Pearson Correlation 0.003 -0.033 P value 0.982 0.834 Vessels area (mm²) 0.930 ± 0.792 Pearson Correlation 0.063 0.026 P value 0.688 0.869 Vessels percentage area 56.15 ± 9.98 Pearson Correlation 0.442 0.345 P value 0.003* 0.023* Total Number of Junctions 86.22 ± 84.53 Pearson Correlation 0.043 0.026 P value 0.786 0.868 Junctions density (n/mm) 0.476 ± 0.101 Pearson Correlation 0.306 0.3 P value 0.046* 0.050 Total Vessels Length (mm) 15.335 ± 13.559 Pearson Correlation 0.032 0.008 P value 0.841 0.960 Average Vessels Length (mm) 5.773 ± 7.401 Pearson Correlation 0.012 0.079 P value 0.938 0.614 Total Number of End Points 25.0 ± 14.8 Pearson Correlation -0.055 -0.119 P value 0.726 0.447 Mean Lacunarity 0.157 ± 0.078 Pearson Correlation -0.403 -0.221 P value 0.007* 0.155 Vascular Dispersion 378.58 ± 2230.63 Pearson Correlation 0.051 0.082 P value 0.744 0.602 Fractal Dimension 1.508 ± 0.091 Pearson Correlation 0.413 0.343 P value 0.005* 0.023* The reported P values are adjusted for age and sex. Statistically significant P values are indicated by an asterisk (*). BCVA (best corrected visual acuity). We stratified patients into two groups based on changes in BCVA from baseline to month 3 and 12. Patients exhibiting a visual gain of more than 15 ETDRS letters (8 patients) were compared to those with a change in BCVA equal to or less than 15 ETDRS letters (38 patients) using multiple logistic regression analysis. Among these subgroups, the only OCT-A quantitative parameters that demonstrated significant differences were vessels percentage area and mean lacunarity, both observed at the 3rd month (Table 2 ). Table 2 Comparison of OCT-A quantitative parameters between patient subgroups based on visual acuity changes at 3 and 12 months. Variables BCVA Change in Month 3 BCVA Change in Month 12 15 ≥ ETDRS letters 15 < ETDRS letters 15 ≥ ETDRS letters 15 < ETDRS letters Mean ± SD Mean ± SD P Mean ± SD Mean ± SD P Explant area (mm²) 1.780 ± 1.457 1.344 ± 0.791 0.393 1.790 ± 1.544 1.507 ± 0.857 0.552 Vessels area (mm²) 0.957 ± 0.849 0.801 ± 0.444 0.590 0.971 ± 0.908 0.835 ± 0.435 0.620 Vessels percentage area 54.82 ± 10.08 62.49 ± 6.89 0.049* 55.01 ± 10.47 58.76 ± 8.53 0.270 Total Number of Junctions 88.95 ± 90.93 73.25 ± 44.77 0.598 91.75 ± 97.47 73.57 ± 42.82 0.536 Junctions density (n/mm) 0.446 ± 0.109 0.526 ± 0.052 0.167 0.477 ± 0.116 0.477 ± 0.072 0.973 Total Vessels Length (mm) 15.867 ± 14.540 12.829 ± 7.555 0.540 16.239 ± 15.553 13.280 ± 7.327 0.528 Average Vessels Length (mm) 6.187 ± 8.024 3.827 ± 2.647 0.408 6.747 ± 8.640 3.558 ± 2.055 0.219 Total Number of End Points 25.66 ± 15.45 21.88 ± 11.53 0.465 25.78 ± 15.79 23.21 ± 12.63 0.632 Mean Lacunarity 0.170 ± 0.079 0.096 ± 0.017 0.037* 0.159 ± 0.076 0.153 ± 0.084 0.800 Fractal Dimension 1.499 ± 0.090 1.554 ± 0.077 0.089 1.500 ± 0.096 1.530 ± 0.072 0.330 The reported P values are adjusted for age and sex using multiple logistic regression analysis. Statistically significant P values are indicated by an asterisk (*). The mean vessels percentage area in the subgroup of patients with a visual gain of more than 15 ETDRS letters and patients with a change of equal to or less than + 15 letters were 62.49 ± 6.89 and 54.82 ± 10.08, respectively. The vessels percentage area was significantly greater in patients with a visual gain of more than 15 letters from baseline to month 3 (P = 0.049). The mean lacunarity in the subgroup of patients with a visual gain of more than 15 ETDRS letters and patients with a change of equal to or less than + 15 letters were 0.10 ± 0.02 and 0.17 ± 0.08, respectively. The mean lacunarity was significantly smaller in patients with a visual gain of more than 15 letters from baseline to month 3 (P = 0.037). Discussion In this study, we assessed the connections between baseline OCTA quantitative morphological CNV parameters and visual acuity improvement following the treatment. To overcome confounding parameters like “normalization” we included treatment naïve active CNVs and measured the visual acuity at month three and one year of follow-up. The normalization hypothesis is a phenomenon that describes the evolution of an immature vascular network to a truncal and mature network over time due to treatment by anti-VEGFs. 10 , 18 Previously Coscas et al, developed a system to score the CNV activity based on some OCTA qualitative parameters including the shape of CNV (sea fan or lacy wheel shape), the presence of tiny capillaries, anastomoses and vessel loops, peripheral arcade, and hyporeflective halo around the lesion. 7 However, the qualitative assessment is highly subject to inter-rater and intra-rater variability. The same group presented an additional intriguing predictive model utilizing quantitative OCTA parameters. They identified variables within the lesion area including vascular density and FD, which prove effective in distinguishing between active and in remission nAMD. The study revealed that measurable blood flow characteristics in OCTA, such as lesion area and FD, seem to be more closely linked with exudation in OCT. 19 Based on these findings, our objective was to ascertain whether specific baseline quantitative morphological parameters of CNV tufts could serve as predictors for the functional response to anti-VEGF treatment in nAMD. Therefore, we tried to implement a quantitative assessment using AngioTool which provides a quantitative measurements. The vessels percentage area represents the ratio of the area occupied by the vessels. Junction density represents the number of vascular junctions per unit of total length of vessels which reflects the density of branching. 20 Lacunarity accounts for structural nonuniformity of vascular complex and more value represents higher voids and gaps and less homogeneity. Some studies have found lacunarity more reproducible than other OCTA parameters of vascular structure. 10 , 21 Fractal dimension is a parameter that reflects morphological complexity, the higher values indicate a more complex vascular network. 21 Our findings suggest to hypothesize that neovascular lesions exhibiting higher baseline vessels percentage area, junctions density, and FD, along with lower lacunarity, may display increased responsiveness to anti-VEGF treatment at the 3-month. Additionally, the percentage area of vessels and the mean lacunarity are two key baseline quantitative factors that can distinguish patients who experience a visual gain of more than 15 ETDRS letters after three months of anti-VEGF therapy from those who do not. It has been shown that immature CNVs with more tangle-young vessels have more values of FD and vessels percentage area. 9 Like our study, Costanzo et al showed that lower perfusion at baseline was associated with poorer treatment response to intravitreal aflibercept injections at the end of the study. 9 This is consistent with previous studies that have shown anti-VEGFs are more effective on capillary micro-vessels compared to mature truncal vessels. 11 , 22 , 23 In contrast, lacunarity as a heterogeneity index of vascular texture which usually has more value in old and previously treated CNVs was negatively correlated with treatment response. These old mature vessels and heterogenous vascular tufts show more resistance to treatment compared to fresh-tangles’ new capillaries. 11 , 22 Out of the measured biomarkers, only vessels percentage area and FD demonstrated the capability to predict visual improvement after one year of treatment. Studies have revealed that CNV lesions displaying heightened arterialization and reduced new vascular sprouting and tiny ramifications, leading to lower FD values, might be associated with a less favorable treatment response. 23 Among the quantitative parameters investigated by Al-Sheikh et.al, higher fractal dimension, along with an elevated rate of small vessel branching were significantly more in actively leaking CNVs in contrast to quiescent ones. 24 However, Told et al didn’t show any correlation between BCVA at month three after treatment with aflibercept and baseline OCTA CNV features measured by AngioTool. 25 They found that vessel density doesn’t change over time and is not a good predictor for treatment response. Miere et al found that there are no different qualitative OCTA features including pruned vascular tree, vascular loop, tangled network, dark halo, and large flow void between active and none active CNVs. 8 Ssimilarly Roberts et al, compared the qualitative and quantitative variables measured by AngioTool between two groups of “good responder” and “poor responder” and they didn’t find any significant parameters correlated with disease activity. 10 However these studies had recruited previously treated eyes, such that in the latter study the median number of previous injections was 34 and they speculated that their contradictory finding might be due to the normalization hypothesis. Regarding other baseline parameters we didn’t find a statistically significant correlation with BCVA improvement at the endpoints. Nevertheless, the prediction of treatment response is a complex entity and several other parameters may play a significant role, making it challenging to rely just on morphological features without considering other factors. 26 Besides there are limitations in OCTA image acquisition as some of the images have significant artifacts that affect the quantitative measurements, making it difficult to use as a routine modality for prediction of treatment response in daily practice. The strength of this study was to include a homogeneous population of nAMD patients treated with the same therapeutic strategy in order to eliminate the confounding factors as the number of injections or the type of drug used. The main drawback of our study primarily arises from the limited sample size, which can be attributed to the stringent inclusion criteria applied to our study population and the retrospective nature of this investigation. Further, we didn’t take into account changes in OCTA parameters over time. Also, this study was conducted in a tertiary care center, which could have led to the recruitment of excessive numbers of chronic cases and selection bias. With the advances in machine learning algorithms and computer vision science, future studies to reveal the baseline OCTA predictors will be more facilitated and promising and will also help in interobserver concordance. In conclusion, our study delved into the connection between baseline quantitative OCTA parameters and visual recovery in treatment-naïve nAMD cases treated with aflibercept. We observed a significant positive correlation between early visual improvement and baseline FD and vessels percentage area values. Conversely, lacunarity displayed a negative correlation with early treatment response. Among the biomarkers analyzed, only vessels percentage area and FD showcased the ability to predict visual improvement after a year of treatment. Declarations Data availability statement: All data during this study are included in this article and can be directed to the corresponding author Author contributions: The authors confirm contribution to the paper as follows: study conception and design: S.F, H.F, F.B, H.R, E.K, and E.A. Data collection, interpretation of results, draft manuscript preparation, and reviewed the manuscript: All authors. Additional Information: The authors declare that they have no conflict of interest. The authors received no financial support for the research, authorship, and publication of this article. References Oliveira, M.A. , et al. Macular atrophy development in neovascular age-related macular degeneration during first year of treatment: Incidence and risk factors. Eur J Ophthalmol 31, 521-528 (2021). Amoaku, W. , et al. Initiation and maintenance of a Treat-and-Extend regimen for ranibizumab therapy in wet age-related macular degeneration: recommendations from the UK Retinal Outcomes Group. 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Cite Share Download PDF Status: Published Journal Publication published 18 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 16 Jul, 2024 Reviews received at journal 12 Jul, 2024 Reviewers agreed at journal 02 Jul, 2024 Reviews received at journal 29 Jun, 2024 Reviewers agreed at journal 20 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviewers agreed at journal 16 Jun, 2024 Reviewers invited by journal 14 Jun, 2024 Editor assigned by journal 14 Jun, 2024 Editor invited by journal 30 May, 2024 Submission checks completed at journal 30 May, 2024 First submitted to journal 29 May, 2024 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. 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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-4498944","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":312531017,"identity":"39f5f066-5cf2-4f8a-b68b-7b21fa66099d","order_by":0,"name":"Shahin Faghihi","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shahin","middleName":"","lastName":"Faghihi","suffix":""},{"id":312531018,"identity":"230d482e-e549-44ec-933e-698d08040f24","order_by":1,"name":"Hooshang Faghihi","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hooshang","middleName":"","lastName":"Faghihi","suffix":""},{"id":312531019,"identity":"8255dc23-b007-4724-8cbe-6e4812db7332","order_by":2,"name":"Fatemeh Bazvand","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Bazvand","suffix":""},{"id":312531020,"identity":"96371cd2-2c74-4353-97cc-601cca1cd0d6","order_by":3,"name":"Mohammadreza Mehrabi Bahar","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohammadreza","middleName":"Mehrabi","lastName":"Bahar","suffix":""},{"id":312531021,"identity":"9ff52184-f12c-4bb8-b77b-0ae56296de03","order_by":4,"name":"Ali Torkashvand","email":"","orcid":"","institution":"Noor Eye Institute","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Torkashvand","suffix":""},{"id":312531022,"identity":"5154a8b7-faf7-412a-9741-a8bcfbd43e28","order_by":5,"name":"Ahmed Husein Ahmed","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"Husein","lastName":"Ahmed","suffix":""},{"id":312531023,"identity":"a69dbbe4-6593-43a0-88ad-9f21722e4ef9","order_by":6,"name":"Masoud Rahimi","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Masoud","middleName":"","lastName":"Rahimi","suffix":""},{"id":312531024,"identity":"9819b58c-294b-4bd3-958d-28f392df85e3","order_by":7,"name":"Ali Akbarzadeh","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Akbarzadeh","suffix":""},{"id":312531025,"identity":"4ddf78f0-8bc8-43f7-94ab-4c92bd5f0d7e","order_by":8,"name":"Esmaeil Asadi Khameneh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYJACiQQwxXyAgbGBeC0GQIotgQQtDGAtPAbEaeHvP/zwxgOGP4lr+898k/i5w0aOgf3w0Q14bbiRZmwBdFjithu52yR7z6QZM/Ckpd3Aa80NBjMJiBbebRK8bYcTGyR4zPBqkT9//BtEy/kzzyT/EqPF4EAO1JYDOWzSRNlieCOnGOgXY+NtQE9Zy7alGbMR8ovc+eMbb/5gkJPddv7ww5tv22zk+NkPH8PvfRBg/AemWCRAJBtB5UiA+QMpqkfBKBgFo2DkAABuqUx4/GKCzAAAAABJRU5ErkJggg==","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Esmaeil","middleName":"Asadi","lastName":"Khameneh","suffix":""},{"id":312531026,"identity":"fe5e8b16-8a2d-4f9c-88d5-3879e5379bde","order_by":9,"name":"Elias Khalili Pour","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Elias","middleName":"Khalili","lastName":"Pour","suffix":""},{"id":312531027,"identity":"1c6cd43f-c2b3-4fe8-9926-73466bf296d6","order_by":10,"name":"Hamid Riazi-Esfahani","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hamid","middleName":"","lastName":"Riazi-Esfahani","suffix":""}],"badges":[],"createdAt":"2024-05-29 19:09:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4498944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4498944/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-75530-x","type":"published","date":"2024-10-18T15:57:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58307743,"identity":"23a301a3-5d47-485c-a3e3-de37da368313","added_by":"auto","created_at":"2024-06-13 18:44:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":589002,"visible":true,"origin":"","legend":"\u003cp\u003eA patient with Neovascular age-related macular degeneration. A and B: Infrared and corresponding spectral domain optical coherence tomography image demonstrates intraretinal fluid, subretinal hyperreflective material, and disruption of outer retinal hyperreflective bands. C: En face outer retina slab of optical coherence tomography angiography shows choroidal neovascular complex. D: The neovascular complex that is extracted from the rest of the outer retina slab. E and F: Corresponding binarized and skeletonized images of choroidal neovascular complex.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4498944/v1/35fdf75a1f483c058118d95b.png"},{"id":58308934,"identity":"16fc7db1-57b0-4df8-b275-bfa7b9118f5c","added_by":"auto","created_at":"2024-06-13 18:52:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":187472,"visible":true,"origin":"","legend":"\u003cp\u003eThe scattered plot shows the relationship between the statistically significant baseline quantitative morphological CNV parameters and the change of BCVA in month 3.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4498944/v1/b98c74f8700ec97c16213a19.png"},{"id":58307742,"identity":"62bce6c6-4165-4cf6-a20e-e33510c1cb39","added_by":"auto","created_at":"2024-06-13 18:44:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":118868,"visible":true,"origin":"","legend":"\u003cp\u003eThe scattered plots show the relationship between the statistically significant baseline quantitative morphological CNV parameters and the change of BCVA in months 12.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4498944/v1/19304d24c4689aea54986170.png"},{"id":67149475,"identity":"7fd206f2-20f3-4410-978d-320ba117472c","added_by":"auto","created_at":"2024-10-21 16:13:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1551994,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4498944/v1/18a8c8c4-62c2-4586-8a0e-6190d7e2a07e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation between baseline optical coherence tomography angiography quantitative biomarkers and visual outcome in treatment naïve patients with neovascular age-related macular degeneration","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChoroidal neovascularization (CNV) in the context of neovascular age-related macular degeneration (nAMD) is among the leading causes of blindness in the world resulting in significant disabilities despite treatment.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The cornerstone of treatment of the disease is intravitreal anti-vascular endothelial growth factor (Anti-VEGF) injection. There are several types of Anti-VEGFs and various kinds of treatment regimens, however, every person could have a different treatment response that may dependent on patient demographics, basic characteristics, genetics background, etc.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Generally, the activity of the disease is defined by optical coherence tomography (OCT) as the presence of subretinal fluid (SRF), intraretinal fluid (IRF), and subretinal hyperreflective material(SHRM).\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e This imaging modality has a crucial role in planning treatment and modifying regimens. In addition, several studies have attempted to develop some OCT biomarkers to estimate the treatment response.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e With the advent of optical coherence tomography angiography (OCTA) as a fast-none invasive imaging modality, it has garnered a lot of attention from investigators as a useful diagnostic tool for retinal diseases.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Today, advanced machines with robust imaging algorithms are able to provide a depth-resolved high-quality image of CNVs architecture in detail. Some previous studies have shown that OCTA outperforms fluorescein angiography (FA) and indocyanine green angiography (ICGA) in demonstrating a CNV network.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Several studies tried to describe CNV appearance based on OCTA images to develop criteria for disease activity and treatment response estimation.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e some of these studies are qualitative and others just used a limited number of measures for quantitative analysis.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Moreover, the presence of contradictory findings could be attributed to varying inclusion criteria, such as distinguishing between previously treated eyes and treatment-naïve eyes, or it might be related to differences in interobserver variability when describing the shape of choroidal neovascularization (CNV) or assessing qualitative indices..\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e–\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In this study, our objective was to quantitatively evaluate the OCTA characteristics of treatment-naïve eyes with nAMD. We aimed to investigate any potential correlation between these OCTA features at baseline and the visual recovery observed after administering anti-VEGF treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eThis study is a retrospective case series conducted at the Retina Clinic of Farabi Eye Hospital in Tehran, Iran, involving patients diagnosed with neovascular age-related macular degeneration (nAMD) who received intravitreal aflibercept injections and followed for at least 12 months. Informed consent was obtained from all subjects or their legal guardians. The study was approved by the institutional review board of Tehran University of Medical Sciences (IR.TUMS.FARABIH.REC.1401.014) and complies with tenets of the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003eInclusion criteria were treatment-naïve patients with active nAMD confirmed by two retina specialists (H.R. and E.K.) based on funduscopy, subretinal and/or intraretinal fluid on macular OCT (Spectralis SDOCT, Heidelberg Engineering, Germany), and dye leakage on FA (Spectralis HRA + OCT; Heidelberg Engineering, Heidelberg, Germany) or presence of CNV complex in OCTA (RTVue-XR; Optovue, Inc., Freemont, CA). Pachychoroid spectrum diseases and other causes of CNV were excluded based on a fundus examination, OCT, OCTA, and FA. When the diagnosis was uncertain, Enhanced depth imaging optical coherence tomography (EDI-OCT) and Indocyanine green angiography (ICGA) were performed. Best corrected visual acuity (BCVA) was measured based on early treatment diabetic retinopathy study (ETDRS) charts.\u003c/p\u003e\u003cp\u003ePatients with diabetes mellitus, occlusive vascular disorders, refractive error exceeding ± 3 diopters of spherical equivalent, a history of intraocular surgery (except cataract surgery), CNV originating from causes other than AMD, image quality score below 6/10, and CNV complexes located outside the 3 × 3 mm scanning area were excluded from the study.\u003c/p\u003e\u003cp\u003ePatients received monthly intravitreal injections of either aflibercept (Eylea, Regeneron, US) or its biosimilar, Tyalia (CinnaGen Company, Iran), for three doses. The previously published investigation demonstrated the non-inferiority of this biosimilar to the reference drug\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Subsequently, injections were continued every two months for up to 12 months.\u003c/p\u003e\u003cp\u003ePatient evaluations were conducted at three time points: baseline, month 3, and the end of 12 months. These evaluations included dilated fundus examination, macular OCT, and measurement of BCVA.\u003c/p\u003e\u003cp\u003eAll patients underwent macular OCTA at baseline (RTVue-XR; Optovue, Inc., Freemont, CA) with 3 × 3 mm and 6 × 6 mm scan sizes at the central macular area. Removal of the projection artifacts is done using the device's built-in software. The presence of CNV was evaluated on the outer retina and choriocapillaris slabs. Segmentation error was manually corrected to include the entire lesion then images were loaded in the FIJI software (Rasband, W.S., ImageJ, U.S. National Institutes of Health, Bethesda, Maryland, USA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij\u003c/span\u003e\u003cspan address=\"https://imagej.nih.gov/ij\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In the FIJI software, the image type was converted to \"8-bit,\" and subsequently, the \"mean threshold\" was applied. After manually extracting CNV complexes using the \"polygon selection\" tool, the images were binarized and skeletonized. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Vascular dispersion (VD) and fractal dimension (FD) were then calculated using the \"directionality\" and \"fractal box count\" functions, respectively.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe explant area, vessels area, vessels percentage area, total number of junctions, junctions density, total vessels length, average vessels length, total number of endpoints, and mean lacunarity were calculated using AngioTool software version 0.6 (National Institutes of Health®, Bethesda, Maryland, United States).\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e The image analysis was reviewed by two independent retina specialists. Any disagreements existed between interpretations were adjudicated by a third senior retina specialist.\u003c/p\u003e\u003cp\u003eTo present data we used mean, standard deviation, minimum and maximum, frequency and percentage. To assess the relation of different parameter on VA and its changes during the follow up we used Pearson correlation coefficient as well as scatter plot which demonstrate the simple linear regression equation. To adjust for the effect of age and sex, we used partial correlation coefficient and multiple logistic regression analysis. All statistical analysis performed by SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp).P-value less than 0.05 considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe recruited 46 eyes of 46 patients with nAMD to the study. Thirty-two patients (69.6%) were male and 14 were female (30.4%). The mean age of participants was 68.41\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 years (range: 55\u0026ndash;80). All the patients completed the 12 months follow-up period. The mean baseline BCVA was 55.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.03 EDTRS letters which increased to 63.04\u0026thinsp;\u0026plusmn;\u0026thinsp;12.89 and 62.65\u0026thinsp;\u0026plusmn;\u0026thinsp;16.53 ETDRS letters at the months three and twelve after treatment, respectively. The mean change in BCVA from baseline to months 3 and 12 were 7.35\u0026thinsp;\u0026plusmn;\u0026thinsp;9.94 and 6.96\u0026thinsp;\u0026plusmn;\u0026thinsp;14.74 ETDRS letters, respectively.\u003c/p\u003e \u003cp\u003eAmong the baseline parameters, The mean vessels percentage area was 56.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.98 and its correlation with BCVA changes in month 3 and 12 was statistically significant (P\u0026thinsp;=\u0026thinsp;0.003, r\u0026thinsp;=\u0026thinsp;0.442, and P\u0026thinsp;=\u0026thinsp;0.023, r\u0026thinsp;=\u0026thinsp;0.345, respectively) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The correlation between junctions density and BCVA changes was only statistically significant in month 3 (P\u0026thinsp;=\u0026thinsp;0.046, r\u0026thinsp;=\u0026thinsp;0.306) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The correlation between mean lacunarity (0.157\u0026thinsp;\u0026plusmn;\u0026thinsp;0.078) and BCVA changes was statistically significant in month 3 (P\u0026thinsp;=\u0026thinsp;0.007, r = -0.403) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), However, This effect was not seen in month 12 (P\u0026thinsp;=\u0026thinsp;0.155). The mean of FD was 1.508\u0026thinsp;\u0026plusmn;\u0026thinsp;0.091 at baseline, and the correlation between baseline FD and BCVA changes in both months 3 and 12 was statistically significant (P\u0026thinsp;=\u0026thinsp;0.005, r\u0026thinsp;=\u0026thinsp;0.413, and P\u0026thinsp;=\u0026thinsp;0.023, r\u0026thinsp;=\u0026thinsp;0.343, respectively) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The mean explant area, vessels area, total number of junctions, total vessels length, average vessels length, total number of end points, and vascular dispersion were not significantly correlated with BCVA changes from baseline to both months three and twelve (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\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 bassline quantitative features of CNV tufts.\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson correlation and P value\u0026dagger;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBCVA change in month 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBCVA change in month 12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExplant area (mm\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.704\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\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-0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVessels area (mm\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.930 \u0026plusmn; 0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVessels percentage area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e56.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\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\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Number of Junctions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e86.22\u0026thinsp;\u0026plusmn;\u0026thinsp;84.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eJunctions density (n/mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.476\u0026thinsp;\u0026plusmn;\u0026thinsp;0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.046*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Vessels Length (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15.335\u0026thinsp;\u0026plusmn;\u0026thinsp;13.559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAverage Vessels Length (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.773\u0026thinsp;\u0026plusmn;\u0026thinsp;7.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Number of End Points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean Lacunarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.157\u0026thinsp;\u0026plusmn;\u0026thinsp;0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVascular Dispersion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e378.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2230.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFractal Dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.508\u0026thinsp;\u0026plusmn;\u0026thinsp;0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eThe reported P values are adjusted for age and sex.\u003c/p\u003e \u003cp\u003eStatistically significant P values are indicated by an asterisk (*).\u003c/p\u003e \u003cp\u003eBCVA (best corrected visual acuity).\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 stratified patients into two groups based on changes in BCVA from baseline to month 3 and 12. Patients exhibiting a visual gain of more than 15 ETDRS letters (8 patients) were compared to those with a change in BCVA equal to or less than 15 ETDRS letters (38 patients) using multiple logistic regression analysis. Among these subgroups, the only OCT-A quantitative parameters that demonstrated significant differences were vessels percentage area and mean lacunarity, both observed at the 3rd month (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eComparison of OCT-A quantitative parameters between patient subgroups based on visual acuity changes at 3 and 12 months.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBCVA Change in Month 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eBCVA Change in Month 12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026thinsp;\u0026ge;\u0026thinsp;ETDRS letters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026lt;\u0026thinsp;ETDRS letters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026thinsp;\u0026ge;\u0026thinsp;ETDRS letters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026thinsp;\u0026lt;\u0026thinsp;ETDRS letters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplant area (mm\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.780\u0026thinsp;\u0026plusmn;\u0026thinsp;1.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.344\u0026thinsp;\u0026plusmn;\u0026thinsp;0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.790\u0026thinsp;\u0026plusmn;\u0026thinsp;1.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.507\u0026thinsp;\u0026plusmn;\u0026thinsp;0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVessels area (mm\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.957\u0026thinsp;\u0026plusmn;\u0026thinsp;0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.801\u0026thinsp;\u0026plusmn;\u0026thinsp;0.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.971\u0026thinsp;\u0026plusmn;\u0026thinsp;0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.835\u0026thinsp;\u0026plusmn;\u0026thinsp;0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVessels percentage area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.82\u0026thinsp;\u0026plusmn;\u0026thinsp;10.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.49 \u0026plusmn; 6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.01\u0026thinsp;\u0026plusmn;\u0026thinsp;10.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Number of Junctions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.95 \u0026plusmn; 90.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.25 \u0026plusmn; 44.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.75 \u0026plusmn; 97.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.57 \u0026plusmn; 42.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunctions density (n/mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.446\u0026thinsp;\u0026plusmn;\u0026thinsp;0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.526\u0026thinsp;\u0026plusmn;\u0026thinsp;0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.477\u0026thinsp;\u0026plusmn;\u0026thinsp;0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.477\u0026thinsp;\u0026plusmn;\u0026thinsp;0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Vessels Length (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.867\u0026thinsp;\u0026plusmn;\u0026thinsp;14.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.829\u0026thinsp;\u0026plusmn;\u0026thinsp;7.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.239\u0026thinsp;\u0026plusmn;\u0026thinsp;15.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.280\u0026thinsp;\u0026plusmn;\u0026thinsp;7.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Vessels Length (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.187\u0026thinsp;\u0026plusmn;\u0026thinsp;8.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.827\u0026thinsp;\u0026plusmn;\u0026thinsp;2.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.747\u0026thinsp;\u0026plusmn;\u0026thinsp;8.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.558\u0026thinsp;\u0026plusmn;\u0026thinsp;2.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Number of End Points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.66\u0026thinsp;\u0026plusmn;\u0026thinsp;15.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.88\u0026thinsp;\u0026plusmn;\u0026thinsp;11.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.78\u0026thinsp;\u0026plusmn;\u0026thinsp;15.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.21\u0026thinsp;\u0026plusmn;\u0026thinsp;12.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Lacunarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.170\u0026thinsp;\u0026plusmn;\u0026thinsp;0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.096\u0026thinsp;\u0026plusmn;\u0026thinsp;0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.037*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.159\u0026thinsp;\u0026plusmn;\u0026thinsp;0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.153\u0026thinsp;\u0026plusmn;\u0026thinsp;0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFractal Dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.499\u0026thinsp;\u0026plusmn;\u0026thinsp;0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.554\u0026thinsp;\u0026plusmn;\u0026thinsp;0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.500\u0026thinsp;\u0026plusmn;\u0026thinsp;0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.530\u0026thinsp;\u0026plusmn;\u0026thinsp;0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eThe reported P values are adjusted for age and sex using multiple logistic regression analysis.\u003c/p\u003e \u003cp\u003eStatistically significant P values are indicated by an asterisk (*).\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\u003eThe mean vessels percentage area in the subgroup of patients with a visual gain of more than 15 ETDRS letters and patients with a change of equal to or less than +\u0026thinsp;15 letters were 62.49\u0026thinsp;\u0026plusmn;\u0026thinsp;6.89 and 54.82\u0026thinsp;\u0026plusmn;\u0026thinsp;10.08, respectively. The vessels percentage area was significantly greater in patients with a visual gain of more than 15 letters from baseline to month 3 (P\u0026thinsp;=\u0026thinsp;0.049).\u003c/p\u003e \u003cp\u003eThe mean lacunarity in the subgroup of patients with a visual gain of more than 15 ETDRS letters and patients with a change of equal to or less than +\u0026thinsp;15 letters were 0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 and 0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08, respectively. The mean lacunarity was significantly smaller in patients with a visual gain of more than 15 letters from baseline to month 3 (P\u0026thinsp;=\u0026thinsp;0.037).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we assessed the connections between baseline OCTA quantitative morphological CNV parameters and visual acuity improvement following the treatment. To overcome confounding parameters like \u0026ldquo;normalization\u0026rdquo; we included treatment na\u0026iuml;ve active CNVs and measured the visual acuity at month three and one year of follow-up. The normalization hypothesis is a phenomenon that describes the evolution of an immature vascular network to a truncal and mature network over time due to treatment by anti-VEGFs.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePreviously Coscas et al, developed a system to score the CNV activity based on some OCTA qualitative parameters including the shape of CNV (sea fan or lacy wheel shape), the presence of tiny capillaries, anastomoses and vessel loops, peripheral arcade, and hyporeflective halo around the lesion. \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, the qualitative assessment is highly subject to inter-rater and intra-rater variability. The same group presented an additional intriguing predictive model utilizing quantitative OCTA parameters. They identified variables within the lesion area including vascular density and FD, which prove effective in distinguishing between active and in remission nAMD. The study revealed that measurable blood flow characteristics in OCTA, such as lesion area and FD, seem to be more closely linked with exudation in OCT.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Based on these findings, our objective was to ascertain whether specific baseline quantitative morphological parameters of CNV tufts could serve as predictors for the functional response to anti-VEGF treatment in nAMD.\u003c/p\u003e \u003cp\u003eTherefore, we tried to implement a quantitative assessment using AngioTool which provides a quantitative measurements. The vessels percentage area represents the ratio of the area occupied by the vessels. Junction density represents the number of vascular junctions per unit of total length of vessels which reflects the density of branching.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Lacunarity accounts for structural nonuniformity of vascular complex and more value represents higher voids and gaps and less homogeneity. Some studies have found lacunarity more reproducible than other OCTA parameters of vascular structure.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Fractal dimension is a parameter that reflects morphological complexity, the higher values indicate a more complex vascular network.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur findings suggest to hypothesize that neovascular lesions exhibiting higher baseline vessels percentage area, junctions density, and FD, along with lower lacunarity, may display increased responsiveness to anti-VEGF treatment at the 3-month. Additionally, the percentage area of vessels and the mean lacunarity are two key baseline quantitative factors that can distinguish patients who experience a visual gain of more than 15 ETDRS letters after three months of anti-VEGF therapy from those who do not. It has been shown that immature CNVs with more tangle-young vessels have more values of FD and vessels percentage area.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Like our study, Costanzo et al showed that lower perfusion at baseline was associated with poorer treatment response to intravitreal aflibercept injections at the end of the study.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e This is consistent with previous studies that have shown anti-VEGFs are more effective on capillary micro-vessels compared to mature truncal vessels. \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e In contrast, lacunarity as a heterogeneity index of vascular texture which usually has more value in old and previously treated CNVs was negatively correlated with treatment response. These old mature vessels and heterogenous vascular tufts show more resistance to treatment compared to fresh-tangles\u0026rsquo; new capillaries.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Out of the measured biomarkers, only vessels percentage area and FD demonstrated the capability to predict visual improvement after one year of treatment. Studies have revealed that CNV lesions displaying heightened arterialization and reduced new vascular sprouting and tiny ramifications, leading to lower FD values, might be associated with a less favorable treatment response.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Among the quantitative parameters investigated by Al-Sheikh et.al, higher fractal dimension, along with an elevated rate of small vessel branching were significantly more in actively leaking CNVs in contrast to quiescent ones.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, Told et al didn\u0026rsquo;t show any correlation between BCVA at month three after treatment with aflibercept and baseline OCTA CNV features measured by AngioTool. \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e They found that vessel density doesn\u0026rsquo;t change over time and is not a good predictor for treatment response. Miere et al found that there are no different qualitative OCTA features including pruned vascular tree, vascular loop, tangled network, dark halo, and large flow void between active and none active CNVs.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003eSsimilarly Roberts et al, compared the qualitative and quantitative variables measured by AngioTool between two groups of \u0026ldquo;good responder\u0026rdquo; and \u0026ldquo;poor responder\u0026rdquo; and they didn\u0026rsquo;t find any significant parameters correlated with disease activity.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e However these studies had recruited previously treated eyes, such that in the latter study the median number of previous injections was 34 and they speculated that their contradictory finding might be due to the normalization hypothesis.\u003c/p\u003e \u003cp\u003eRegarding other baseline parameters we didn\u0026rsquo;t find a statistically significant correlation with BCVA improvement at the endpoints. Nevertheless, the prediction of treatment response is a complex entity and several other parameters may play a significant role, making it challenging to rely just on morphological features without considering other factors. \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Besides there are limitations in OCTA image acquisition as some of the images have significant artifacts that affect the quantitative measurements, making it difficult to use as a routine modality for prediction of treatment response in daily practice.\u003c/p\u003e \u003cp\u003eThe strength of this study was to include a homogeneous population of nAMD patients treated with the same therapeutic strategy in order to eliminate the confounding factors as the number of injections or the type of drug used.\u003c/p\u003e \u003cp\u003eThe main drawback of our study primarily arises from the limited sample size, which can be attributed to the stringent inclusion criteria applied to our study population and the retrospective nature of this investigation. Further, we didn\u0026rsquo;t take into account changes in OCTA parameters over time. Also, this study was conducted in a tertiary care center, which could have led to the recruitment of excessive numbers of chronic cases and selection bias. With the advances in machine learning algorithms and computer vision science, future studies to reveal the baseline OCTA predictors will be more facilitated and promising and will also help in interobserver concordance.\u003c/p\u003e \u003cp\u003eIn conclusion, our study delved into the connection between baseline quantitative OCTA parameters and visual recovery in treatment-na\u0026iuml;ve nAMD cases treated with aflibercept. We observed a significant positive correlation between early visual improvement and baseline FD and vessels percentage area values. Conversely, lacunarity displayed a negative correlation with early treatment response. Among the biomarkers analyzed, only vessels percentage area and FD showcased the ability to predict visual improvement after a year of treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability statement: All data during this study are included in this article and can be directed to the corresponding author\u003c/p\u003e\n\u003cp\u003eAuthor contributions: The authors confirm contribution to the paper as follows: study conception and design: S.F, H.F, F.B, H.R, E.K, and E.A. Data collection, interpretation of results, draft manuscript preparation, and reviewed the manuscript: All authors.\u003c/p\u003e\n\u003cp\u003eAdditional Information: \u0026nbsp;The authors declare that they have no conflict of interest. The authors received no financial support for the research, authorship, and publication of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOliveira, M.A.\u003cem\u003e, et al.\u003c/em\u003e Macular atrophy development in neovascular age-related macular degeneration during first year of treatment: Incidence and risk factors. \u003cem\u003eEur J Ophthalmol\u003c/em\u003e 31, 521-528 (2021).\u003c/li\u003e\n\u003cli\u003eAmoaku, W.\u003cem\u003e, et al.\u003c/em\u003e Initiation and maintenance of a Treat-and-Extend regimen for ranibizumab therapy in wet age-related macular degeneration: recommendations from the UK Retinal Outcomes Group. \u003cem\u003eClin Ophthalmol\u003c/em\u003e 12, 1731-1740 (2018).\u003c/li\u003e\n\u003cli\u003eShijo, T.\u003cem\u003e, et al.\u003c/em\u003e Incidence and risk of advanced age-related macular degeneration in eyes with drusenoid pigment epithelial detachment. \u003cem\u003eSci Rep\u003c/em\u003e 12, 4715 (2022).\u003c/li\u003e\n\u003cli\u003eCoscas, F.\u003cem\u003e, et al.\u003c/em\u003e Optical coherence tomography angiography in exudative age-related macular degeneration: a predictive model for treatment decisions. \u003cem\u003eBr J Ophthalmol\u003c/em\u003e 103, 1342-1346 (2019).\u003c/li\u003e\n\u003cli\u003eBousquet, E.\u003cem\u003e, et al.\u003c/em\u003e Optical Coherence Tomography Angiography of Flat Irregular Pigment Epithelium Detachment in Chronic Central Serous Chorioretinopathy. \u003cem\u003eRetina\u003c/em\u003e 38, 629-638 (2018).\u003c/li\u003e\n\u003cli\u003ede Carlo, T.E.\u003cem\u003e, et al.\u003c/em\u003e Spectral-domain optical coherence tomography angiography of choroidal neovascularization. \u003cem\u003eOphthalmology\u003c/em\u003e 122, 1228-1238 (2015).\u003c/li\u003e\n\u003cli\u003eCoscas, G.J., Lupidi, M., Coscas, F., Cagini, C. \u0026amp; Souied, E.H. 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Incomplete response to Anti-VEGF therapy in neovascular AMD: Exploring disease mechanisms and therapeutic opportunities. \u003cem\u003eProg Retin Eye Res\u003c/em\u003e 82, 100906 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"age-related macular degeneration, choroidal neovascularization, anti-vascular endothelial growth factor, optical coherence tomography angiography","lastPublishedDoi":"10.21203/rs.3.rs-4498944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4498944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study aimed to assess different choroidal neovascular network characteristics in relation to changes in best corrected visual acuity (BCVA) over 3 and 12 months following treatment. Using optical coherence tomography angiography, the choroidal neovascular complexes of 46 treatment na\u0026iuml;ve patients with neovascular age-related macular degeneration (nAMD) were evaluated. The change in BCVA from baseline to 3 months and 12 months after treatment was recorded. The mean vessels percentage area, junctions density, lacunarity, and fractal dimension were significantly correlated with the change of BCVA from baseline to month 3 (P\u0026thinsp;=\u0026thinsp;0.003, 0.046, 0.007, and 0.005 respectively). FD and vessels percentage area were correlated with the change of BCVA from baseline to month 12 (P\u0026thinsp;=\u0026thinsp;0.023 and 0.023 respectively). The findings suggest that baseline characteristics of choroidal neovascular complexes may serve as predictors for BCVA changes following treatment with aflibercept in nAMD patients.\u003c/p\u003e","manuscriptTitle":"Correlation between baseline optical coherence tomography angiography quantitative biomarkers and visual outcome in treatment naïve patients with neovascular age-related macular degeneration","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-13 18:44:29","doi":"10.21203/rs.3.rs-4498944/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-16T06:23:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-13T00:45:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311460475920804994384245253375567142843","date":"2024-07-02T22:55:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-29T13:26:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156614408705394110770099252617465991354","date":"2024-06-20T07:19:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-18T10:45:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35560630523467341826479649224063237692","date":"2024-06-16T22:51:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-14T17:56:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-14T17:37:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-30T14:16:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-30T06:59:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-29T19:08:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"478d83bd-23d1-4b84-9ae3-a3b4b832687c","owner":[],"postedDate":"June 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-21T16:08:08+00:00","versionOfRecord":{"articleIdentity":"rs-4498944","link":"https://doi.org/10.1038/s41598-024-75530-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-18 15:57:41","publishedOnDateReadable":"October 18th, 2024"},"versionCreatedAt":"2024-06-13 18:44:29","video":"","vorDoi":"10.1038/s41598-024-75530-x","vorDoiUrl":"https://doi.org/10.1038/s41598-024-75530-x","workflowStages":[]},"version":"v1","identity":"rs-4498944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4498944","identity":"rs-4498944","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}