Evaluation of Radiation Maculopathy after Treatment of Choroidal Melanoma with Ruthenium-106 using Optical Coherence Tomography Angiography

Evaluation of Radiation Maculopathy after Treatment of Choroidal Melanoma with Ruthenium-106 using Optical Coherence Tomography Angiography | 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 Evaluation of Radiation Maculopathy after Treatment of Choroidal Melanoma with Ruthenium-106 using Optical Coherence Tomography Angiography Ali Torkashvand, Hamid Riazi-Esfahani, Fariba Ghassemi, Elias Khalil Pour, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-362423/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract BACKGROUND : To assess the impact of brachytherapy on macular microvasculature utilizing optical coherence tomography angiography (OCTA) in treated choroidal melanoma. METHODS : In this retrospective observational case series, we reviewed the recorded data of the patients with choroidal melanoma treated with rheuthenium-106 ( 106 Ru) plaque radiotherapy with follow-up period of more than 6 months. Automatically measured OCTA retinal parameters were analyzed after image processing. The non-irradiated fellow eye is considered as the control. RESULTS: Thirty-one eyes of 31 patients with the mean age of 51.1 years were recruited. Six eyes had no radiation maculopathy (RM). From 25 eyes with RM, nine eyes (36%) revealed a burnout macular microvasculature with imperceptible vascular details. Foveal and optic disc radiation dose had the highest value to predict the burnout pattern (ROC, AUC: 0.763, 0.727). Superficial and deep foveal avascular zone (FAZ) were larger in irradiated eyes in comparison to healthy eyes (1629 µm 2 vs. 428 µm 2 , P =0.005; 1837 µm 2 vs 268 µm 2 , P =0.021; respectively). Foveal and parafoveal vascular area density (VAD) and vascular skeleton density (VSD) in both superficial and deep capillary plexus (SCP and DCP) were decreased in all irradiated eyes in comparison with control eyes (P< 0.001). Compared with fellow healthy eyes, irradiated eyes without RM had significantly lower VAD and VSD at foveal and parafoveal DCP (all P<0.02). However, these differences at SCP were not statistically significant. CONCLUSION : The OCTA is a valuable tool for evaluating RM. Initial subclinical microvascular insult after 106 Ru brachytherapy is more likely to occur in DCP. The deep FAZ area was identified as a more critical biomarker of BCVA than superficial FAZ in these patients. Ophthalmology Deep capillary plexus Foveal avascular zone (FAZ) Radiation maculopathy Radiation retinopathy Retina burnout Ruthenium-106 Superficial capillary plexus Figures Figure 1 Figure 2 Background: Ocular melanoma is the most common primary intraocular malignancy.[ 1 , 2 ] Brachytherapy and teleradiotherapy have been used in the treatment of choroidal melanoma in the last decades. Both modes cause microvascular injuries in the retina and optic nerve, resulting in macular and optic disc edema, retinal ischemia, retinal hemorrhage, and neovascularization.[ 3 , 4 ] Radiation retinopathy (RR), first described by Stallard (1993)[ 5 ], is characterized by irreversible endothelial cell damages leading to progressive occlusive vasculopathy.[ 6 ] It seems that small and deep vessels are more susceptible to this damage than the large and superficial retinal vessels.[ 7 ] In 1300 patients with posterior uveal melanoma treated with 125 I (Iodide-125) plaque brachytherapy, Gündüz et al reported a rate of 5% and 43% of RR based on fundus photography (FP) and fluorescein angiography (FA), at 1 and 5 years, respectively.[ 8 ] Using optical coherence tomography (OCT) in 135 uveal melanoma patients treated with 125 I brachytherapy, Horgan et al. demonstrated that the incidence of macular edema was 17%, 40%, and 61% at 6 months, and one and two years thereafter, correspondingly.[ 9 ] Another study showed that macular edema can be detected by OCT even 4 months after irradiation which is nearly 5 months earlier than ophthalmoscopic detection.[ 10 ] Optical coherence tomography angiography (OCTA) has recently emerged as a novel, fast, noninvasive and reproducible imaging modality to evaluate the microvascular status in the macular region. It provides high-resolution quantitative data of both superficial and deep capillary plexus (SCP and DCP) within macular region.[ 11 – 13 ] Changes in capillary density in the macular area after 125 I brachytherapy have been investigated by OCTA in few studies.[ 11 – 13 ] Based on these reports, irradiated eyes had more sectors of non-perfusion areas and microaneurysms, as well as an enlarged foveal avascular area (FAZ) in both SCP and DCP. Even eyes without apparent RM, OCTA has shown significant reduction of capillary density in SCP and DCP.[ 14 ] Widely adopted in Europe, Ruthenium-106 ( 106 Ru) is an alternative isotope to 125 I for brachytherapy of uveal melanoma.[ 15 ] This β-emitting radioisotope has a threefold faster dose fall-off a greater lateral constriction than gamma emitting 125 I, with increasingly lower relative energies for every millimeter of target tissue thickness and normal surrounding tissues.[ 15 , 16 ] [ 16 , 17 ] However, the consequences of 106 Ru plaque brachytherapy on macular vasculature have not been comprehensively assessed by OCTA. In this study, we evaluated the macular OCTA metrics following brachytherapy with 106 Ru plaque for choroidal melanoma in comparison to the healthy fellow eye, to explore the impact of 106 Ru plaque on macular microvasculature. Methods: Our retrospective observational case series have been approved by Farabi Eye Hospital Institutional Review Board and Ethics Committee. The study adhered to the tenets of the Declaration of Helsinki. An informed consent was obtained from all participants. Participants Between 1 February 2019 and 1 January 2020, consecutive patients treated with 106 Ru brachytherapy for uveal melanoma and followed up at least 6 months were enrolled in the study. Surgical details of treatment have already been published elsewhere.[ 18 ] Bilateral same-day OCT and OCTA (Optovue Inc, Fremont, CA) imaging were performed for every patient. For the patients with no evidence of RR in clinical examination and OCT, fluorescein angiography (Heidelberg Engineering, Heidelberg, Germany) and OCTA were performed to obtain more details. Demographic data, pre-treatment tumor characteristics (largest tumor diameter, thickness and location, and distance to fovea and disc), history of retinal disorders (diabetic retinopathy, hypertensive retinopathy), and radiation parameters including radiation dose to tumor apex and base, foveola and optic disc (Gy) were collected from medical documents. Subsequent consolidation therapies for tumor (transpupillary thermotherapy-TTT) and treatments directed for radiation side effects (intravitreal bevacizumab injection and sector laser photocoagulation) were also documented. The exclusion criteria were macular location of the tumor, presence of diabetic or hypertensive retinopathy in the fellow eye, the history of other retinal vascular disorders (e.g., retinal vascular occlusion), glaucoma, macular disorders (age related macular degeneration or choroidal neovascularization), retinal dystrophies and pan-retinal photocoagulation in either eye, previous vitreoretinal surgery, ocular trauma and significant media opacity precluding quality imaging. Considering the presence or absence of RR based on clinical, FA and OCT findings, patients were divided into two subgroups. RR was defined as the presence of macular edema (cystoid or non-cystoid), retinal telangiectasia, microaneurysm, cotton wool spots, exudation, hemorrhage, vascular occlusions, capillary nonperfusion area, and/or neovascularization. Imaging acquisition protocol All OCT and OCTA images were taken by Optovue RTVue XR AVANTI (Optovue Inc, Fremont, CA) device. For OCT scans, the device uses an 840-nm wavelength laser with a 3-mm scan width at macular area and bandwidth of 45 nm to acquire 70,000 A-scans per second and 316 A-scans per B scan. Central foveal thickness (CFT) was documented and three investigators (FG, H.R.E and A.T) examined the images to detect the presence of any sign of RR. The scanning algorithm for OCTA image acquisition starts with 2 B-scans taken before the next sampling location at each fixed spot and two orthogonal OCTA volume scans (one horizontal and one vertical) were taken to reduce fixation changes and motion artifacts. Split-spectrum amplitude-decorrelation angiography algorithm (SSADA) and projection artifact removal (PAR) algorithm is integral module in Angio-Analytics software (version 2017.1.0.151). The segmentation of different layers of the retina was automatically performed. The boundaries of retinal slab for SCP were defined as 3µm below ILM to 15µm below the inner plexiform layer (IPL)-inner nuclear layer (INL) junction. The boundary of retinal slabs for DCP was defined as 15µm to 70µm below IPL-INL junction. All images were reviewed by two assessors (H.R.E and A.T) for image quality and segmentation errors. The segmentations were manually corrected or imaging was repeated, if necessary. If the assessors’ grading differed, a third opinion was sought (FG). Choroidal flow was automatically measured and documented. Patients with OCTA scans that had significant artifacts including defocusing, movement, mirror and shadow artifacts, and/or low signal strength (signal strength less than 5/10) were excluded from the study. If the OCTA images from the involved eye were acceptable, the OCTA images of the non-irradiated fellow eye were considered as the control eye. The eye was classified as a 'burnout' case if the radiation damage was so severe that the vascular structures were not identifiable in OCTA. Vessel density calculation Obtained data were evaluated in the case and the control eyes. There were no variations in SCP and DCP vascular density in both study groups. We noticed that the software wrongly interpreted the increased noise signals in the irradiated eyes due to poor vision and improper fixation as vascular signals. We decided to use image processing to get meaningful results in order to overcome this challenge. All images were exported to Matlab software R2019a (Mathworks, Inc., Natick, MA) for further image processing and analysis. In the preprocessing stage, the original image was converted to the gray scale and then resized to 364x364 pixels. After applying the homomorphic filter and normalization, an area within FAZ was manually selected in each image. Then the average of all pixel values in this area was computed to establish a threshold for being globally subtracted from the original image. Subsequently, the morphological top-hat and bottom-hat operations were applied. This was performed using a disc structural element with a radius of 4 pixels. Then, a bilateral filter was applied for edge preservation and noise reduction. In the next step, a Hessian vesselness filter proposed by Jerman et al,[ 19 ] was employed to improve the contrast of vessels. In the second stage, an Otsu algorithm was applied for the detection of retinal vessels in SCP and DCP.[ 20 ] This algorithm uses a bi-modal histogram to find the optimum threshold in the image. Consequently, a binary image was constructed which included the location of vessels in SCP and DCP. To quantify the retinal vasculature, the skeleton of the image was required. Therefore, the skeletonization was implemented to iteratively thin the segmented vessels until a series of connected lines with a thickness of one pixel remained. In the final stage, vessel area density (VAD) and vessel skeleton density (VSD) was calculated. VAD is calculated as a unitless ratio of the total image area occupied by the vasculature to the total image area in the binary vessel maps. VSD is calculated as the ratio of the length occupied by the blood vessels to the total area in the skeletonized vessel map. [ 13 ] For calculation of foveal and parafoveal VAD and parafoveal VSD, two concentric circles were centered on the fovea with diameters of 1 mm and 3 mm. Then vessel density was calculated in the obtained ring. (Figure-1) FAZ area extraction The FAZ area extraction algorithm was implemented in python using OpenCV and skimage libraries. The first step of FAZ area extraction was binarizing raw images with a variable threshold. The threshold was calculated as only the pixels representing the vessel's margin that were identified by the algorithm and therefore the noise and motion artifacts were excluded. After the binarization of the image, some small white dots persisted in the center of the FAZ region that interfered with the automated determination of the FAZ region margins. These dots were eliminated from the image by morphological hole removal operations. The resulting images were then morphologically opened with a square or rectangular shaped structural elements to link the edges of the detected vessels in the image to form the FAZ area. Finally, the largest connected component that was nearest to the center of the image was selected as the FAZ and the area was calculated in mm 2 based on image size.(Figure-2) STATISTICAL ANALYSIS: All statistical analysis were performed by SPSS software (IBM Corp. Released in 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.). Quantitative data was described as mean ± SD, and a normality test was performed for each variable. We used generalized estimation equation (GEE) to compare vascular indices between two eyes considering inter-eye correlation. Spearman rank correlation method was applied to evaluate the correlation of the variables. Receiver Operating Characteristic analysis (ROC) was performed to define the best variable that could predict the burnout condition in the eye. Logistic regression analysis was used to evaluate the effect of variables on development of RM in irradiated eyes. A p-value of less than 0.05 was considered statistically significant. Results: From 47 patients who had been undergone 106 Ru brachytherapy for extramacular choroidal melanoma, thirty-one eyes of 31 patients were recruited in this study based on the inclusion and exclusion criteria. Sixteen eyes were excluded due to low OCTA picture quality or poor fixation. The mean age of patients was 51.1 ± 14.6 years (range: 22–74 years) and 18 patients (56.8%) were female. The mean time period between brachytherapy and OCTA imaging was 32.8 ± 15.1 months (range: 6–62 months). Right eye was involved in 20 cases (62.5%). All tumors were located in the extramacular area, with a mean largest tumor diameter of 14.0 ± 5.8 mm (range: 8.50–21) and a mean thickness of 6.7 ± 2.2 mm (range: 2.84-10mm). The mean distance between the tumor and the fovea and optic disc was 3.5 ± 3.3 mm (range 2-12mm) and 3.8 ± 3.4 mm (range 0–12 mm), correspondingly. The mean radiation dose to the fovea, optic disc, apex of the tumor, and sclera was 45.7 ± 97.5, 32.9 ± 53.6, 84.2 ± 9.2, and 525.2 ± 298.4 Gy, respectively. The median of BCVA in treated eyes was 0.71 LogMAR (interquartile 25–75: 0.30–1.00 LogMAR) at the time of image acquisition. Adjuvant treatments like TTT, sector retinal laser photocoagulation and intravitreal bevacizumab were performed for 7(22.3%), 15(48.3%) and 19(61.2%) of the cases, respectively. Table 1 provides the baseline characteristics of the participants and treatment features. Table 1 Baseline features of 31 participants and characteristics of the tumor and treatment with 106 Ru brachytherapy Features Age mean (median, range-Y) 51 (55, 22–74) Sex (F) 18 (56.8%) BCVA mean (median, range-LogMAR) 0.71 (0.52, 0.00–3.00) Involved eye (OD) 20 (62.5%) Mean distance to fovea (median, range-mm) 3.53 (3.00, 2.00–12.00) Mean distance to optic disc (median, range-mm) 3.81 (3.00, 0.00–12.00) Mean largest tumor diameter (median, range-mm) 14.08 (14.00,8.50–21.00) Mean thickness (median, range-mm) 6.75 (6.70, 2.84-10) Mean foveal dose (median, range-Gy) 45.76 (11.00, 0.00-501) Mean optic disc dose (median, range-Gy) 32.91 (13.50, 0.00-266) Mean apex dose (median, range-Gy) 84.29 (85, 40–100) Among the 31 eyes, six eyes (19.4%) had no signs of RM based on the funduscopy, FA and OCT results and classified as irradiated eyes without RM, while the remaining 25(80.6%) patients had evidence of maculopathy based on these tests. The mean interval between brachytherapy and OCTA imaging in eyes with and without RM was 34.3 ± 12.1 months and 15.4 ± 14.9 months, respectively. Burnout eyes: From 25 eyes with documented RM, nine eyes (36%) had serious attenuation of retinal vasculature and remarkable macular ischemia (more than 9mm 2 ) with undetectable capillary plexus details in OCTA (burnout macula). Among the tumor characteristics and radiation parameters, the foveal and the optic disc radiation dose had the highest sensitivity and specificity to predict the burnout macula (ROC, AUC: 0.763 and 0.727, correspondingly). Irradiated vs non-irradiated eyes: Table 2 demonstrates the comparison of OCT and OCTA metrics between irradiated (16 eyes with RM and 6 eyes without RM) and non-irradiated eyes. The central foveal thickness (CFT) was more in treated eyes in comparison with the non-irradiated fellow eyes, even though the difference was not significant (291.81 µm vs. 248.46 µm, P = 0.133). Superficial FAZ area was increased in treated eyes (1629 ± 206.3 µm 2 vs 428 ± 778 µm 2 , P = 0.005). Deep FAZ area was also increased in treated eyes in comparison with control eyes (1837 ± 225.2 µm 2 vs 268 ± 120 µm 2 , P = 0.021). The foveal superficial VAD was lower in treated eyes (22.2 ± 8.3 vs 29.4 ± 3.8, P < 0.001). Comparatively, the parafoveal superficial VAD also showed a decrease in the treated eyes (23.54 ± 9.29 vs 32.13 ± 4.11, P < 0.001). Similarly, at DCP, the foveal VAD (23.2 ± 9.3 vs 34.6 ± 3.5, P < 0.001) and parafoveal VAD (24.2 ± 9.9 vs 36.5 ± 3.5, P < 0.001) were lower in irradiated eyes. The VSD was also decreased in both SCP and DCP in the fovea and parafovea area of the irradiated eyes (P < 0.001 for all). (Table 2 ) Choriocapillaris flow area was significantly lower in treated eyes (1.9 ± 0.2 vs 2.1 ± 0.10, P < 0.001). Table 2 Comparison of OCT and OCTA parameters in eyes with or without 106Ru brachytherapy for choroidal melanoma. Treatment status Difference (CI95%) P-value† Yes (n = 22) No (n = 21) Foveal thickness µm 291.81 ± 144.13 248.46 ± 35.08 -44.16 (-101–13.40) 0.133 FAZ µm 2 Superficial 1629 ± 2063 428 ± 778 -1200 (-2036 – -363) 0.005 Deep 1837 ± 2252 268 ± 120 -1569 (-2504 – -634) 0.001 Superficial vascular density % Fovea 22.22 ± 8.33 29.43 ± 3.81 7.24 (3.64–10.84) < 0.001 Parafovea 23.54 ± 9.29 32.13 ± 4.11 8.58 (4.38–12.77 < 0.001 Deep vascular density % Fovea 23.25 ± 9.38 34.67 ± 3.55 11.38 (7.15–15.61) < 0.001 Parafovea 24.29 ± 9.91 36.58 ± 3.54 12.19 (7.57–16.81) < 0.001 Choriocapillaris flow area mm 2 1.92 ± 0.26 2.12 ± 0.10 0.20 (0.09–0.30) < 0.001 Superficial skeleton density % Fovea 8.36 ± 3.43 11.46 ± 1.54 3.13 (1.73–4.53) < 0.001 Parafovea 8.80 ± 3.84 12.47 ± 1.65 3.69 (2.06–5.32) < 0.001 Deep skeleton density % Fovea 10.03 ± 4.11 15.18 ± 1.55 5.14 (3.30–6.98) < 0.001 Parafovea 10.29 ± 4.37 15.90 ± 1.53 5.56 (3.55–7.57) < 0.001 †Based on GEE analysis FAZ: foveal avascular zone Among the baseline tumor features, the best-corrected visual acuity (BCVA-LogMAR) was correlated to foveal dose (r = 0.386, p = 0.032) and deep FAZ area (r = 0.450, p = 0.036). Optic disc dose was correlated with superficial and deep FAZ (r = 0.447, p = 0.048; r = 0.599, P = 0.005; respectively) and showed an inverse correlation with superficial foveal and parafoveal vascular density (r=-0.482, p = 0.023; r=-0.485, P = 0.022; respectively). Irradiated eyes with vs without RM: Table 3 illustrates associations of various factors with RM in irradiated eyes. The foveal and parafoveal VAD and VSD of SCP were lower in eyes with RM; however, this difference was not statistically significant. The same pattern was observed for DCP foveal and parafoveal vascular indexes. The time interval between plaque implantation and image acquisition had a direct modest correlation with RM (34.3 ± 12.1 months vs 15.4 ± 14.9 months, OR: 1.124, 95%CI: 1.021–1.239; P = 0.017). An inverse marginal association was observed between the tumor to fovea distance and the presence of RM (5.67 ± 3.88 vs 3.00 ± 3.02, OR: 0.795, 95%CI: 0.608–1.040; P = 0.094). In multivariate regression analysis after adjusting the effect of age and sex, the time interval between plaque implantation and image acquisition was still significantly associated with RM (OR: 1.118, 95%CI: 1.015–1.231; P = 0.024). Table 3 Association of various parameters with the presence of radiation retinopathy in irradiated eyes. Radiation Retinopathy Odds Ratio (Confidence Interval 95%) P-value† Yes (n = 16) No (n = 6) Age 51.75 ± 14.11 49.00 ± 16.68 1.013 (0.956–1.074) 0.654 Foveal Thickness µm 319 ± 166 237 ± 64 1.004 (0.996–1.012) 0.319 FAZ mm 2 Superficial 1775 ± 2127 311 ± 262 1.005 (0.993–1.016) 0.411 Deep 2023 ± 2303 168 ± 74 1.019 (0.983–1.055) 0.306 Superficial Vascular Area Density % Fovea 20.75 ± 8.72 26.14 ± 6.15 0.913 (0.798–1.044) 0.183 Parafovea 21.98 ± 9.85 27.70 ± 6.54 0.925 (0.820–1.043) 0.204 Deep Vascular area Density % Fovea 22.23 ± 9.94 25.99 ± 7.80 0.955 (0.859–1.062) 0.397 Parafovea 23.20 ± 10.43 27.19 ± 8.50 0.957 (0.865–1.059) 0.396 Superficial vascular Skeleton Density % Fovea 7.76 ± 3.65 9.95 ± 2.29 0.806 (0.585–1.111) 0.189 Parafovea 8.16 ± 4.12 10.49 ± 2.50 0.834 (0.627–1.108) 0.210 Deep vascular Skeleton Density % Fovea 9.51 ± 4.37 11.42 ± 3.24 0.886 (0.694–1.131) 0.330 Parafovea 9.74 ± 4.63 11.77 ± 3.48 0.891 (0.707–1.123) 0.327 Choriocapillaris Flow Area mm 2 1.88 ± 0.28 2.07 ± 0.14 0.019 (0.000–4.470) 0.156 Follow-up Time (m) 34.33 ± 12.17 15.43 ± 14.98 1.124 (1.021–1.239) 0.017 Fovea Dose (Gy) 20.50 ± 29.60 55.42 ± 110.53 1.009 (0.986–1.032) 0.445 Apex Dose (Gy) 83.42 ± 9.51 87.29 ± 7.78 0.889 (0.720–1.097) 0.273 †Based on logistic regression analysis FAZ: foveal avascular zone; In the subgroup of eyes that did not have any signs of RM at the time of acquisition of OCTA, the disparity between mean CFT in irradiated and other eyes was not statistically significant (P = 0.707). The FAZ area was larger in the irradiated eyes compared to the fellow eyes, but these differences for superficial (P = 0.292) and deep FAZ (P = 0.689) were not significant. In this subgroup, VAD and VSD at SCP in both foveal and parafoveal areas of the irradiated eyes were lower, but this differences for superficial VAD (P = 0.282 and P = 0.200, respectively) and superficial VSD of foveal and parafoveal area (P = 0.091 and P = 0.064, respectively) were not significant. In contrast, in the DCP region, the foveal (P = 0.014) and parafoveal VAD (P = 0.016) were significantly decreased in irradiated eyes compared to non-irradiated fellow eyes. A significant difference in both foveal and parafoveal VSD was also detected (P = 0.010 for both). (Table 4 ) Table 4 The OCTA features of irradiated eyes without radiation retinopathy in comparison with the fellow non-radiated eye in the patients with choroidal melanoma. Treatment status Difference (CI95%) P-value† Yes (n = 6) No (n = 6) Retinal foveal thickness µm 237 ± 64 231 ± 61 -5.50 (-34.19–23.19) 0.707 FAZ µm 2 Superficial 612 ± 626 537 ± 447 -75.20 (-215–64.81) 0.292 Deep 339 ± 320 346 ± 333 7.22 (-28.17–42.61) 0.689 Superficial vascular density % Fovea 26.14 ± 6.15 28.70 ± 4.26 2.55 (-2.09–7.20) 0.282 Parafovea 27.70 ± 6.54 31.04 ± 4.71 2.60 (-1.77–8.45) 0.200 Deep vascular density % Fovea 25.99 ± 7.80 34.28 ± 3.22 8.28 (1.65–14.91) 0.014 Parafovea 27.19 ± 8.50 36.19 ± 2.90 9.00 (1.68–16.32) 0.016 Superficial skeleton density % Fovea 9.95 ± 2.29 11.31 ± 1.71 1.35 (-0.21–2.93) 0.091 Parafovea 10.49 ± 2.50 12.18 ± 1.88 1.68 (-0.09–3.47) 0.064 Deep skeleton density % Fovea 11.42 ± 3.24 15.10 ± 1.41 3.68 (0.89–6.46) 0.010 Parafovea 11.77 ± 3.48 15.76 ± 1.39 3.98 (0.93–7.02) 0.010 †Based on GEE analysis FAZ: foveal avascular zone Discussion: Current study revealed that DCP is likely to develop the earliest subclinical radiation induced microvascular insult following 106 Ru plaque brachytherapy. The deep FAZ area was identified as a more critical determinant of BCVA than superficial FAZ in these patients. Among the tumor characteristics and radiation parameters, the foveal dose and the optic disc dose had the highest sensitivity and specificity to predict the burnout pattern of the retinal microvasculature. Choriocapillaris flow area was significantly decreased in the treated eyes. RR may lead to visual morbidity and blindness following choroidal melanoma brachytherapy, in fact in cases of maculopathy.[ 15 – 17 ] The Collaborative Ocular Melanoma Study Group (COMS-report No.16) recorded 6 lines of vision loss in 49% of patients who were treated with 125 I brachytherapy after 3 years. 20 In 43% of patients with an initial vision of 20/200 or better at the time of diagnosis, vision declined gradually to 20/200 or worse by 3 years. [ 21 ] According to previous studies, the risk of RR following brachytherapy is directly linked to the overall dose of administered radiation.[ 22 ] In the treatment of choroidal melanoma, the dose of radiation to the apex of the tumor is between 62–104 Gy based on various studies.[ 23 ] Other factors, such as tumor height and diameter as well as the position of the tumor, are correlated with the risk of retinopathy.[ 22 ] Our results showed that the time interval between plaque implantation and image acquisition is the only independent factor predicting RM based on fundoscopy, FA and/or OCT findings. (Table 3 ) To date, RR diagnosis has been primarily based on biomicroscopic and angiographic data or OCT findings of macular edema.[ 10 ] Few studies investigated the role of OCTA in early detection of RR. Previous studies in patients treated with 125 I plaques have shown that OCTA is probably the most effective existing imaging for detecting early signs of RM.[ 11 – 14 ] OCTA offers a 3-dimensional volumetric scan that displays the segmented distribution of the blood in macular area—something that is not possible with conventional FA. All of our patients were treated with 106 Ru plaque brachytherapy. The study showed that most of the examined OCTA-derived metrics, including the vascular density and FAZ in the SCP and DCP, had been altered in irradiated eyes compared to non-irradiated eyes. According to this report, it appears that the evaluation of the crude data directly obtained from the OCTA instrument is not appropriate for the assessment of vascular density of capillary plexus in the macular area due to the high rate of noises obscuring the information. As reported in previous studies, imaging artifacts and noises may induce some signals and may influence the vascular density and FAZ measurement.[ 12 , 14 ] Despite higher speed of current OCTA machines, these artifacts are usually present in irradiated eyes because of low vision and resulted fixation deficit and apparent structural changes. It is noteworthy that OCTA artifacts are more common in eyes treated by brachytherapy than untreated eyes.[ 14 ] Although, improvements in density measurement could be attained with repeated imaging and fixation aids in some cases, image processing, noise reduction and binarization are usually needed to alleviate this problem. In this study, the images were processed with sufficient filters to generate high-quality valid data for analysis. By measuring the skeleton mass of vessels and minimizing the weight of large vessels, the analysis was made more specified for small vessels that are possibly most commonly affected by radiation.[ 13 ] The endpoints assessed after noise reduction and image processing indicated macular capillary plexus disorganization and obliteration after 106 Ru brachytherapy. Since the manual segmentation and analysis of the images could be a possible source of variability, we designed automated methods to measure biomarkers like VAD, VSD and FAZ area as the strength of this study. Although few studies have reported OCTA results after 125I brachytherapy, no comparable comprehensive study after 106Ru brachytherapy is available.[ 3 , 4 , 11 , 12 , 14 , 24 , 25 ] Veverka et al.[ 26 ] showed gradual alterations of the macular microvasculature on OCTA following melanoma treatment with 125 I plaque. Shields et al.[ 12 ] reported an enlargement of the FAZ region and decreased capillary density in both SCP and DCP after 125 I brachytherapy. In another study[ 14 ], the patients with choroidal melanoma treated with 125 I plaque and normal macular ophthalmoscopy and OCT, showed a statistically significant decrease in density of both SCP and DCP. Most of these studies signified the role of OCTA in the early detection of changes even in eyes without RM. [ 12 , 14 , 24 , 25 ] According to the present research, DCP vascular density decrease (VAD and VSD) in foveal and parafoveal areas is the first biomarker for RM occurring prior to clinical and OCT and FA signs of RM. Consistently, Matet et al [ 27 ] showed that after proton beam therapy, the DCP of irradiated eyes was altered more severely than the SCP. Using volume-rendering display, Spaide showed that in RM, macular edema is associated with DCP non-perfusion.[ 28 ] We assume that in the earlier stage of RM, the measured loss of capillary density could be secondary to a decrease in flow velocity below the predetermined decorrelation threshold of the SSADA algorithm and not a true structural loss of the vessel. Histopathological and ultrastructural studies of the human retina following radiation are extremely scarce and mainly report changes with varying degrees of retinal ischemia and atrophy in the larger retinal and choroidal vessels. Histologic studies have also confirmed the early and preferentially loss of vascular endothelial cells leading to occlusion of capillaries in which pericytes still survived.[ 29 ] Endothelial cell loss is due to impaired cell division and free radical production.[ 3 , 4 , 22 ] More severely affected retina revealed acellular capillaries with the residual basement membrane tubes being typically fused, shrunken or collapsed.[ 6 ] It can be concluded that slower than normal cellular (red and white blood cells) flow in the basement membrane walled tubes could be detected as lower vascular density in both SCP and DCP in the irradiated parts of retina. Radio-sensitivity of the DCP is higher than that of the SCP. The smaller capillaries in DCP are more radiosensitive than larger capillaries in SCP. [ 30 ] The lower perfusion pressure in these capillaries as terminal vessels make them more vulnerable to occlusion after endothelial cell damage or loss. Moreover, studies suggest that blood flows from SCP through serial connections of vertically descending anastomoses and vortex-like channels to the DCP.[ 31 , 32 ] Capillaries of DCP are likely to be terminal vessels and tend to be more sensitive than SCP to ischemic stress, similar to terminal capillaries in other organs, as kidney.[ 32 , 33 ] Even slight changes in retinal circulation may also primarily affect DCP. Some studies, evaluating other retinal vascular disorders such as retinal vein occlusion and diabetic retinopathy, have shown that reduced perfusion is more common in DCP than SCP. 34,35 On the other hand, the DCP non-perfusion has recently been identified as a more critical determinant of BCVA than SCP nonperfusion in patients with retinal vascular disorders.[ 34 , 35 ] We also revealed that the deep FAZ was significantly correlated with BCVA. Finally, DCP flow derives exclusively from SCP, therefore it may receive a larger amount of downstream inflammatory or free radicals from the upstream part of SCP after irradiation.[ 27 ] It seems that, 106 Ru is less destructive to fovea and optic disc compared to 125 I due to a higher dose gradient through the tissue and shorter penetration and lateral distribution.[ 16 , 18 , 36 ] No study has yet compared vascular changes found in OCTA characteristics of retina and choroid following brachytherapy with 125 I and 106 Ru plaques. Despite a higher dose of radiation to the tumor apex (84.29 Gy vs. 71.5 Gy) in our study compared to the report by Shields et al, 14 , the mean dose of radiation to fovea and optic disc was lower (45.76 Gy vs 50.6 Gy and 32.5 Gy vs 40.3 Gy, respectively). The quantitative comparison of our findings with the detailed features reported by Shields et al[ 12 ] showed similar results. From the eyes with documented RM, nine eyes (36%) had severe damages with very extensive macular ischemia in which capillary plexus detail was not detectable in OCTA (burnout). In ROC analysis, the foveal dose and optic disc dose were better parameters for predicting the burnout pattern. However, due to the insufficient number of cases, the macular tolerance threshold could not be calculated. The optic disc dose was positively correlated with superficial and deep FAZ area and had an inverse correlation with foveal and parafoveal SCP vascular density. As a result, foveal and disc radiation doses appear to be the primary predictors of both macular microvascular damage and visual function (BCVA). The limitations of our study are mostly related to the retrospective design and the small number of cases, and imaging acquisition. While extensive efforts have been made to remove the artifacts of OCTA images, the development of new algorithms has not been entirely successful in this period for patients with RR. The study removed low-quality images, a source of selection bias. This may lead to underestimation or oversimplification of the exact impact of radiation on vascular indices. Although we chose the patients who had extra-macular tumors, but adjuvant treatments potential impact were overlooked. According to recent studies, retinal capillary density and FAZ area remain statistically unchanged after intravitreal injection of an anti-VEGF agent or PRP in patients with diabetic retinopathy.[ 37 , 38 ] In addition, we also have not assessed the status of the retinal vasculature at baseline and the longitudinal changes after treatment. In this study, using suitable image processing software added more value to the analysis by reducing abnormal noise and more precise segmentation as a strength. Conclusions: In conclusion, initial subclinical microvascular insult after 106 Ru plaque brachytherapy is more likely to occur in DCP. The deep FAZ area was identified as a more critical biomarker of BCVA than superficial FAZ in these patients. The foveal dose and the optic disc dose had the highest sensitivity and specificity among the tumor characteristics and radiation parameters to predict retinal microvascular burnout. Potential artifacts are more common in irradiated eyes with worse visual function, hence image processing seems to be necessary in these cases prior to image analysis. Future prospective chronologic studies focused on serial OCTA imaging are required to better understand the pathophysiology of RM. List Of Abbreviations Optical coherence tomography angiography (OCTA), Optical coherence tomography (OCT), Rheuthenium-106 (Ru-106), Iodine 125 ( 125 I), Foveal avascular zone (FAZ), Vascular area density (VAD), Vascular skeleton density (VSD), superficial capillary plexuses (SCP), deep capillary plexuses (DCP), Radiation maculopathy (RM), Radiation retinopathy (RR), Proton beam radiotherapy (PBR), Central foveal thickness (CFT), Best corrected visual acuity(BCVA), Inner plexiform layer (IPL), Inner nuclear layer (INL), Transpupillary thermotherapy (TTT). Declarations Ethics approval and consent to participate Written informed consents were obtained from each participant. This study adhered to the tenets of the Declaration of Helsinki and was approved by the ethics committee of Farabi eye hospital, Tehran university of medical sciences. Consent for publication: Written informed consents were obtained from each participant. Availability of data and materials: The datasets generated and/or analysed during the current study are not publicly available due to limitations of ethical approval involving the patient data and anonymity but are available from the corresponding author on reasonable request. Competing interests: None of the authors have any proprietary interests or conflicts of interest related to this submission. Funding : The authors indicate no financial support. Acknowledgments: The authors would like to thank Pooran Fadakar in Farabi Eye Hospital for her attentive contribution and help in this study. Authors’ contributions Concept and design (FG,HRE, HF, BM); data acquisition (HRE, AT, FT, EK, MZ, KF, RD, LE, HM,TM); data analysis/interpretation (FG, KF, HRE, EK, RD,HM,TM); drafting of the manuscript (FG, HRE, HF,KF, RD, HM,LE, TM); critical revision of the manuscript (BM, AT, FT, EK, MZ); supervision (FG,HRE, HF); All authors read and approved the final manuscript. 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Volume Rendering of Dense B-Scan Optical Coherence Tomography Angiography to Evaluate the Connectivity of Macular Blood Flow. Invest Ophthalmol Vis Sci. 2020;61:44. Rahimy E, Sarraf D. Paracentral acute middle maculopathy spectral-domain optical coherence tomography feature of deep capillary ischemia. Curr Opin Ophthalmol. 2014;25:207–12. Yu S, Pang CE, Gong Y, Freund KB, Yannuzzi LA, Rahimy E, et al. The spectrum of superficial and deep capillary ischemia in retinal artery occlusion. Am J Ophthalmol. 2015;159:52–3. Wakabayashi T, Sato T, Hara-Ueno C, Fukushima Y, Sayanagi K, Shiraki N, et al. Retinal Microvasculature and Visual Acuity in Eyes With Branch Retinal Vein Occlusion: Imaging Analysis by Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 2017;58:2087–94. Dupas B, Minvielle W, Bonnin S, Couturier A, Erginay A, Massin P, et al. Association Between Vessel Density and Visual Acuity in Patients With Diabetic Retinopathy and Poorly Controlled Type 1 Diabetes. JAMA Ophthalmol. 2018;136:721–8. Takiar V, Gombos DS, Mourtada F, Rechner LA, Lawyer AA, Morrison WH, et al. Disease control and toxicity outcomes using ruthenium eye plaque brachytherapy in the treatment of uveal melanoma. Pract Radiat Oncol. 2014;4:e189-94. Ghasemi Falavarjani K, Iafe NA, Hubschman J-P, Tsui I, Sadda SR, Sarraf D. Optical Coherence Tomography Angiography Analysis of the Foveal Avascular Zone and Macular Vessel Density After Anti-VEGF Therapy in Eyes With Diabetic Macular Edema and Retinal Vein Occlusion. Invest Ophthalmol Vis Sci. 2017;58:30–4. Faghihi H, Riazi-Esfahani H, Khodabande A, Khalili Pour E, Mirshahi A, Ghassemi F, et al. Effect of panretinal photocoagulation on macular vasculature using optical coherence tomography angiography. Eur J Ophthalmol. 2020;:1120672120952642. doi: 10.1177/1120672120952642 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 20 Sep, 2021 Reviews received at journal 14 Sep, 2021 Reviewers agreed at journal 07 Sep, 2021 Reviews received at journal 09 May, 2021 Reviewers agreed at journal 06 May, 2021 Reviewers agreed at journal 05 May, 2021 Reviewers invited by journal 29 Apr, 2021 Editor assigned by journal 15 Apr, 2021 Editor invited by journal 12 Apr, 2021 Submission checks completed at journal 12 Apr, 2021 First submitted to journal 25 Mar, 2021 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-362423","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":20886729,"identity":"747ef3b7-beea-4423-8d8c-4d06ea893a4b","order_by":0,"name":"Ali Torkashvand","email":"","orcid":"","institution":"Farabi Eye Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Torkashvand","suffix":""},{"id":20886730,"identity":"18623aab-49e6-4aff-89c2-9552a6a58cf1","order_by":1,"name":"Hamid Riazi-Esfahani","email":"","orcid":"","institution":"Farabi Eye 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19:58:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-362423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-362423/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":7971981,"identity":"46c562b3-f73a-40ea-895b-0dfe78bcf1b3","added_by":"auto","created_at":"2021-04-13 17:52:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1455872,"visible":true,"origin":"","legend":"Original and processed images of superficial (upper row: A to E) and deep (lower row: F to J) capillary plexus of a 25-year-old patient, 14 months after plaque radiation. Figure A and F represents the original superficial capillary plexus (SCP) and deep capillary plexus (DCP) images, respectively. Vessel density maps that are binarized images of SCP and DCP and produced after applying denoising and preprocessing algorithms on the original images have been shown in Figures B and G, respectively. Figures C and H show the skeletonization map-a series of connected lines with the thickness of one pixel that represents the route of vessels- in SCP and DCP, respectively. For calculation of the parafoveal vascular and skeleton density, two concentric circles were centered on the fovea with diameters of 1 mm and 3 mm. Figures D and I represent SCP and DCP parafoveal vascular density map and figures E and J show the skeletonization map in corresponding images. ","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-362423/v1/82e01728e3da3beea0db48ce.jpg"},{"id":7971980,"identity":"c37ead09-27da-430c-8878-99cc51530516","added_by":"auto","created_at":"2021-04-13 17:52:21","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1077231,"visible":true,"origin":"","legend":"Foveal avascular zone extraction in superficial capillary plexus (SCP) and deep capillary plexus (DCP) images of right and left eye of a 52-year-old patient with choroidal melanoma who underwent plaque radiotherapy 30 months earlier. Figures A and C show original SCP images and figures E and G represent original DCP images of right and left eye, respectively. The green line in Figures B and D shows the foveal avascular zone (FAZ) area in SCP images and in figures F and H represent the FAZ area in DCP images, respectively.","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-362423/v1/a9f9a40bb4eb980a95b85599.jpg"},{"id":13685855,"identity":"59ea6753-5c78-494e-b709-f944e079d804","added_by":"auto","created_at":"2021-09-17 12:14:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":831517,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-362423/v1/995c7e7b-ef9c-46dd-aaf4-ce17c9989ec2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Radiation Maculopathy after Treatment of Choroidal Melanoma with Ruthenium-106 using Optical Coherence Tomography Angiography","fulltext":[{"header":"Background:","content":" \u003cp\u003eOcular melanoma is the most common primary intraocular malignancy.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Brachytherapy and teleradiotherapy have been used in the treatment of choroidal melanoma in the last decades. Both modes cause microvascular injuries in the retina and optic nerve, resulting in macular and optic disc edema, retinal ischemia, retinal hemorrhage, and neovascularization.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eRadiation retinopathy (RR), first described by Stallard (1993)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], is characterized by irreversible endothelial cell damages leading to progressive occlusive vasculopathy.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] It seems that small and deep vessels are more susceptible to this damage than the large and superficial retinal vessels.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn 1300 patients with posterior uveal melanoma treated with \u003csup\u003e125\u003c/sup\u003eI (Iodide-125) plaque brachytherapy, G\u0026uuml;nd\u0026uuml;z et al reported a rate of 5% and 43% of RR based on fundus photography (FP) and fluorescein angiography (FA), at 1 and 5 years, respectively.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] Using optical coherence tomography (OCT) in 135 uveal melanoma patients treated with \u003csup\u003e125\u003c/sup\u003eI brachytherapy, Horgan et al. demonstrated that the incidence of macular edema was 17%, 40%, and 61% at 6 months, and one and two years thereafter, correspondingly.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] Another study showed that macular edema can be detected by OCT even 4 months after irradiation which is nearly 5 months earlier than ophthalmoscopic detection.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOptical coherence tomography angiography (OCTA) has recently emerged as a novel, fast, noninvasive and reproducible imaging modality to evaluate the microvascular status in the macular region. It provides high-resolution quantitative data of both superficial and deep capillary plexus (SCP and DCP) within macular region.[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Changes in capillary density in the macular area after \u003csup\u003e125\u003c/sup\u003eI brachytherapy have been investigated by OCTA in few studies.[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Based on these reports, irradiated eyes had more sectors of non-perfusion areas and microaneurysms, as well as an enlarged foveal avascular area (FAZ) in both SCP and DCP. Even eyes without apparent RM, OCTA has shown significant reduction of capillary density in SCP and DCP.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWidely adopted in Europe, Ruthenium-106 (\u003csup\u003e106\u003c/sup\u003eRu) is an alternative isotope to \u003csup\u003e125\u003c/sup\u003eI for brachytherapy of uveal melanoma.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] This β-emitting radioisotope has a threefold faster dose fall-off a greater lateral constriction than gamma emitting \u003csup\u003e125\u003c/sup\u003eI, with increasingly lower relative energies for every millimeter of target tissue thickness and normal surrounding tissues.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] However, the consequences of \u003csup\u003e106\u003c/sup\u003eRu plaque brachytherapy on macular vasculature have not been comprehensively assessed by OCTA.\u003c/p\u003e \u003cp\u003eIn this study, we evaluated the macular OCTA metrics following brachytherapy with \u003csup\u003e106\u003c/sup\u003eRu plaque for choroidal melanoma in comparison to the healthy fellow eye, to explore the impact of \u003csup\u003e106\u003c/sup\u003eRu plaque on macular microvasculature.\u003c/p\u003e "},{"header":"Methods:","content":"\u003cp\u003eOur retrospective observational case series have been approved by Farabi Eye Hospital Institutional Review Board and Ethics Committee. The study adhered to the tenets of the Declaration of Helsinki. An informed consent was obtained from all participants.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eParticipants\u003c/h2\u003e\n\u003cp\u003eBetween 1 February 2019 and 1 January 2020, consecutive patients treated with \u003csup\u003e106\u003c/sup\u003eRu brachytherapy for uveal melanoma and followed up at least 6 months were enrolled in the study. Surgical details of treatment have already been published elsewhere.[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eBilateral same-day OCT and OCTA (Optovue Inc, Fremont, CA) imaging were performed for every patient. For the patients with no evidence of RR in clinical examination and OCT, fluorescein angiography (Heidelberg Engineering, Heidelberg, Germany) and OCTA were performed to obtain more details.\u003c/p\u003e\n\u003cp\u003eDemographic data, pre-treatment tumor characteristics (largest tumor diameter, thickness and location, and distance to fovea and disc), history of retinal disorders (diabetic retinopathy, hypertensive retinopathy), and radiation parameters including radiation dose to tumor apex and base, foveola and optic disc (Gy) were collected from medical documents. Subsequent consolidation therapies for tumor (transpupillary thermotherapy-TTT) and treatments directed for radiation side effects (intravitreal bevacizumab injection and sector laser photocoagulation) were also documented.\u003c/p\u003e\n\u003cp\u003eThe exclusion criteria were macular location of the tumor, presence of diabetic or hypertensive retinopathy in the fellow eye, the history of other retinal vascular disorders (e.g., retinal vascular occlusion), glaucoma, macular disorders (age related macular degeneration or choroidal neovascularization), retinal dystrophies and pan-retinal photocoagulation in either eye, previous vitreoretinal surgery, ocular trauma and significant media opacity precluding quality imaging.\u003c/p\u003e\n\u003cp\u003eConsidering the presence or absence of RR based on clinical, FA and OCT findings, patients were divided into two subgroups. RR was defined as the presence of macular edema (cystoid or non-cystoid), retinal telangiectasia, microaneurysm, cotton wool spots, exudation, hemorrhage, vascular occlusions, capillary nonperfusion area, and/or neovascularization.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eImaging acquisition protocol\u003c/h2\u003e\n\u003cp\u003eAll OCT and OCTA images were taken by Optovue RTVue XR AVANTI (Optovue Inc, Fremont, CA) device. For OCT scans, the device uses an 840-nm wavelength laser with a 3-mm scan width at macular area and bandwidth of 45 nm to acquire 70,000 A-scans per second and 316 A-scans per B scan. Central foveal thickness (CFT) was documented and three investigators (FG, H.R.E and A.T) examined the images to detect the presence of any sign of RR.\u003c/p\u003e\n\u003cp\u003eThe scanning algorithm for OCTA image acquisition starts with 2 B-scans taken before the next sampling location at each fixed spot and two orthogonal OCTA volume scans (one horizontal and one vertical) were taken to reduce fixation changes and motion artifacts. Split-spectrum amplitude-decorrelation angiography algorithm (SSADA) and projection artifact removal (PAR) algorithm is integral module in Angio-Analytics software (version 2017.1.0.151). The segmentation of different layers of the retina was automatically performed. The boundaries of retinal slab for SCP were defined as 3\u0026micro;m below ILM to 15\u0026micro;m below the inner plexiform layer (IPL)-inner nuclear layer (INL) junction. The boundary of retinal slabs for DCP was defined as 15\u0026micro;m to 70\u0026micro;m below IPL-INL junction. All images were reviewed by two assessors (H.R.E and A.T) for image quality and segmentation errors. The segmentations were manually corrected or imaging was repeated, if necessary. If the assessors\u0026rsquo; grading differed, a third opinion was sought (FG). Choroidal flow was automatically measured and documented.\u003c/p\u003e\n\u003cp\u003ePatients with OCTA scans that had significant artifacts including defocusing, movement, mirror and shadow artifacts, and/or low signal strength (signal strength less than 5/10) were excluded from the study. If the OCTA images from the involved eye were acceptable, the OCTA images of the non-irradiated fellow eye were considered as the control eye. The eye was classified as a 'burnout' case if the radiation damage was so severe that the vascular structures were not identifiable in OCTA.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003eVessel density calculation\u003c/h2\u003e\n\u003cp\u003eObtained data were evaluated in the case and the control eyes. There were no variations in SCP and DCP vascular density in both study groups. We noticed that the software wrongly interpreted the increased noise signals in the irradiated eyes due to poor vision and improper fixation as vascular signals. We decided to use image processing to get meaningful results in order to overcome this challenge. All images were exported to Matlab software R2019a (Mathworks, Inc., Natick, MA) for further image processing and analysis. In the preprocessing stage, the original image was converted to the gray scale and then resized to 364x364 pixels. After applying the homomorphic filter and normalization, an area within FAZ was manually selected in each image. Then the average of all pixel values in this area was computed to establish a threshold for being globally subtracted from the original image. Subsequently, the morphological top-hat and bottom-hat operations were applied. This was performed using a disc structural element with a radius of 4 pixels. Then, a bilateral filter was applied for edge preservation and noise reduction. In the next step, a Hessian vesselness filter proposed by Jerman et al,[\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e] was employed to improve the contrast of vessels.\u003c/p\u003e\n\u003cp\u003eIn the second stage, an Otsu algorithm was applied for the detection of retinal vessels in SCP and DCP.[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e] This algorithm uses a bi-modal histogram to find the optimum threshold in the image. Consequently, a binary image was constructed which included the location of vessels in SCP and DCP. To quantify the retinal vasculature, the skeleton of the image was required. Therefore, the skeletonization was implemented to iteratively thin the segmented vessels until a series of connected lines with a thickness of one pixel remained.\u003c/p\u003e\n\u003cp\u003eIn the final stage, vessel area density (VAD) and vessel skeleton density (VSD) was calculated. VAD is calculated as a unitless ratio of the total image area occupied by the vasculature to the total image area in the binary vessel maps. VSD is calculated as the ratio of the length occupied by the blood vessels to the total area in the skeletonized vessel map. [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eFor calculation of foveal and parafoveal VAD and parafoveal VSD, two concentric circles were centered on the fovea with diameters of 1 mm and 3 mm. Then vessel density was calculated in the obtained ring. (Figure-1)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eFAZ area extraction\u003c/h2\u003e\n\u003cp\u003eThe FAZ area extraction algorithm was implemented in python using OpenCV and skimage libraries. The first step of FAZ area extraction was binarizing raw images with a variable threshold. The threshold was calculated as only the pixels representing the vessel's margin that were identified by the algorithm and therefore the noise and motion artifacts were excluded. After the binarization of the image, some small white dots persisted in the center of the FAZ region that interfered with the automated determination of the FAZ region margins. These dots were eliminated from the image by morphological hole removal operations. The resulting images were then morphologically opened with a square or rectangular shaped structural elements to link the edges of the detected vessels in the image to form the FAZ area. Finally, the largest connected component that was nearest to the center of the image was selected as the FAZ and the area was calculated in mm\u003csup\u003e2\u003c/sup\u003e based on image size.(Figure-2)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eSTATISTICAL ANALYSIS:\u003c/h2\u003e\n\u003cp\u003eAll statistical analysis were performed by SPSS software (IBM Corp. Released in 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.). Quantitative data was described as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, and a normality test was performed for each variable. We used generalized estimation equation (GEE) to compare vascular indices between two eyes considering inter-eye correlation. Spearman rank correlation method was applied to evaluate the correlation of the variables. Receiver Operating Characteristic analysis (ROC) was performed to define the best variable that could predict the burnout condition in the eye. Logistic regression analysis was used to evaluate the effect of variables on development of RM in irradiated eyes. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results:","content":"\u003cp\u003eFrom 47 patients who had been undergone \u003csup\u003e106\u003c/sup\u003eRu brachytherapy for extramacular choroidal melanoma, thirty-one eyes of 31 patients were recruited in this study based on the inclusion and exclusion criteria. Sixteen eyes were excluded due to low OCTA picture quality or poor fixation. The mean age of patients was 51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6 years (range: 22\u0026ndash;74 years) and 18 patients (56.8%) were female. The mean time period between brachytherapy and OCTA imaging was 32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1 months (range: 6\u0026ndash;62 months). Right eye was involved in 20 cases (62.5%).\u003c/p\u003e\n\u003cp\u003eAll tumors were located in the extramacular area, with a mean largest tumor diameter of 14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 mm (range: 8.50\u0026ndash;21) and a mean thickness of 6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 mm (range: 2.84-10mm). The mean distance between the tumor and the fovea and optic disc was 3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 mm (range 2-12mm) and 3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4 mm (range 0\u0026ndash;12 mm), correspondingly. The mean radiation dose to the fovea, optic disc, apex of the tumor, and sclera was 45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;97.5, 32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;53.6, 84.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2, and 525.2\u0026thinsp;\u0026plusmn;\u0026thinsp;298.4 Gy, respectively. The median of BCVA in treated eyes was 0.71 LogMAR (interquartile 25\u0026ndash;75: 0.30\u0026ndash;1.00 LogMAR) at the time of image acquisition. Adjuvant treatments like TTT, sector retinal laser photocoagulation and intravitreal bevacizumab were performed for 7(22.3%), 15(48.3%) and 19(61.2%) of the cases, respectively. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e provides the baseline characteristics of the participants and treatment features.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline features of 31 participants and characteristics of the tumor and treatment with\u003csup\u003e106\u003c/sup\u003eRu brachytherapy\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFeatures\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge mean (median, range-Y)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51 (55, 22\u0026ndash;74)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex (F)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (56.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBCVA mean (median, range-LogMAR)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.71 (0.52, 0.00\u0026ndash;3.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInvolved eye (OD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (62.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean distance to fovea (median, range-mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.53 (3.00, 2.00\u0026ndash;12.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean distance to optic disc (median, range-mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.81 (3.00, 0.00\u0026ndash;12.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean largest tumor diameter (median, range-mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.08 (14.00,8.50\u0026ndash;21.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean thickness (median, range-mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.75 (6.70, 2.84-10)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean foveal dose (median, range-Gy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.76 (11.00, 0.00-501)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean optic disc dose (median, range-Gy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32.91 (13.50, 0.00-266)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean apex dose (median, range-Gy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84.29 (85, 40\u0026ndash;100)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong the 31 eyes, six eyes (19.4%) had no signs of RM based on the funduscopy, FA and OCT results and classified as irradiated eyes without RM, while the remaining 25(80.6%) patients had evidence of maculopathy based on these tests. The mean interval between brachytherapy and OCTA imaging in eyes with and without RM was 34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1 months and 15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9 months, respectively.\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eBurnout eyes:\u003c/h2\u003e\n\u003cp\u003eFrom 25 eyes with documented RM, nine eyes (36%) had serious attenuation of retinal vasculature and remarkable macular ischemia (more than 9mm\u003csup\u003e2\u003c/sup\u003e) with undetectable capillary plexus details in OCTA (burnout macula). Among the tumor characteristics and radiation parameters, the foveal and the optic disc radiation dose had the highest sensitivity and specificity to predict the burnout macula (ROC, AUC: 0.763 and 0.727, correspondingly).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eIrradiated vs non-irradiated eyes:\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrates the comparison of OCT and OCTA metrics between irradiated (16 eyes with RM and 6 eyes without RM) and non-irradiated eyes. The central foveal thickness (CFT) was more in treated eyes in comparison with the non-irradiated fellow eyes, even though the difference was not significant (291.81 \u0026micro;m vs. 248.46 \u0026micro;m, P\u0026thinsp;=\u0026thinsp;0.133). Superficial FAZ area was increased in treated eyes (1629\u0026thinsp;\u0026plusmn;\u0026thinsp;206.3 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e vs 428\u0026thinsp;\u0026plusmn;\u0026thinsp;778 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.005). Deep FAZ area was also increased in treated eyes in comparison with control eyes (1837\u0026thinsp;\u0026plusmn;\u0026thinsp;225.2 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e vs 268\u0026thinsp;\u0026plusmn;\u0026thinsp;120 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.021). The foveal superficial VAD was lower in treated eyes (22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3 vs 29.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Comparatively, the parafoveal superficial VAD also showed a decrease in the treated eyes (23.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.29 vs 32.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, at DCP, the foveal VAD (23.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3 vs 34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and parafoveal VAD (24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9 vs 36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were lower in irradiated eyes. The VSD was also decreased in both SCP and DCP in the fovea and parafovea area of the irradiated eyes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all). (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) Choriocapillaris flow area was significantly lower in treated eyes (1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 vs 2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eComparison of OCT and OCTA parameters in eyes with or without 106Ru brachytherapy for choroidal melanoma.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\" rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTreatment status\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDifference (CI95%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eP-value\u0026dagger;\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eFoveal thickness \u0026micro;m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e291.81\u0026thinsp;\u0026plusmn;\u0026thinsp;144.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e248.46\u0026thinsp;\u0026plusmn;\u0026thinsp;35.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-44.16 (-101\u0026ndash;13.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.133\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFAZ \u0026micro;m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1629\u0026thinsp;\u0026plusmn;\u0026thinsp;2063\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e428\u0026thinsp;\u0026plusmn;\u0026thinsp;778\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1200 (-2036 \u0026ndash; -363)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1837\u0026thinsp;\u0026plusmn;\u0026thinsp;2252\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e268\u0026thinsp;\u0026plusmn;\u0026thinsp;120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1569 (-2504 \u0026ndash; -634)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial vascular density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.22\u0026thinsp;\u0026plusmn;\u0026thinsp;8.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.24 (3.64\u0026ndash;10.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.58 (4.38\u0026ndash;12.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep vascular density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.25\u0026thinsp;\u0026plusmn;\u0026thinsp;9.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.38 (7.15\u0026ndash;15.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.29\u0026thinsp;\u0026plusmn;\u0026thinsp;9.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.19 (7.57\u0026ndash;16.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eChoriocapillaris flow area mm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.20 (0.09\u0026ndash;0.30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial skeleton density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.36\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.13 (1.73\u0026ndash;4.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.69 (2.06\u0026ndash;5.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep skeleton density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.14 (3.30\u0026ndash;6.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.29\u0026thinsp;\u0026plusmn;\u0026thinsp;4.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.56 (3.55\u0026ndash;7.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u0026dagger;Based on GEE analysis\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eFAZ: foveal avascular zone\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong the baseline tumor features, the best-corrected visual acuity (BCVA-LogMAR) was correlated to foveal dose (r\u0026thinsp;=\u0026thinsp;0.386, p\u0026thinsp;=\u0026thinsp;0.032) and deep FAZ area (r\u0026thinsp;=\u0026thinsp;0.450, p\u0026thinsp;=\u0026thinsp;0.036). Optic disc dose was correlated with superficial and deep FAZ (r\u0026thinsp;=\u0026thinsp;0.447, p\u0026thinsp;=\u0026thinsp;0.048; r\u0026thinsp;=\u0026thinsp;0.599, P\u0026thinsp;=\u0026thinsp;0.005; respectively) and showed an inverse correlation with superficial foveal and parafoveal vascular density (r=-0.482, p\u0026thinsp;=\u0026thinsp;0.023; r=-0.485, P\u0026thinsp;=\u0026thinsp;0.022; respectively).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eIrradiated eyes with vs without RM:\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates associations of various factors with RM in irradiated eyes. The foveal and parafoveal VAD and VSD of SCP were lower in eyes with RM; however, this difference was not statistically significant. The same pattern was observed for DCP foveal and parafoveal vascular indexes. The time interval between plaque implantation and image acquisition had a direct modest correlation with RM (34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1 months vs 15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9 months, OR: 1.124, 95%CI: 1.021\u0026ndash;1.239; P\u0026thinsp;=\u0026thinsp;0.017). An inverse marginal association was observed between the tumor to fovea distance and the presence of RM (5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88 vs 3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02, OR: 0.795, 95%CI: 0.608\u0026ndash;1.040; P\u0026thinsp;=\u0026thinsp;0.094). In multivariate regression analysis after adjusting the effect of age and sex, the time interval between plaque implantation and image acquisition was still significantly associated with RM (OR: 1.118, 95%CI: 1.015\u0026ndash;1.231; P\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAssociation of various parameters with the presence of radiation retinopathy in irradiated eyes.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRadiation Retinopathy\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eOdds Ratio\u003c/p\u003e\n\u003cp\u003e(Confidence Interval 95%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eP-value\u0026dagger;\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.75\u0026thinsp;\u0026plusmn;\u0026thinsp;14.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.00\u0026thinsp;\u0026plusmn;\u0026thinsp;16.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.013 (0.956\u0026ndash;1.074)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.654\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFoveal Thickness \u0026micro;m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e319\u0026thinsp;\u0026plusmn;\u0026thinsp;166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e237\u0026thinsp;\u0026plusmn;\u0026thinsp;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.004 (0.996\u0026ndash;1.012)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.319\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFAZ mm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSuperficial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1775\u0026thinsp;\u0026plusmn;\u0026thinsp;2127\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e311\u0026thinsp;\u0026plusmn;\u0026thinsp;262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.005 (0.993\u0026ndash;1.016)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.411\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2023\u0026thinsp;\u0026plusmn;\u0026thinsp;2303\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e168\u0026thinsp;\u0026plusmn;\u0026thinsp;74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.019 (0.983\u0026ndash;1.055)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.306\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial Vascular Area Density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.75\u0026thinsp;\u0026plusmn;\u0026thinsp;8.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.913 (0.798\u0026ndash;1.044)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.183\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.98\u0026thinsp;\u0026plusmn;\u0026thinsp;9.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.925 (0.820\u0026ndash;1.043)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.204\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep Vascular area Density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.23\u0026thinsp;\u0026plusmn;\u0026thinsp;9.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.99\u0026thinsp;\u0026plusmn;\u0026thinsp;7.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.955 (0.859\u0026ndash;1.062)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.397\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.20\u0026thinsp;\u0026plusmn;\u0026thinsp;10.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.19\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.957 (0.865\u0026ndash;1.059)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.396\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial vascular Skeleton Density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.95\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.806 (0.585\u0026ndash;1.111)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.189\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.16\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.834 (0.627\u0026ndash;1.108)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.210\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep vascular Skeleton Density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.886 (0.694\u0026ndash;1.131)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.330\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.74\u0026thinsp;\u0026plusmn;\u0026thinsp;4.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.891 (0.707\u0026ndash;1.123)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.327\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eChoriocapillaris Flow Area mm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.019 (0.000\u0026ndash;4.470)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.156\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFollow-up Time (m)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.33\u0026thinsp;\u0026plusmn;\u0026thinsp;12.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.43\u0026thinsp;\u0026plusmn;\u0026thinsp;14.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.124 (1.021\u0026ndash;1.239)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFovea Dose (Gy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.50\u0026thinsp;\u0026plusmn;\u0026thinsp;29.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.42\u0026thinsp;\u0026plusmn;\u0026thinsp;110.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.009 (0.986\u0026ndash;1.032)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.445\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eApex Dose (Gy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e83.42\u0026thinsp;\u0026plusmn;\u0026thinsp;9.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87.29\u0026thinsp;\u0026plusmn;\u0026thinsp;7.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.889 (0.720\u0026ndash;1.097)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.273\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u0026dagger;Based on logistic regression analysis\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eFAZ: foveal avascular zone;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn the subgroup of eyes that did not have any signs of RM at the time of acquisition of OCTA, the disparity between mean CFT in irradiated and other eyes was not statistically significant (P\u0026thinsp;=\u0026thinsp;0.707). The FAZ area was larger in the irradiated eyes compared to the fellow eyes, but these differences for superficial (P\u0026thinsp;=\u0026thinsp;0.292) and deep FAZ (P\u0026thinsp;=\u0026thinsp;0.689) were not significant.\u003c/p\u003e\n\u003cp\u003eIn this subgroup, VAD and VSD at SCP in both foveal and parafoveal areas of the irradiated eyes were lower, but this differences for superficial VAD (P\u0026thinsp;=\u0026thinsp;0.282 and P\u0026thinsp;=\u0026thinsp;0.200, respectively) and superficial VSD of foveal and parafoveal area (P\u0026thinsp;=\u0026thinsp;0.091 and P\u0026thinsp;=\u0026thinsp;0.064, respectively) were not significant. In contrast, in the DCP region, the foveal (P\u0026thinsp;=\u0026thinsp;0.014) and parafoveal VAD (P\u0026thinsp;=\u0026thinsp;0.016) were significantly decreased in irradiated eyes compared to non-irradiated fellow eyes. A significant difference in both foveal and parafoveal VSD was also detected (P\u0026thinsp;=\u0026thinsp;0.010 for both). (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe OCTA features of irradiated eyes without radiation retinopathy in comparison with the fellow non-radiated eye in the patients with choroidal melanoma.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003cth style=\"height: 70px;\" colspan=\"3\" rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTreatment status\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 70px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDifference (CI95%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 70px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eP-value\u0026dagger;\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003cth style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eRetinal foveal thickness \u0026micro;m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e237\u0026thinsp;\u0026plusmn;\u0026thinsp;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e231\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e-5.50 (-34.19\u0026ndash;23.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.707\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFAZ \u0026micro;m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e612\u0026thinsp;\u0026plusmn;\u0026thinsp;626\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e537\u0026thinsp;\u0026plusmn;\u0026thinsp;447\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e-75.20 (-215\u0026ndash;64.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.292\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e339\u0026thinsp;\u0026plusmn;\u0026thinsp;320\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e346\u0026thinsp;\u0026plusmn;\u0026thinsp;333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e7.22 (-28.17\u0026ndash;42.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.689\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial vascular density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e28.70\u0026thinsp;\u0026plusmn;\u0026thinsp;4.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e2.55 (-2.09\u0026ndash;7.20)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.282\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e27.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e31.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e2.60 (-1.77\u0026ndash;8.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep vascular density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e25.99\u0026thinsp;\u0026plusmn;\u0026thinsp;7.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e34.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e8.28 (1.65\u0026ndash;14.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e27.19\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e36.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e9.00 (1.68\u0026ndash;16.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSuperficial skeleton density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e9.95\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e11.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e1.35 (-0.21\u0026ndash;2.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.091\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e10.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e12.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e1.68 (-0.09\u0026ndash;3.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.064\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDeep skeleton density %\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e11.42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e15.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e3.68 (0.89\u0026ndash;6.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eParafovea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e15.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e3.98 (0.93\u0026ndash;7.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr style=\"height: 13px;\"\u003e\n\u003ctd style=\"height: 13px;\" colspan=\"7\"\u003e\u0026dagger;Based on GEE analysis\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 13.2375px;\"\u003e\n\u003ctd style=\"height: 13.2375px;\" colspan=\"7\"\u003eFAZ: foveal avascular zone\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion:","content":" \u003cp\u003eCurrent study revealed that DCP is likely to develop the earliest subclinical radiation induced microvascular insult following \u003csup\u003e106\u003c/sup\u003eRu plaque brachytherapy. The deep FAZ area was identified as a more critical determinant of BCVA than superficial FAZ in these patients. Among the tumor characteristics and radiation parameters, the foveal dose and the optic disc dose had the highest sensitivity and specificity to predict the burnout pattern of the retinal microvasculature. Choriocapillaris flow area was significantly decreased in the treated eyes.\u003c/p\u003e \u003cp\u003eRR may lead to visual morbidity and blindness following choroidal melanoma brachytherapy, in fact in cases of maculopathy.[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] The Collaborative Ocular Melanoma Study Group (COMS-report No.16) recorded 6 lines of vision loss in 49% of patients who were treated with \u003csup\u003e125\u003c/sup\u003eI brachytherapy after 3 years. \u003csup\u003e20\u003c/sup\u003e In 43% of patients with an initial vision of 20/200 or better at the time of diagnosis, vision declined gradually to 20/200 or worse by 3 years. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAccording to previous studies, the risk of RR following brachytherapy is directly linked to the overall dose of administered radiation.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] In the treatment of choroidal melanoma, the dose of radiation to the apex of the tumor is between 62\u0026ndash;104 Gy based on various studies.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Other factors, such as tumor height and diameter as well as the position of the tumor, are correlated with the risk of retinopathy.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Our results showed that the time interval between plaque implantation and image acquisition is the only independent factor predicting RM based on fundoscopy, FA and/or OCT findings. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eTo date, RR diagnosis has been primarily based on biomicroscopic and angiographic data or OCT findings of macular edema.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Few studies investigated the role of OCTA in early detection of RR. Previous studies in patients treated with \u003csup\u003e125\u003c/sup\u003eI plaques have shown that OCTA is probably the most effective existing imaging for detecting early signs of RM.[\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] OCTA offers a 3-dimensional volumetric scan that displays the segmented distribution of the blood in macular area\u0026mdash;something that is not possible with conventional FA. All of our patients were treated with \u003csup\u003e106\u003c/sup\u003eRu plaque brachytherapy. The study showed that most of the examined OCTA-derived metrics, including the vascular density and FAZ in the SCP and DCP, had been altered in irradiated eyes compared to non-irradiated eyes.\u003c/p\u003e \u003cp\u003eAccording to this report, it appears that the evaluation of the crude data directly obtained from the OCTA instrument is not appropriate for the assessment of vascular density of capillary plexus in the macular area due to the high rate of noises obscuring the information. As reported in previous studies, imaging artifacts and noises may induce some signals and may influence the vascular density and FAZ measurement.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Despite higher speed of current OCTA machines, these artifacts are usually present in irradiated eyes because of low vision and resulted fixation deficit and apparent structural changes. It is noteworthy that OCTA artifacts are more common in eyes treated by brachytherapy than untreated eyes.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Although, improvements in density measurement could be attained with repeated imaging and fixation aids in some cases, image processing, noise reduction and binarization are usually needed to alleviate this problem. In this study, the images were processed with sufficient filters to generate high-quality valid data for analysis.\u003c/p\u003e \u003cp\u003eBy measuring the skeleton mass of vessels and minimizing the weight of large vessels, the analysis was made more specified for small vessels that are possibly most commonly affected by radiation.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] The endpoints assessed after noise reduction and image processing indicated macular capillary plexus disorganization and obliteration after \u003csup\u003e106\u003c/sup\u003eRu brachytherapy. Since the manual segmentation and analysis of the images could be a possible source of variability, we designed automated methods to measure biomarkers like VAD, VSD and FAZ area as the strength of this study.\u003c/p\u003e \u003cp\u003eAlthough few studies have reported OCTA results after 125I brachytherapy, no comparable comprehensive study after 106Ru brachytherapy is available.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] Veverka et al.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] showed gradual alterations of the macular microvasculature on OCTA following melanoma treatment with \u003csup\u003e125\u003c/sup\u003eI plaque. Shields et al.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] reported an enlargement of the FAZ region and decreased capillary density in both SCP and DCP after \u003csup\u003e125\u003c/sup\u003eI brachytherapy. In another study[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], the patients with choroidal melanoma treated with \u003csup\u003e125\u003c/sup\u003eI plaque and normal macular ophthalmoscopy and OCT, showed a statistically significant decrease in density of both SCP and DCP. Most of these studies signified the role of OCTA in the early detection of changes even in eyes without RM. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] According to the present research, DCP vascular density decrease (VAD and VSD) in foveal and parafoveal areas is the first biomarker for RM occurring prior to clinical and OCT and FA signs of RM. Consistently, Matet et al [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] showed that after proton beam therapy, the DCP of irradiated eyes was altered more severely than the SCP. Using volume-rendering display, Spaide showed that in RM, macular edema is associated with DCP non-perfusion.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWe assume that in the earlier stage of RM, the measured loss of capillary density could be secondary to a decrease in flow velocity below the predetermined decorrelation threshold of the SSADA algorithm and not a true structural loss of the vessel. Histopathological and ultrastructural studies of the human retina following radiation are extremely scarce and mainly report changes with varying degrees of retinal ischemia and atrophy in the larger retinal and choroidal vessels. Histologic studies have also confirmed the early and preferentially loss of vascular endothelial cells leading to occlusion of capillaries in which pericytes still survived.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] Endothelial cell loss is due to impaired cell division and free radical production.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] More severely affected retina revealed acellular capillaries with the residual basement membrane tubes being typically fused, shrunken or collapsed.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] It can be concluded that slower than normal cellular (red and white blood cells) flow in the basement membrane walled tubes could be detected as lower vascular density in both SCP and DCP in the irradiated parts of retina.\u003c/p\u003e \u003cp\u003eRadio-sensitivity of the DCP is higher than that of the SCP. The smaller capillaries in DCP are more radiosensitive than larger capillaries in SCP. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] The lower perfusion pressure in these capillaries as terminal vessels make them more vulnerable to occlusion after endothelial cell damage or loss. Moreover, studies suggest that blood flows from SCP through serial connections of vertically descending anastomoses and vortex-like channels to the DCP.[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] Capillaries of DCP are likely to be terminal vessels and tend to be more sensitive than SCP to ischemic stress, similar to terminal capillaries in other organs, as kidney.[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] Even slight changes in retinal circulation may also primarily affect DCP.\u003c/p\u003e \u003cp\u003eSome studies, evaluating other retinal vascular disorders such as retinal vein occlusion and diabetic retinopathy, have shown that reduced perfusion is more common in DCP than SCP.\u003csup\u003e34,35\u003c/sup\u003e On the other hand, the DCP non-perfusion has recently been identified as a more critical determinant of BCVA than SCP nonperfusion in patients with retinal vascular disorders.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] We also revealed that the deep FAZ was significantly correlated with BCVA. Finally, DCP flow derives exclusively from SCP, therefore it may receive a larger amount of downstream inflammatory or free radicals from the upstream part of SCP after irradiation.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIt seems that, \u003csup\u003e106\u003c/sup\u003eRu is less destructive to fovea and optic disc compared to \u003csup\u003e125\u003c/sup\u003eI due to a higher dose gradient through the tissue and shorter penetration and lateral distribution.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] No study has yet compared vascular changes found in OCTA characteristics of retina and choroid following brachytherapy with \u003csup\u003e125\u003c/sup\u003eI and \u003csup\u003e106\u003c/sup\u003eRu plaques. Despite a higher dose of radiation to the tumor apex (84.29 Gy vs. 71.5 Gy) in our study compared to the report by Shields et al,\u003csup\u003e14\u003c/sup\u003e, the mean dose of radiation to fovea and optic disc was lower (45.76 Gy vs 50.6 Gy and 32.5 Gy vs 40.3 Gy, respectively). The quantitative comparison of our findings with the detailed features reported by Shields et al[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] showed similar results.\u003c/p\u003e \u003cp\u003eFrom the eyes with documented RM, nine eyes (36%) had severe damages with very extensive macular ischemia in which capillary plexus detail was not detectable in OCTA (burnout). In ROC analysis, the foveal dose and optic disc dose were better parameters for predicting the burnout pattern. However, due to the insufficient number of cases, the macular tolerance threshold could not be calculated.\u003c/p\u003e \u003cp\u003eThe optic disc dose was positively correlated with superficial and deep FAZ area and had an inverse correlation with foveal and parafoveal SCP vascular density. As a result, foveal and disc radiation doses appear to be the primary predictors of both macular microvascular damage and visual function (BCVA).\u003c/p\u003e \u003cp\u003eThe limitations of our study are mostly related to the retrospective design and the small number of cases, and imaging acquisition. While extensive efforts have been made to remove the artifacts of OCTA images, the development of new algorithms has not been entirely successful in this period for patients with RR. The study removed low-quality images, a source of selection bias. This may lead to underestimation or oversimplification of the exact impact of radiation on vascular indices.\u003c/p\u003e \u003cp\u003eAlthough we chose the patients who had extra-macular tumors, but adjuvant treatments potential impact were overlooked. According to recent studies, retinal capillary density and FAZ area remain statistically unchanged after intravitreal injection of an anti-VEGF agent or PRP in patients with diabetic retinopathy.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] In addition, we also have not assessed the status of the retinal vasculature at baseline and the longitudinal changes after treatment.\u003c/p\u003e \u003cp\u003eIn this study, using suitable image processing software added more value to the analysis by reducing abnormal noise and more precise segmentation as a strength.\u003c/p\u003e "},{"header":"Conclusions:","content":" \u003cp\u003eIn conclusion, initial subclinical microvascular insult after \u003csup\u003e106\u003c/sup\u003eRu plaque brachytherapy is more likely to occur in DCP. The deep FAZ area was identified as a more critical biomarker of BCVA than superficial FAZ in these patients. The foveal dose and the optic disc dose had the highest sensitivity and specificity among the tumor characteristics and radiation parameters to predict retinal microvascular burnout. Potential artifacts are more common in irradiated eyes with worse visual function, hence image processing seems to be necessary in these cases prior to image analysis. Future prospective chronologic studies focused on serial OCTA imaging are required to better understand the pathophysiology of RM.\u003c/p\u003e "},{"header":"List Of Abbreviations","content":" \u003cp\u003eOptical coherence tomography angiography (OCTA), Optical coherence tomography (OCT), Rheuthenium-106 (Ru-106), Iodine 125 (\u003csup\u003e125\u003c/sup\u003eI), Foveal avascular zone (FAZ), Vascular area density (VAD), Vascular skeleton density (VSD), superficial capillary plexuses (SCP), deep capillary plexuses (DCP), Radiation maculopathy (RM), Radiation retinopathy (RR), Proton beam radiotherapy (PBR), Central foveal thickness (CFT), Best corrected visual acuity(BCVA), Inner plexiform layer (IPL), Inner nuclear layer (INL), Transpupillary thermotherapy (TTT).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\n\u003cul\u003e\n\u003cli\u003eWritten informed consents were obtained from each participant.\u003c/li\u003e\n\u003cli\u003eThis study adhered to the tenets of the Declaration of Helsinki and was approved by the ethics committee of Farabi eye hospital, Tehran university of medical sciences.\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Written informed consents were obtained from each participant.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAvailability of data and materials: \u003c/strong\u003eThe datasets generated and/or analysed during the current study are not publicly available due to limitations of ethical approval involving the patient data and anonymity but are available from the corresponding author on reasonable request.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e None of the authors have any proprietary interests or conflicts of interest related to this submission.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: The authors indicate no financial support.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAcknowledgments: \u003c/strong\u003eThe authors would like to thank Pooran Fadakar in Farabi Eye Hospital for her attentive contribution and help in this study.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eConcept and design (FG,HRE, HF, BM); data acquisition (HRE, AT, FT, EK, MZ, KF, RD, LE, HM,TM); data analysis/interpretation (FG, KF, HRE, EK, RD,HM,TM); drafting of the manuscript (FG, HRE, HF,KF, RD, HM,LE, TM); critical revision of the manuscript (BM, AT, FT, EK, MZ); supervision (FG,HRE, HF); All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMahendraraj K, Lau CS, Lee I, Chamberlain RS. 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Retinal Microvasculature and Visual Acuity in Eyes With Branch Retinal Vein Occlusion: Imaging Analysis by Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 2017;58:2087\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDupas B, Minvielle W, Bonnin S, Couturier A, Erginay A, Massin P, et al. Association Between Vessel Density and Visual Acuity in Patients With Diabetic Retinopathy and Poorly Controlled Type 1 Diabetes. JAMA Ophthalmol. 2018;136:721\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakiar V, Gombos DS, Mourtada F, Rechner LA, Lawyer AA, Morrison WH, et al. Disease control and toxicity outcomes using ruthenium eye plaque brachytherapy in the treatment of uveal melanoma. Pract Radiat Oncol. 2014;4:e189-94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhasemi Falavarjani K, Iafe NA, Hubschman J-P, Tsui I, Sadda SR, Sarraf D. Optical Coherence Tomography Angiography Analysis of the Foveal Avascular Zone and Macular Vessel Density After Anti-VEGF Therapy in Eyes With Diabetic Macular Edema and Retinal Vein Occlusion. Invest Ophthalmol Vis Sci. 2017;58:30\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaghihi H, Riazi-Esfahani H, Khodabande A, Khalili Pour E, Mirshahi A, Ghassemi F, et al. Effect of panretinal photocoagulation on macular vasculature using optical coherence tomography angiography. Eur J Ophthalmol. 2020;:1120672120952642. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1120672120952642\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Deep capillary plexus, Foveal avascular zone (FAZ), Radiation maculopathy, Radiation retinopathy, Retina burnout, Ruthenium-106, Superficial capillary plexus","lastPublishedDoi":"10.21203/rs.3.rs-362423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-362423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBACKGROUND\u003c/strong\u003e: To assess the impact of brachytherapy on macular microvasculature utilizing optical coherence tomography angiography (OCTA) in treated choroidal melanoma.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMETHODS\u003c/strong\u003e: In this retrospective observational case series, we reviewed the recorded data of the patients with choroidal melanoma treated with rheuthenium-106 (\u003csup\u003e106\u003c/sup\u003eRu) plaque radiotherapy with follow-up period of more than 6 months. Automatically measured OCTA retinal parameters were analyzed after image processing. The non-irradiated fellow eye is considered as the control.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eRESULTS:\u003c/strong\u003e Thirty-one eyes of 31 patients with the mean age of 51.1 years were recruited. Six eyes had no radiation maculopathy (RM). From 25 eyes with RM, nine eyes (36%) revealed a burnout macular microvasculature with imperceptible vascular details. Foveal and optic disc radiation dose had the highest value to predict the burnout pattern (ROC, AUC: 0.763, 0.727). Superficial and deep foveal avascular zone (FAZ) were larger in irradiated eyes in comparison to healthy eyes (1629 µm\u003csup\u003e2\u003c/sup\u003e vs. 428 µm\u003csup\u003e2\u003c/sup\u003e, P =0.005; 1837 µm\u003csup\u003e2\u003c/sup\u003e vs 268 µm\u003csup\u003e2\u003c/sup\u003e, P =0.021; respectively). Foveal and parafoveal vascular area density (VAD) and vascular skeleton density (VSD) in both superficial and deep capillary plexus (SCP and DCP) were decreased in all irradiated eyes in comparison with control eyes (P\u0026lt; 0.001).\u0026nbsp;Compared with fellow healthy eyes, irradiated eyes without RM had significantly lower VAD and VSD at foveal and parafoveal DCP (all P\u0026lt;0.02). However, these differences at SCP were not statistically significant. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCONCLUSION\u003c/strong\u003e: The OCTA is a valuable tool for evaluating RM. Initial subclinical microvascular insult after \u003csup\u003e106\u003c/sup\u003eRu brachytherapy is more likely to occur in DCP. The deep FAZ area was identified as a more critical biomarker of BCVA than superficial FAZ in these patients.\u003c/p\u003e","manuscriptTitle":"Evaluation of Radiation Maculopathy after Treatment of Choroidal Melanoma with Ruthenium-106 using Optical Coherence Tomography Angiography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-04-13 17:52:19","doi":"10.21203/rs.3.rs-362423/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-09-20T08:45:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-09-14T23:58:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37aea22d-d054-4c8c-a08e-71925a9458e9","date":"2021-09-07T18:03:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-05-10T02:14:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6e22b84f-bdd3-456e-8f2c-49308e823700","date":"2021-05-06T11:01:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"fd546763-08b7-42dc-b425-57333a5e4186","date":"2021-05-06T00:25:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-04-29T14:19:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-04-15T12:33:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-04-12T10:25:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-04-12T10:17:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ophthalmology","date":"2021-03-25T19:44:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c2fd1a3-6ea3-45d1-8171-3abaa0131589","owner":[],"postedDate":"April 13th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":3609244,"name":"Ophthalmology"}],"tags":[],"updatedAt":"2021-10-06T08:44:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-04-13 17:52:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-362423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-362423","identity":"rs-362423","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}