Changes in Retinal Vasculature and Thickness After Femtosecond Laser-assisted Cataract Surgery and Conventional Cataract Surgery Using Optical Coherence Tomography Angiography

Purpose To assess the changes in retinal vasculature and thickness after femtosecond laser-assisted cataract surgery (FLACS) using optical coherence tomography angiography (OCTA).Methods Fifty-six eyes of 56 patients with age-related cataract were enrolled in this study. Patients were divided into FLACS or conventional phacoemulsification surgery (CPS) due to the choice of operation. Vessel density (VD) and thickness at the macular area and optic nerve head (ONH) were checked by OCTA at baseline and at 1 day, 1 month and 3 months after cataract surgery.Results In the FLACS group: The radial peripapillary capillary (RPC) density displayed a significant reduction during the follow-up (P < 0.05), even when the retinal nerve fiber layer (RNFL) thickness was not significantly changed. There was a significant negative correlation between the changes in RPC density and femtosecond laser-assisted pre-treatment time (FLAPT) at 1 day and 1 month after cataract surgery respectively (both P < 0.05). At 3 months postoperatively, the macular thickness had a significant increase in all regions (all P < 0.05). In the CPS group, the retinal VD and thickness did not show statistically significant changes in all regions during the follow-up (all P > 0.05). However, the best corrected visual acuity (BCVA) was significantly improved in both groups postoperatively (both P < 0.001).Conclusions OCTA provided a promising analysis of retinal vascular alterations, demonstrating the reduction of RPC density and the increase of macular thickness after FLACS. However, these changes had no effect on the improvement of visual acuity after cataract surgery.

DAVS-NET: Dense Aggregation Vessel Segmentation Network for retinal vasculature detection in fundus images

In this era, deep learning-based medical image analysis has become a reliable source in assisting medical practitioners for various retinal disease diagnosis like hypertension, diabetic retinopathy (DR), arteriosclerosis glaucoma, and macular edema etc. Among these retinal diseases, DR can lead to vision detachment in diabetic patients which cause swelling of these retinal blood vessels or even can create new vessels. This creation or the new vessels and swelling can be analyzed as biomarker for screening and analysis of DR. Deep learning-based semantic segmentation of these vessels can be an effective tool to detect changes in retinal vasculature for diagnostic purposes. This segmentation task becomes challenging because of the low-quality retinal images with different image acquisition conditions, and intensity variations. Existing retinal blood vessels segmentation methods require a large number of trainable parameters for training of their networks. This paper introduces a novel Dense Aggregation Vessel Segmentation Network (DAVS-Net), which can achieve high segmentation performance with only a few trainable parameters. For faster convergence, this network uses an encoder-decoder framework in which edge information is transferred from the first layers of the encoder to the last layer of the decoder. Performance of the proposed network is evaluated on publicly available retinal blood vessels datasets of DRIVE, CHASE_DB1, and STARE. Proposed method achieved state-of-the-art segmentation accuracy using a few number of trainable parameters.

Diabetic and Hypertensive Retinopathy Screening in Fundus Images Using Artificially Intelligent Shallow Architectures

Retinal blood vessels are considered valuable biomarkers for the detection of diabetic retinopathy, hypertensive retinopathy, and other retinal disorders. Ophthalmologists analyze retinal vasculature by manual segmentation, which is a tedious task. Numerous studies have focused on automatic retinal vasculature segmentation using different methods for ophthalmic disease analysis. However, most of these methods are computationally expensive and lack robustness. This paper proposes two new shallow deep learning architectures: dual-stream fusion network (DSF-Net) and dual-stream aggregation network (DSA-Net) to accurately detect retinal vasculature. The proposed method uses semantic segmentation in raw color fundus images for the screening of diabetic and hypertensive retinopathies. The proposed method’s performance is assessed using three publicly available fundus image datasets: Digital Retinal Images for Vessel Extraction (DRIVE), Structured Analysis of Retina (STARE), and Children Heart Health Study in England Database (CHASE-DB1). The experimental results revealed that the proposed method provided superior segmentation performance with accuracy (Acc), sensitivity (SE), specificity (SP), and area under the curve (AUC) of 96.93%, 82.68%, 98.30%, and 98.42% for DRIVE, 97.25%, 82.22%, 98.38%, and 98.15% for CHASE-DB1, and 97.00%, 86.07%, 98.00%, and 98.65% for STARE datasets, respectively. The experimental results also show that the proposed DSA-Net provides higher SE compared to the existing approaches. It means that the proposed method detected the minor vessels and provided the least false negatives, which is extremely important for diagnosis. The proposed method provides an automatic and accurate segmentation mask that can be used to highlight the vessel pixels. This detected vasculature can be utilized to compute the ratio between the vessel and the non-vessel pixels and distinguish between diabetic and hypertensive retinopathies, and morphology can be analyzed for related retinal disorders.

Quantitative analysis of retinal vasculature in normal eyes using ultra-widefield fluorescein angiography

AIM: To quantify the area and density of retinal vascularity by ultra-widefield fluorescein angiography (UWFA). METHODS: In a retrospective study, UWFA images were obtained using an ultra-widefield imaging device in 42 normal eyes of 42 patients. Central and peripheral steered images were used to define the edge of retinal vasculature by a certified grader. The length from the center of the optic disc to the edge of retinal vascularity (RVL) in each quadrant and the total retinal vascular perfusion area (RVPA) were determined by the grader using OptosAdvance software. The density of retinal vascularity (RVD) was quantified in different zones of central-steered images using Image J software. RESULTS: Among 42 healthy eyes, the values for mean RVL in each quadrant were 19.007±0.781 mm (superior), 18.467±0.869 mm (inferior), 17.738±0.622 mm (nasal) and 24.241±1.336 mm (temporal). The mean RVPA was 1140.117±73.825 mm2. The mean RVD of the total retina was 4.850%±0.638%. RVD varied significantly between different retina zones (P<0.001), and significant differences existed in the RVD values for total retinal area in patients over 50 years old compared to those under 50 years old (P=0.033). No gender difference was found. CONCLUSION: The UWFA device can be a promising tool for analyzing the overall retinal vasculature and may provide a better understanding of retinal vascular morphology in normal eyes. Aging may be related to lower RVD.

Retinal Microvasculature Changes in Patients With Coronary Total Occlusion on Optical Coherence Tomography Angiography

Background: Retinal microvasculature has been associated with coronary artery disease (CAD), but the exact contributory role in coronary total occlusion (CTO) is unclear. We aimed to investigate whether retinal vasculature is associated with CTO and could provide incremental value in the assessment of CTO.Methods: A total of 218 CAD patients including 102 CTO and 116 non-CTO were enrolled. Retinal vasculature was measured by optical coherence tomography angiography (OCTA) for all patients. Receiver operating characteristic (ROC) curve was used to assess the performance of retinal vasculature in differentiating CTO from non-CTO patients.Results: In non-CTO CAD patients, vessel density (VD) of mean superficial capillary plexus (SCP) and parafovea SCP were 49.85 and 52.56%, respectively; in CTO patients, VD of mean SCP and parafovea SCP were 47.77, and 49.58%, respectively. After multiple adjustment, VD in the SCP was significantly lower in CTO patients compared to non-CTO patients. VD of superior hemi in the parafovea SCP combined with the clinical variates showed the best ability to predict CTO from CAD with an area under the curve (AUC) of 0.812 (specificity of 89.0% and sensitivity of 65.9%).Conclusions: In CTO patients, retinal VD was significantly decreased, and microvascular damage might specifically target to arterioles than capillaries. Retinal vasculature could thus be a surrogate for detecting the microvascular damage and assist in the assessment of CTO patients. OCTA examination could be suggested to monitor the process of coronary arteries lesions.

Characterization of the Canine Retinal Vasculature With Optical Coherence Tomography Angiography: Comparisons With Histology and Fluorescein Angiography

Purpose: To present a methodology for quantification of the canine retinal vasculature imaged by optical coherence tomography angiography (OCTA) and validate this approach by comparison with fluorescein angiography (FA) and confocal imaging of retinal wholemounts labelled by immunohistochemistry (IHC).Methods: Six normal adult dogs underwent retinal OCTA imaging in both eyes. The images extracted from the different microvascular plexuses at eight retinal locations spanning the central and mid-peripheral fundus were analyzed using the AngioTool software. FA was performed in one eye and was compared to the OCTA images. Six eyes from three dogs were processed by IHC to examine the retinal vasculature.Results: A total of four retinal plexuses were identified by OCTA in the canine retina, and their density and topographical pattern varied with eccentricity. OCTA offered improved resolution over FA with the advantage of allowing imaging of the individual plexuses. Detection by OCTA of small vessels within the deep capillary plexus was possible and approached the level of resolution achieved with ex vivo imaging of the retinal vasculature by confocal microscopy/IHC. The plexuses herein described are analogous to human retinal vasculature.Conclusion: OCTA can be used to image and quantify non-invasively the vascular retinal networks of the canine retina. We provide normative data in eight different retinal locations that can be imaged non-invasively with this technology. This could support analysis of retinal vascular changes associated with disease and following therapeutic intervention.

Assessment of the retinal vasculature in healthy Chinese preschool children aged 4–6 years old using optical coherence tomography angiography

Purpose To establish normal parameters of macular and optic disc vasculature by optical coherence tomography angiography (OCTA) in healthy preschool children aged 4–6 years old in China. OCTA reflects retinal metabolism and development in children at these ages and could be used clinically and in future studies to aid diagnosis and prediction of retinal abnormalities and developmental stagnation. Methods In this cross-sectional study, we measured foveal, parafoveal, and perifoveal vessel density in the superficial capillary plexus (SCP); the deep capillary plexus (DCP), the foveal avascular zone (FAZ), and the radial capillary peripapillary (RPC) in the optic disc using investigational spectral-domain OCTA. The magnification effect of the FAZ area and microvasculature measurements was corrected by Littman and the modified Bennett formula. Results A total of 242 eyes (116 males and 126 females, 5.31 ± 0.73 years) were recruited for the analysis. The mean macular vessel density was 48.10 ± 2.92% and 48.74 ± 6.51% in the SCP and the DCP, respectively. The RPC vessel density was 47.17 ± 2.52%, 47.99 ± 4.48%, and 48.41 ± 3.07% in the whole image, inside disc, and peripapillary, respectively; and the mean FAZ area was 0.28 ± 0.11 mm2. A significant difference between male and female participants was found in the retinal vasculature (DCP, SCP, and RPC). None of these parameters were significantly different in age (P > 0.05), except that DCP slightly increased with aging. The right and left eyes had good consistency in the parameters of the macula and optic disc. Conclusions Our study establishes the macular and optic disc OCTA reference values in 4- to 6-year-old healthy preschool children. They may be used in longitudinal OCTA studies and clinical applications.