New findings on choroidal features in healthy people by ultra-widefield swept-source optical coherence tomography angiography.

To evaluate the distribution of choroidal thickness (CT) and its trend with age in healthy people using 120° ultra-wide field swept-source optical coherence tomography angiography (UWF SS-OCTA). In this cross-sectional observational study, healthy volunteers underwent single imaging of the fundus with UWF SS-OCTA at a field of view (FOV) of 120° (24 mm × 20 mm) centered on the macula. The characteristics of CT distribution in different regions and its changes with age were analyzed. A total of 128 volunteers with a mean age of 34.9 ± 20.1 years and 210 eyes were enrolled in the study. The thickest mean choroid thickness (MCT) was located at the macular region and supratemporal region, followed by the nasal side of the optic disc, and thinnest below the optic disc. The maximum MCT was: 213.40 ± 36.65 µm for the group aged 20-29, and the minimum MCT was: 162.11 ± 31.96 µm for the group aged ≥ 60. After the age of 50, MCT was significantly and negatively correlated decreased with age (r = - 0.358, p = 0.002), and the MCT in the macular region decreased more remarkably compared to other regions. The 120° UWF SS-OCTA can observe the distribution of choroidal thickness in the range of 24 mm × 20 mm and its variation with age. It was revealed that MCT decreased more rapidly in the macular region relative to other regions after 50 years old.

Different scan areas affect the detection rates of diabetic retinopathy lesions by high-speed ultra-widefield swept-source optical coherence tomography angiography.

Introduction: The study aimed to determine the effect of the scanning area used for high-speed ultra-widefield swept-source optical coherence tomography angiography (SS-OCTA) on the detection rate of diabetic retinopathy (DR) lesions. Methods: This prospective, observational study involved diabetic patients between October 2021 and April 2022. The participants underwent a comprehensive ophthalmic examination and high-speed ultra-widefield SS-OCTA using a 24 mm × 20 mm scanning protocol. A central area denoted as "12 mm × 12 mm-central" was extracted from the 24 mm × 20 mm image, and the remaining area was denoted as "12 mm~24mm-annulus." The rates of detection of DR lesions using the two scanning areas were recorded and compared. Results: In total, 172 eyes (41 eyes with diabetes mellitus without DR, 40 eyes with mild to moderate non-proliferative diabetic retinopathy (NPDR), 51 eyes with severe NPDR, and 40 eyes with proliferative diabetic retinopathy (PDR) from 101 participants were included. The detection rates of microaneurysms (MAs), intraretinal microvascular abnormalities (IRMAs), and neovascularization (NV) for the 12 mm × 12 mm central and 24 mm × 20 mm images were comparable (p > 0.05). The detection rate of NPAs for the 24 mm × 20 mm image was 64.5%, which was significantly higher than that for the 12 mm × 12 mm central image (52.3%, p < 0.05). The average ischemic index (ISI) was 15.26% for the 12 mm~24mm-annulus, which was significantly higher than that for the 12 mm × 12 mm central image (5.62%). Six eyes had NV and 10 eyes had IRMAs that only existed in the 12 mm~24mm-annulus area. Conclusions: The newly developed high-speed ultra-widefield SS-OCTA can capture a 24 mm × 20 mm retinal vascular image during a single scan, which improves the accuracy of detecting the degree of retinal ischemia and detection rate of NV and IRMAs.

Ultra-widefield color fundus photography combined with high-speed ultra-widefield swept-source optical coherence tomography angiography for non-invasive detection of lesions in diabetic retinopathy.

Purpose: To compare the detection rate of diabetic retinopathy (DR) lesions and the agreement of DR severity grading using the ultra-widefield color fundus photography (UWF CFP) combined with high-speed ultra-widefield swept-source optical coherence tomography angiography (UWF SS-OCTA) or fluorescein angiography (FFA). Methods: This prospective, observational study recruited diabetic patients who had already taken the FFA examination from November 2021 to June 2022. These patients had either no DR or any stage of DR. All participants were imaged with a 200° UWF CFP and UWF SS-OCTA using a 24 × 20 mm scan model. Images were independently evaluated for the presence or absence of DR lesions including microaneurysms (MAs), intraretinal hemorrhage (IRH), non-perfusion areas (NPAs), intraretinal microvascular abnormalities (IRMAs), venous beading (VB), neovascularization elsewhere (NVE), neovascularization of the optic disc (NVD), and vitreous or preretinal hemorrhage (VH/PRH). Agreement of DR severity grading based on UWF CFP plus UWF SS-OCTA and UWF CFP plus FFA was compared. All statistical analyses were performed using SPSS V.26.0. Results: One hundred and fifty-three eyes of 86 participants were enrolled in the study. The combination of UWF CFP with UWF SS-OCTA showed a similar detection rate compared with UWF CFP plus FFA for all the characteristic DR lesions (p>0.05), except NPAs (p = 0.039). Good agreement was shown for the identification of VB (κ = 0.635), and very good agreement for rest of the DR lesions between the two combination methods (κ-value ranged from 0.858 to 0.974). When comparing the grading of DR severity, very good agreement was achieved between UWF CFP plus UWF SS-OCTA and UWF CFP plusr FFA (κ = 0.869). Conclusion: UWF CFP plus UWF SS-OCTA had a very good agreement in detecting DR lesions and determining the severity of DR compared with UWF CFP plus FFA. This modality has the potential to be used as a fast, reliable, and non-invasive method for DR screening and monitoring in the future.

Overexpression of Twist1 in vascular endothelial cells promotes pathological retinal angiogenesis in mice.

Retinal angiogenesis is a critical process for normal retinal function. However, uncontrolled angiogenesis can lead to pathological neovascularization (NV), which is closely related to most irreversible blindness-causing retinal diseases. Understanding the molecular basis behind pathological NV is important for the treatment of related diseases. Twist-related protein 1 (TWIST1) is a well-known transcription factor and principal inducer of epithelial-mesenchymal transition (EMT) in many human cancers. Our previous study showed that Twist1 expression is elevated in pathological retinal NV. To date, however, the role of TWIST1 in retinal pathological angiogenesis remains to be elucidated. To study the role of TWIST1 in pathological retinal NV and identify specific molecular targets for antagonizing pathological NV, we generated an inducible vascular endothelial cell (EC)-specific Twist1 transgenic mouse model ( Tg-Twist1 iEC+ ). Whole-mount retinas from Tg-Twist1 iEC+ mice showed retarded vascular progression and increased vascular density in the front end of the growing retinal vasculature, as well as aneurysm-like pathological retinal NV. Furthermore, overexpression of Twist1 in the ECs promoted cell proliferation but disturbed cell polarity, thus leading to uncontrolled retinal angiogenesis. TWIST1 promoted pathological NV by activating the Wnt/ß-catenin signaling pathway and inducing the expression of NV formation-related genes, thereby acting as a 'valve' in the regulation of pathological angiogenesis. This study identified the critical role of TWIST1 in retinal pathological NV, thus providing a potential therapeutic target for pathological NV.

EVALUATION OF ARTIFICIAL INTELLIGENCE-BASED QUANTITATIVE ANALYSIS TO IDENTIFY CLINICALLY SIGNIFICANT SEVERE RETINOPATHY OF PREMATURITY.

PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP). METHODS: Fundus photographs were collected, and standard panel diagnosis was generated for each examination by combining three independent image-based gradings. All images were analyzed using a deep learning algorithm, and a quantitative assessment of retinal vascular abnormality (DeepROP score) was assigned on a 1 to 100 scale. The area under the receiver operating curve and distribution pattern of all diagnostic parameters and categories of ROP were analyzed. The correlation between the DeepROP score and expert rank ordering according to overall ROP severity of 50 examinations was calculated. RESULTS: A total of 9,882 individual examinations with 54,626 images from 2,801 infants were analyzed. Fifty-six examinations (0.6%) demonstrated Type 1 ROP and 54 examinations (0.5%) demonstrated Type 2 ROP. The DeepROP score had an area under the receiver operating curve of 0.981 for detecting Type 1 ROP and 0.986 for Type 2 ROP. There was a statistically significant correlation between the expert rank ordering of overall disease severity and the DeepROP score (correlation coefficient 0.758, P < 0.001). When hypothetical referral cutoff score of 35 was selected, all cases of severe ROP (Type 1 and Type 2 ROP) was captured and 8,562 eyes (87.6%) with no or mild ROP were excluded. CONCLUSION: The DeepROP score determined by deep learning algorithm was an objective and quantitative indicator for the severity of ROP, and it had potential in automated detecting clinically significant severe ROP.