(1) Background: The fundus examination is one of the best and popular methods in the assessment of vascular status in the human body. Direct viewing of retinal vessels by ophthalmoscopy has been utilized in judging hypertensive change or arteriosclerosis. Recently, fundus imaging with the non-mydriatic scanning laser ophthalmoscope (SLO) has been widely used in ophthalmological clinics since it has multimodal functions for optical coherence tomography or angiography with contrast agent dye. The purpose of this study was to examine the utility in detecting arteriosclerosis of retinal vessels in SLO images; (2) Methods: Both color and blue standard field SLO images of eyes with diabetic retinopathy (DR) were examined retrospectively. Retinal arteriosclerosis in color SLO images was graded according to the Scheie classification. Additionally, characteristics of retinal arterioles in blue SLO images were identified and examined for their relevance to arteriosclerosis grades, stages of DR or general complications; (3) Results: Relative to color fundus images, blue SLO images showed distinct hyper-reflective retinal arterioles against a monotone background. Irregularities of retinal arterioles identified in blue SLO images were frequently observed in the eyes of patients with severe arteriosclerosis (Grade 3: 79.0% and Grade 4: 81.8%). Furthermore, the findings on arterioles were more frequently associated with the eyes of DR patients with renal dysfunction (p < 0.05); (4) Conclusions: While color SLO images are equally as useful in assessing retinal arteriosclerosis as photography or ophthalmoscopy, the corresponding blue SLO images show arteriosclerotic lesions with high contrast in a monotone background. Retinal arteriosclerosis in eyes of advanced grades or advanced DR frequently show irregularities of retinal arterioles in the blue images. The findings of low, uneven, or discontinuous attenuation were easier to find in blue than in color SLO images. Consequently, blue SLO images can show pathological micro-sclerosis in retinal arterioles and are potentially one of the safe and practical methods for the vascular assessment of diabetic patients.

This review critically assesses the applicability of retinal periphery imaging technology, scrutinizing its practical limitations and potential advancements within ophthalmology. It underscores the significant costs and the need to evaluate the clinical utility of optical coherence tomography (OCT) and OCT angiography devices. It emphasizes how clinicians should consider their practice-specific use-cases while investing in devices with capabilities like ultra-widefield OCT, autofluorescence imaging, and angiography. The paper also highlights the challenges associated with image acquisition, such as artifact management and patient cooperation for extended fixation periods. This review outlines the utility of these modalities in various retinal pathologies, as well as their contribution to telemedicine and personalized care, facilitated by artificial intelligence for improved image processing, quantification, and interpretation. These techniques potentially offer a more comprehensive understanding of peripheral retinal conditions and associated pathologies, thus influencing clinical decision-making, particularly in remote regions with limited specialist access.

In recent years, optoretinography has become an important functional imaging method for the retina, as light-evoked changes in the photoreceptors have been demonstrated for a large number of different OCT systems. Full-field swept-source optical coherence tomography (FF-SS-OCT) is particularly phase-stable, and it is currently the only technique sensitive enough to detect the smaller functional changes in the inner plexiform layer (IPL). However, the resolution of state-of-the art FF-SS-OCT systems is not high enough to distinguish individual photoreceptors. This makes it difficult to separate rods from cones. In this work, we circumvent this problem by separating the functional changes in rods and cones by their different temporal dynamics to the same light stimulus. For this purpose, a mathematical model was developed that represents the measured signals as a superposition of two impulse responses. The developed model describes the measured data under different imaging conditions very well and is able to analyze the sensitivity and temporal dynamics of the two photoreceptor types separately.

UNASSIGNED: To compare radial peripapillary capillary (RPC) vascular plexus parameters and peripapillary retinal nerve fiber layer (pRNFL) thickness between Early-Treated Adults with Phenylketonuria (ETPKU) and controls.
UNASSIGNED: This observational study was a monocentric, case control study including 36 eyes of 36 participants. Among these, 18 were early-treated PKU (ETPKU) and 18 were controls. A SD-OCTA (XR Avanti AngioVue OCTA; Optovue Inc., Fremont, CA) was employed to assess the OCT and OCTA parameters of all the participants. The main outcome measures were the RPC vessels density (VD) %, and the pRNFL thickness.
UNASSIGNED: The average pRNFL thickness was significantly reduced in ETPKU (110.78 ± 12.48 μm) compared to controls (113.22 ± 13.95 μm), p = 0.046. The mean VD% of the small vessels of the RPC plexus was 52.31 ± 2.2 in ETPKU and 50.71 ± 3.2 in controls (p = 0.049), while the VD% of all the radial peripapillary capillary plexus (RPCP) was 58.5 ± 2.2 in ETPKU and 55.08 ± 3.4 in controls (p < 0.001). By contrast, there were no differences in age, sex, and IOP between the two groups.
UNASSIGNED: Through structural OCT and OCTA, we observed thinning of the nerve fibers accompanied by an increase in perfusion of the RPC plexus. Thus, our conclusions suggest that OCTA may serve as a noninvasive method to identify novel retinal biomarkers in ETPKU.

This commentary article delves into the transformative role of optical coherence tomography angiography (OCTA) in diagnosing and managing a wide array of eye conditions, including diabetic retinopathy, age-related macular degeneration, retinal vein occlusions, and white dot syndromes. Developed in 2005, OCTA has emerged as a non-invasive, high-resolution imaging technique that offers advantages over traditional fluorescein angiography (FA), providing quicker and safer monitoring of ocular conditions with similar diagnostic accuracy. In diabetic retinopathy, OCTA has been instrumental in early identification of retinal changes, offering quantifiable metrics including perfused capillary density (PCD) for assessing vascular alterations. For age-related macular degeneration (AMD), OCTA has deepened our understanding of non-exudative neovascular AMD, allowing for more effective monitoring and potential earlier initiation of treatment. In cases of retinal vein occlusions, OCTA can reveal specific microvascular features and allow for depth-resolved measurements of the foveal avascular zone, providing significant prognostic implications. OCTA has also been invaluable in studying rare white dot syndromes, enabling nuanced differentiation between conditions that often present similarly. Emerging research also suggests that OCTA can have potential utility in neurodegenerative diseases like Alzheimer\'s, where retinal vascular patterns could offer diagnostic insights. While OCTA is revolutionizing ophthalmic care, further clinical trials and standardization are needed for its broader adoption into clinical practice.

Schizophrenia (SZ) and bipolar disorder (BD) are characterized by major symptomatic, cognitive, and neuroanatomical changes. Recent studies have used optical coherence tomography (OCT) to investigate retinal changes in SZ and BD, but their unique and shared changes require further evaluation. Articles were identified using PubMed and Google Scholar. 39 studies met the inclusion criteria. Diagnostic groups were proband (SZ/BD combined), SZ, BD, and healthy control (HC) eyes. Meta-analyses utilized fixed and random effects models when appropriate, and publication bias was corrected using trim-and-fill analysis (\"meta\" package in R). Results are reported as standardized mean differences with 95% CIs. Data from 3145 patient eyes (1956 SZ, 1189 BD) and 3135 HC eyes were included. Studies identified thinning of the peripapillary retinal nerve fiber layer (pRNFL, overall and in 2 subregions), m-Retina (overall and all subregions), mGCL-IPL, mIPL, and mRPE in SZ patients. BD showed thinning of the pRNFL (overall and in each subregion), pGCC, and macular Retina (in 5 subregions), but no changes in thickness or volume for the total retina. Neither SZ nor BD patients demonstrated significant changes in the fovea, mRNFL, mGCL, mGCC, mINL, mOPL, mONL, or choroid thicknesses. Moderating effects of age, illness duration, and smoking on retinal structures were identified. This meta-analysis builds upon previous literature in this field by incorporating recent OCT studies and examining both peripapillary and macular retinal regions with respect to psychotic disorders. Overall, this meta-analysis demonstrated both peripapillary and macular structural retinal abnormalities in people with SZ or BD compared with HCs.

BACKGROUND: Diabetic retinopathy (DR) and diabetic macular edema (DME) are major causes of visual impairment that challenge global vision health. New strategies are needed to tackle these growing global health problems, and the integration of artificial intelligence (AI) into ophthalmology has the potential to revolutionize DR and DME management to meet these challenges.
METHODS: This review discusses the latest AI-driven methodologies in the context of DR and DME in terms of disease identification, patient-specific disease profiling, and short-term and long-term management. This includes current screening and diagnostic systems and their real-world implementation, lesion detection and analysis, disease progression prediction, and treatment response models. It also highlights the technical advancements that have been made in these areas. Despite these advancements, there are obstacles to the widespread adoption of these technologies in clinical settings, including regulatory and privacy concerns, the need for extensive validation, and integration with existing healthcare systems. We also explore the disparity between the potential of AI models and their actual effectiveness in real-world applications.
CONCLUSIONS: AI has the potential to revolutionize the management of DR and DME, offering more efficient and precise tools for healthcare professionals. However, overcoming challenges in deployment, regulatory compliance, and patient privacy is essential for these technologies to realize their full potential. Future research should aim to bridge the gap between technological innovation and clinical application, ensuring AI tools integrate seamlessly into healthcare workflows to enhance patient outcomes.

High resolution retinal imaging paired with intravitreal injection of a viral vector coding for the calcium indicator GCaMP has enabled visualization of activity dependent calcium changes in retinal ganglion cells (RGCs) at single cell resolution in the living eye. The inner limiting membrane (ILM) is a barrier for viral vectors, restricting transduction to a ring of RGCs serving the fovea in both humans and non-human primates (NHP). We evaluate peeling the ILM prior to intravitreal injection as a strategy to expand calcium imaging beyond the fovea in the NHP eye in vivo. Five Macaca fascicularis eyes (age 3-10y; n=3 individuals; 2M, 1F) underwent vitrectomy and 5 to 6-disc diameter ILM peel centered on the fovea prior to intravitreal delivery of 7m8:SNCG:GCaMP8s. Calcium responses from RGCs were recorded using a fluorescence adaptive optics scanning laser ophthalmoscope. In all eyes GCaMP was expressed throughout the peeled area, representing a mean 8-fold enlargement in area of expression relative to a control eye. Calcium recordings were obtained up to 11 degrees from the foveal center. RGC responses were comparable to the fellow control eye and showed no significant decrease over the 6 months post ILM peel, suggesting that RGC function was not compromised by the surgical procedure. In addition, we demonstrate that activity can be recorded directly from the retinal nerve fiber layer. This approach will be valuable for a range of applications in visual neuroscience including pre-clinical evaluation of retinal function, detecting vision loss, and assessing the impact of therapeutic interventions.

UNASSIGNED: To report the clinical course and the retinal imaging features of a case of cytology-proven primary vitreoretinal lymphoma (PVRL) presenting with a transient bacillary layer detachment (BALAD) during the disease course.
UNASSIGNED: Observational case report.
UNASSIGNED: A 50 year-old woman was referred to us with a 2-month history of vitritis in both eyes, poorly responding to oral prednisolone. After discontinuation of oral prednisolone, worsening of vitritis and the appearance of multiple creamy-like subretinal infiltrates in the mid-peripheral retina of both eyes, along with the exclusion of common causes of intermediate/posterior uveitis, made us consider PVRL. Aqueous humor sampling detected MYD88 L265P mutation, and subsequent diagnostic pars plana vitrectomy in the left eye yielded a positive cytology for large B cell lymphoma consistent with PVRL. During the disease course, optical coherence tomography of the macula showed a BALAD in the right eye, which resolved during follow-up.
UNASSIGNED: Our case indicates that BALAD is a possible rare manifestation of PVRL, and this should be considered in the differential diagnosis process in order to avoid diagnostic delays.

UNASSIGNED: Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death globally, and early detection of high-risk individuals is essential for initiating timely interventions. The authors aimed to develop and validate a deep learning (DL) model to predict an individual\'s elevated 10-year ASCVD risk score based on retinal images and limited demographic data.
UNASSIGNED: The study used 89,894 retinal fundus images from 44,176 UK Biobank participants (96% non-Hispanic White, 5% diabetic) to train and test the DL model. The DL model was developed using retinal images plus age, race/ethnicity, and sex at birth to predict an individual\'s 10-year ASCVD risk score using the pooled cohort equation (PCE) as the ground truth. This model was then tested on the US EyePACS 10K dataset (5.8% non-Hispanic White, 99.9% diabetic), composed of 18,900 images from 8969 diabetic individuals. Elevated ASCVD risk was defined as a PCE score of ≥7.5%.
UNASSIGNED: In the UK Biobank internal validation dataset, the DL model achieved an area under the receiver operating characteristic curve of 0.89, sensitivity 84%, and specificity 90%, for detecting individuals with elevated ASCVD risk scores. In the EyePACS 10K and with the addition of a regression-derived diabetes modifier, it achieved sensitivity 94%, specificity 72%, mean error -0.2%, and mean absolute error 3.1%.
UNASSIGNED: This study demonstrates that DL models using retinal images can provide an additional approach to estimating ASCVD risk, as well as the value of applying DL models to different external datasets and opportunities about ASCVD risk assessment in patients living with diabetes.