Age-related macular degeneration (AMD) is a leading cause of blindness and visual impairment worldwide. Structural en face optical coherence tomography (OCT) is an innovative imaging technology that has recently attracted interest because of its potential for assessing AMD features. We conducted a comprehensive review of its application in AMD. In neovascular AMD, structural en face OCT can detect exudative activity, monitor the neovascularization area, study the choroid in polypoidal choroidal vasculopathy, and visualize neovascular membranes in pigment epithelial detachments. Moreover, in nonneovascular AMD, this study provides details on geographic atrophy and drusen, the identification of intraretinal retinal pigment epithelium migration, and the detection of different patterns of outer retinal tubulations. Our study revealed that structural en face OCT can provide relevant information on patients with AMD.

Pachychoroid spectrum disorders (PSDs) represent a group of chorioretinal disorders characterized by abnormal choroidal thickening and various pathological changes in the choroid, retinal pigment epithelium, and retina. This review provides a comprehensive analysis of current multimodal imaging techniques in the diagnosis and management of PSDs. We examine the role of various imaging modalities including optical coherence tomography (OCT), OCT angiography (OCTA), en face OCT, fluorescein angiography (FA), indocyanine green angiography (ICGA), infrared imaging (IR), and fundus autofluorescence (FAF) in evaluating PSDs. Each imaging modality provides unique insights: OCT reveals characteristic choroidal thickening and structural changes; OCTA demonstrates alterations in choroidal flow and neovascularization; en face OCT allows detailed visualization of choroidal vasculature and intervortex anastomoses; FA shows patterns of leakage; ICGA reveals choroidal hyperpermeability and pachyvessels; IR imaging assists in RPE evaluation; and FAF highlights RPE dysfunction. The integration of these imaging techniques has enhanced our understanding of the pathophysiology of PSDs and improved our ability to diagnose, monitor, and treat these conditions. This review particularly emphasizes how OCTA has advanced our knowledge of choroidal circulation and neovascularization in PSDs. We also discuss future directions in imaging technology and their potential impact on personalized therapeutic approaches, including optimized photodynamic therapy based on imaging biomarkers. The synergistic use of multimodal imaging represents a cornerstone in the management of PSDs, enabling more precise diagnosis and tailored treatment strategies.

Despite current screening models, enhanced imaging modalities, and treatment regimens, diabetic retinopathy (DR) remains one of the leading causes of vision loss in working age adults. DR can result in irreversible structural and functional retinal damage, leading to visual impairment and reduced quality of life. Given potentially irreversible photoreceptor damage, diagnosis and treatment at the earliest stages will provide the best opportunity to avoid visual disturbances or retinopathy progression. We will review herein the current structural imaging methods used for DR assessment and their capability of detecting DR in the first stages of disease. Imaging tools, such as fundus photography, optical coherence tomography, fundus fluorescein angiography, optical coherence tomography angiography and adaptive optics-assisted imaging will be reviewed. Finally, we describe the future of DR screening programmes and the introduction of artificial intelligence as an innovative approach to detecting subtle changes in the diabetic retina. CLINICAL TRIAL REGISTRATION NUMBER: N/A.

This review article systematically assesses existing literature on studies employing retinal optical coherence tomography angiography (OCTA) metrics as surrogate biomarkers for cardiovascular disease. A comprehensive, literature review of published peer-reviewed research was conducted within PubMed utilizing the following medical subject headings (MeSH) terms: "optical coherence tomography", "cardiovascular diseases", "retina", and "retinal vessels". A total of 840 articles were reviewed and selectively filtered with ultimately 50 articles being included. This review article elucidates key findings, identifies limitations, and pinpoints gaps within these investigations. Additionally, this article delineates constraints related to OCTA technology and image processing that presently hinder the widespread adoption of this promising technology.

To observe the dynamic changes of microvascular injury and repair in the penumbra of traumatic brain injury (TBI) rats with effective cerebral perfusion microvascular imaging using optical coherence tomography angiography (OCTA).

Transparent closed cranial windows were placed in craniotomy rats after TBI caused by weight drop. All the rats in TBI group and control group underwent head MRI examination on the first postoperative day, and the changes of cerebral cortical microvessel density were measured by OCTA through cranial windows on d0, d2, d4, d6, and d8. On the second day after the operation, the same number of rats in the two groups were selected to complete the immunohistochemical staining of brain tissue with pimonidazole, an indicator of hypoxia.

MRI T2W1 and immunohistochemical staining demonstrated that edema and hypoxia in the traumatic brain tissue extended deeply throughout the entire cortex. OCTA showed that the cortical surface veins of the rats in both groups were significantly dilated and tortuous after operation, and recovered to the postoperative day level on d8. The effective perfusion microvessel density of the rats in both groups gradually recovered after a temporary decrease, and the TBI group decreased from 39.38%±4.48% on d0 to 27.84%±6.01% on d2, which was significantly lower than that on d0, d6, and d8 (P < 0.05). The highest value was 61.71%±7.69% on d8, which was significantly higher than that on d0, d2, and d4 (P < 0.05). The control group decreased from 44.59%±7.78% on d0 to 36.69%±5.49% on d2, which was significantly lower than that on d0, d6, and d8 (P < 0.05). The highest value was 51.92%±5.96% on d8, which was significantly higher than that on d2, and d4 (P < 0.05). Comparing the two groups, the effective perfusion microvessel density in the TBI group was significantly lower than that in the control group on d2 (P=0.021), and significantly higher than that in the control group on d8 (P=0.030).

OCTA can be used as a method of imaging and measurement of effective perfusion microvessels in the injured cerebral cortex of TBI rats. After TBI, the effective perfusion microvessel density in the wound penumbra gradually recovered after decreasing, and increased significantly on d8.

Background: Anti-Vascular Endothelial Growth Factor (VEGF) therapy is an effective therapy for improving and stabilizing the vision of patients with neovascular age-related macular degeneration (nAMD). However, the treatment requirements, particularly the number of intraocular injections, can vary significantly among patients. This study aimed to analyze the vascular characteristics of macular neovascularizations (MNVs) to identify potential biomarkers that could predict the required injection frequency throughout the disease course. Methods: In all patients, the initial diagnosis of nAMD was confirmed using optic coherence tomography (OCT), fluorescein angiography, and OCT angiography (OCTA). MNVs detected using OCTA were subjected to quantitative vascular analysis of their area, total vascular length (sumL), fractal dimension (FD), and flow density. These results were then correlated with the number of intravitreal anti-VEGF treatments administered during the first 3 years of treatment. Additionally, the relationship between the parameters and visual acuity progression was analyzed. Results: A total of 68 treatment-naïve eyes were included in the study, comprising 31 eyes with type 1 MNV, 19 eyes with type 2 MNV, and 18 eyes with type 3 MNV. The average MNV area at baseline was 1.11 mm2 ± 1.18 mm2, the mean total vascular length was 12.95 mm ± 14.24 mm, the mean fractal dimension was 1.26 ± 0.14, and the mean flow density was 41.19 ± 5.87. On average, patients in our cohort received 19.8 ± 8.5 intravitreal injections (IVIs). A significant correlation was found between the number of administered IVIs in the first 3 treatment years and the MNV area (p < 0.005), sumL (p < 0.005), and FD (p < 0.05), while no correlation was found with flow density. Additionally, there was no significant association between MNV type and treatment requirements, nor between MNV vascular architecture and visual acuity progression. Conclusions: The results suggest that the specific vascular structure of untreated MNV may serve as a predictor of long-term treatment demand. With the emergence of new drug classes and advancements in imaging techniques, these parameters could offer valuable insights for forecasting treatment requirements.

This study aimed to show the changes in retinal vascular densities and thicknesses in the peripapillary and macular regions in the acute period in patients with acute pancreatitis (AP).

This prospective cross-sectional study included 57 eyes of 30 patients with AP and 58 eyes of 30 healthy people. Optical coherence tomography angiography (OCTA) was taken within 24-72 h of AP patients' hospitalization. OCTA was used to evaluate the retinal microvascular structure and retinal thickness.

Peripapillary retinal nerve fiber layer (pp-RNFL) and perifoveolar ganglion cell complex (pef-GCC) thickness in patients with AP were significantly higher than in the healthy control group (p = 0.020 and p = 0.039, respectively). While whole image vessel density (wiVD) and perifoveal vessel density (pefVD) were significantly lower in the deep capillary plexus (DCP), choriocapillaris flow area (CCFA) in the macula were significantly lower in each of the 1 mm and 3 mm radius areas in patients with AP (p = 0.014, p = 0.011; p = 0.011, and p = 0.035 respectively). In the univariable and multivariable linear regression analysis, it was observed that serum lipase and procalcitonin levels affected the thickness of pp-RNFL and pef-GCC (for pp-RNFL, β= 0.001, p = 0.002, β=24.992, p < 0.001, and for pef-GCC, β= 0.001 p = 0.014, β=17.107 p < 0.001 respectively).

There are significant microvascular and structural changes in the optic nerve and macula in patients with AP. The relationship between these changes and serum lipase and procalcitonin levels was shown. Clinicians should consider ocular involvement in AP patients with high serum lipase and procalcitonin levels.

Optical coherence tomography angiography (OCTA) holds promise in enhancing the care of various retinal vascular diseases, including neovascular age-related macular degeneration (nAMD). Given nAMD's vascular nature and the distinct vasculature of macular neovascularization (MNV), detailed analysis is expected to gain significance. Research in artificial intelligence (AI) indicates that en-face OCTA views may offer superior predictive capabilities than spectral domain optical coherence tomography (SD-OCT) images, highlighting the necessity to identify key vascular parameters. Analyzing vasculature could facilitate distinguishing MNV subtypes and refining diagnosis. Future studies correlating OCTA parameters with clinical data might prompt a revised classification system. However, the combined utilization of qualitative and quantitative OCTA biomarkers to enhance the accuracy of diagnosing disease activity remains underdeveloped. Discrepancies persist regarding the optimal biomarker for indicating an active lesion, warranting comprehensive prospective studies for validation. AI holds potential in extracting valuable insights from the vast datasets within OCTA, enabling researchers and clinicians to fully exploit its OCTA imaging capabilities. Nevertheless, challenges pertaining to data quantity and quality pose significant obstacles to AI advancement in this field. As OCTA gains traction in clinical practice and data volume increases, AI-driven analysis is expected to further augment diagnostic capabilities.

Background and Objectives: This study explores the relationship between retinal structure, vascular densities (VD), and the progression of myopia, aiming to identify novel biomarkers for assessing myopia severity. Materials and Methods: A total of 260 eyes were divided into four groups: Emmetropia (EM) (n = 74), Low Myopia (LM) (n = 68), Moderate Myopia (MM) (n = 64), and High Myopia (HM) (n = 54). VD and retinal thickness (RT) in the macular and peripheral quadrants were measured using optical coherence tomography-angiography (OCTA). SVD and DVD were analyzed across the paranasal, peritemporal, perisuperior, and peri-inferior quadrants. Results: Significant differences in superficial vessel density (SVD) were found in the paranasal (EM vs. MM, p = 0.017; EM vs. HM, p = 0.001), peritemporal (EM vs. MM, p = 0.006; EM vs. HM, p = 0.001; LM vs. HM, p = 0.004; MM vs. HM, p = 0.032), perisuperior (EM vs. MM, p = 0.005; EM vs. HM, p = 0.001; LM vs. HM, p = 0.027), and perifoveal quadrants (EM vs. MM, p = 0.003; EM vs. HM, p = 0.008; LM vs. HM, p = 0.004; MM vs. HM, p = 0.012). Deep vessel density (DVD) showed significant differences in the paranasal (p = 0.012-0.022), peritemporal (p = 0.002-0.026), perisuperior (p = 0.003-0.034), perifoveal (p = 0.002-0.017), and peri-inferior (p = 0.002-0.022) quadrants. Retinal thickness was significantly reduced in HM eyes, with the most pronounced reduction in the peritemporal quadrant (mean difference: 16.7 ± 3.2 µm; p < 0.001). Conclusions: Structural and vascular changes in the retina become more pronounced as myopia progresses from moderate to high. The strong correlation between DVD, RT, and myopia severity highlights their potential as reliable biomarkers for monitoring myopia progression through OCTA imaging. These findings provide new insights into the vascular and structural changes underlying myopia and their diagnostic significance.

Alzheimer's disease (AD) is a major healthcare challenge, with existing diagnostics being costly/infeasible. This study explores retinal biomarkers from optical coherence tomography (OCT) and OCT angiography (OCTA) as a cost-effective and non-invasive solution to differentiate AD, mild cognitive impairment (MCI), and healthy controls (HCs).

Participants from the CALLIOPE Research Program were classified as "Dem" (AD and early AD), "MCI," and "HCs" using neuropsychological tests and clinical diagnosis by a neurologist. OCT/OCTA examinations were conducted using the RTVue XR 100 Avanti SD-OCT system (VISIONIX), with retinal parameters extracted. Statistical analysis included normality and homogeneity of variance (HOV) tests to select ANOVA methods. Post-hoc analyses utilized Mann-Whitney U, Dunnett, or Tukey-HSD tests based on parameters' normality and HOV. Correlations with age were assessed via Pearson or Spearman tests. A generalized linear model (GLM) using Tweedie regression modeled the relationship between OCT/OCTA parameters and MMSE scores, correcting for age. Another ordinal logistic GLM (OL-GLM) modeled OCT/OCTA parameters against classes, adjusting for multiple confounders.

We analyzed 357 participants: 44 Dem, 139 MCI, and 174 HCs. Significant microvascular density (VD) reductions around the fovea were linked with MCI and Dem compared to HCs. Age-related analysis associated thickness parameters with HCs' old age. Our OL-GLM demonstrated significant thickness/volume reductions in Inner_Retina and Full_Retina layers. Foveal avascular zone (FAZ) area and perimeter were initially not correlated with cognitive decline; however, OL-GLM significantly associated FAZ perimeter enlargement with Dem and MCI groups. Significant average and inferior peripapillary RNFL thinning were linked to Dem and MCI groups.

This is the first study to examine VD changes in G grid sections among Dem, MCI, and HCs. We found a significant association between various VD parameters and cognitive decline. Most macular thickness/volume changes did not correlate with cognitive decline initially; however, our OL-GLM succeeded, highlighting the importance of the confounders' corrections. Our analysis excluded individual retinal layer parameters due to limitations; however, the literature suggests their value. Our study confirmed existing biomarkers' efficacy and uncovered novel retinal parameters for cognitive decline, requiring further validation.

To investigate the retinochoroidal and optic nerve head (ONH) microstructural and microvascular age-related changes in healthy subjects by examining the ganglion cell-inner plexiform layer thickness (GC-IPLT), vessel density (VD), and their ratio.

In this cross-sectional study, 203 subjects (20-69 years old) were divided into five age groups: 20-29 (G1), 30-39 (G2), 40-49 (G3), 50-59 (G4), and 60-69 (G5) (G5). Following a thorough ophthalmological examination, enhanced depth imaging optical coherence tomography (EDI-OCT) scanning was performed along with OCT angiography (OCTA) in a 6 × 6 mm2 scanning area.

After adjusting for axial length the GC-IPLT varied significantly among groups, with thickness peaking in G3 (39.63 ± 1.14 µm) and then decreasing to the lowest in G5 (34.15 ± 5.93 µm) (p = 0.008). The whole, foveal, parafoveal, and perifoveal superficial and deep capillary plexus (SCP and DCP) VDs all varied significantly among groups, peaking in G2 and falling to their lowest in G5 (p < 0.05). No significant differences existed among groups regarding the GC-IPLT/whole SCP VD (p = 0.163) or GC-IPLT/whole DCP VD (p = 0.258) ratios. The foveal VDs in a 300-μm wide region surrounding the foveal avascular zone (FAZ) (FD-300) varied significantly among groups, peaking in G1 (57.06 ± 0.58) and dropping to its lowest in G5 (53.54 ± 0.59) (p < 0.05). The choriocapillaris flow differed significantly among groups, peaking in G1 (20.39 ± 0.15 mm2) and dropping to its lowest in G5 (19.24 ± 0.16 mm2) (p < 0.001).

The retinochoroidal microstructure and microvasculature ratios display an inverted U-shaped pattern with age, which could be linked to a considerably decreased GC-IPLT versus capillary plexus VDs with age, notably in subjects in their sixties.

Smoking increases oxidative stress, affecting the vascular endothelium by decreasing the antioxidant vitamin C and disrupting regular nitric oxide activity. It reduces blood flow in the retina and choroid due to increased vascular resistance and compromised choroidal blood flow regulation compared to nonsmokers. This systematic review and meta-analysis aimed to elucidate the impact of cigarette smoking on retinal thickness and the choroidal vascularity index (CVI).

A comprehensive literature search was performed across multiple databases, including Web of Science, Medline, PubMed, and Embase, adhering to the PRISMA and MOOSE guidelines. Observational studies were selected to explore the relationships between smoking and ocular parameters such as CVI, full-retinal, and choroidal thickness. Two independent reviewers conducted the data extraction and quality assessment using a modified Newcastle-Ottawa scale. Statistical analysis was performed using a random-effects model.

Four out of the 743 identified articles, involving 702 eyes, met the inclusion criteria. The analysis revealed a significant reduction in the CVI among smokers (SMD: -0.61, 95% CI: -0.78 to -0.43, p < 0.00001), indicating compromised choroidal vascularity. In contrast, the impact of smoking on subfoveal choroidal thickness (SFCT) was not statistically significant (mean difference: 3.88 μm, 95% CI: -7.34 to 15.10, p = 0.50), with high heterogeneity (I² = 79%). Additionally, the full-retinal thickness (FRT) did not show a significant difference between smokers and nonsmokers.

Cigarette smoking negatively affects choroidal vascularity, as indicated by a significant reduction in CVI. However, its impact on FRT and SFCT remains unclear and requires further research. These findings highlight the importance of smoking cessation for eye health and suggest that CVI is a valuable noninvasive biomarker for monitoring vascular changes in smokers.

PROSPERO registration number: CRD42024627478.

Retinal models play a pivotal role in translational drug development, bridging preclinical research and therapeutic applications for both ocular and systemic diseases. This review highlights the retina as an ideal organ for studying advanced therapies, thanks to its immune privilege, vascular and neuronal networks, accessibility, and advanced imaging capabilities. Preclinical retinal disease models offer unparalleled insights into inflammation, angiogenesis, fibrosis, and hypoxia, utilizing clinically translatable bioimaging tools like fundoscopy, optical coherence tomography, confocal scanning laser ophthalmoscopy, fluorescein angiography, optokinetic tracking, and electroretinography. These models have driven innovations in anti-inflammatory, anti-angiogenic, and neuroprotective strategies, with broader implications for systemic diseases such as rheumatoid arthritis, Alzheimer's, and fibrosis-related conditions. By emphasizing the integration of the 3Rs principles and novel imaging modalities, this review highlights how retinal research not only enhances therapeutic precision but also minimizes ethical concerns, paving the way for more predictive and human-relevant approaches in drug development.

Diabetic retinopathy (DR) is a leading cause of vision loss globally, with early detection and intervention critical to preventing severe outcomes. This narrative review examines the role of retinal biomarkers-molecular and imaging-in improving early diagnosis, tracking disease progression, and advancing personalized treatment for DR. Key biomarkers, such as inflammatory and metabolic markers, imaging findings from optical coherence tomography and fluorescence angiography and genetic markers, provide insights into disease mechanisms, help predict progression, and monitor responses to treatments, like anti-VEGF and corticosteroids. While challenges in standardization and clinical integration remain, these biomarkers hold promise for a precision medicine approach that could transform DR management through early, individualized care.

Macular telangiectasia (MacTel) is a rare retinal condition that can cause vision loss, and anti-vascular endothelial growth factor (anti-VEGF) agents have emerged as a potential treatment. This study aimed to evaluate the clinical outcomes of anti-VEGF therapy in patients with MacTel.

A systematic literature search on Ovid MEDLINE, Embase, and Cochrane Library was performed from inception to June 2024 for comparative studies on anti-VEGF agents in MacTel. The primary outcome was the change in best-corrected visual acuity (BCVA). Secondary outcomes were central macular thickness (CMT), central choroidal thickness (CCT), and fluorescein angiography (FA) leakage.

Ten studies on 377 eyes of 239 patients followed up over 23.4 ± 8.3 months were included. Mean (SD) BCVA changed from 0.42 (0.39) to 0.35 (0.18) over 23.4 (8.3) months of follow-up in non-proliferative MacTel. Mean BCVA changed from 0.66 (0.43) to 0.52 (0.34) at final follow-up in eyes with choroidal neovascularization (CNV). Five studies reported improved visual acuity, one showed improved FA leakage without visual acuity benefit, and four found no functional benefit. In non-proliferative MacTel, four studies showed no functional improvement, two reported significant functional and morphological improvements, and one suggested potential benefits in improving BCVA. In proliferative MacTel, two studies demonstrated improvement in both anatomical and functional outcomes, while one indicated that anti-VEGF treatment might produce improved results. In non-proliferative MacTel, mean CMT changed from 201 (32) µm to 199 (29) µm. CMT in patients with CNV decreased from an initial value of 328.23 (161.16) µm to 267.44 (118.56) µm at the final follow-up. CCT in proliferative MacTel eyes decreased from 272.37 (52.65) µm and 247.40 (48.80) µm on anti-VEGF therapy. Overall, FA leakage outcomes were improved on ranibizumab therapy. No study documented any significant adverse effects with treatment.

Anti-VEGF agents may be associated with favorable anatomical and functional outcomes, particularly in proliferative MacTel; however, future large-scale clinical trials are warranted.

Retinal imaging, used for assessing stroke-related retinal changes, is a non-invasive and cost-effective method that can be enhanced by machine learning and deep learning algorithms, showing promise in early disease detection, severity grading, and prognostic evaluation in stroke patients. This review explores the role of artificial intelligence (AI) in stroke patient care, focusing on retinal imaging integration into clinical workflows. Retinal imaging has revealed several microvascular changes, including a decrease in the central retinal artery diameter and an increase in the central retinal vein diameter, both of which are associated with lacunar stroke and intracranial hemorrhage. Additionally, microvascular changes, such as arteriovenous nicking, increased vessel tortuosity, enhanced arteriolar light reflex, decreased retinal fractals, and thinning of retinal nerve fiber layer are also reported to be associated with higher stroke risk. AI models, such as Xception and EfficientNet, have demonstrated accuracy comparable to traditional stroke risk scoring systems in predicting stroke risk. For stroke diagnosis, models like Inception, ResNet, and VGG, alongside machine learning classifiers, have shown high efficacy in distinguishing stroke patients from healthy individuals using retinal imaging. Moreover, a random forest model effectively distinguished between ischemic and hemorrhagic stroke subtypes based on retinal features, showing superior predictive performance compared to traditional clinical characteristics. Additionally, a support vector machine model has achieved high classification accuracy in assessing pial collateral status. Despite this advancements, challenges such as the lack of standardized protocols for imaging modalities, hesitance in trusting AI-generated predictions, insufficient integration of retinal imaging data with electronic health records, the need for validation across diverse populations, and ethical and regulatory concerns persist. Future efforts must focus on validating AI models across diverse populations, ensuring algorithm transparency, and addressing ethical and regulatory issues to enable broader implementation. Overcoming these barriers will be essential for translating this technology into personalized stroke care and improving patient outcomes.

This study aimed to compare the outcomes of Optical Coherence Tomography-Angiography (OCT-A) with the clinical assessments conducted by an experienced ophthalmologist, as well as to analyze the alterations in the conjunctiva of individuals utilizing spherical scleral contact lenses. OCT-A imaging was conducted on 13 patients (mean age: 34.1 years, 10 males) in a prospective study at two time points: at least 8 h post-lens removal and 1-hour post-lens application. The scleral region in the quadrants (superior, inferior, temporal, and nasal) was designated as the region of interest (ROI), located 3 mm from the limbus. This ROI was further divided into two bands: Band 1 (1.5 mm width under the lens) and Band 2 (1.5 mm width outside the lens). The vascular density ratios in the inferior quadrant were significantly reduced after the lens fitting: ROI (0.362 ± 0.074 post-lens vs. 0.452 ± 0.099 pre-lens, adjusted P-value = 0.027) and Band 1 (0.353 ± 0.075 post-lens vs. 0.462 ± 0.095 pre-lens, adjusted P-value = 0.008). In the superior (P-value = 0.026), inferior (P-value < 0.001), and temporal (P-value < 0.001) quadrants, the degree of conjunctival impingement, as scored by an experienced ophthalmologist using slit photographs, was significantly correlated with OCT-A findings. In conclusion, OCT-A identifies microvascular changes undetectable by slit-lamp examination, providing quantitative insights into vascular alterations from scleral lens use and complementing clinical evaluations.

We aimed to compare fluorescein angiography (FA)-based classification of macular neovascularisation (MNV) with optical coherence tomography (OCT)-based classification, as well as examine differences in retinal fluid among OCT MNV types. We analyzed baseline FA and OCT images from 704 eyes of neovascular AMD patients across two multicenter trials, with grading conducted at the Vienna Reading Center. Using a validated AI tool (RetInSight Fluid Monitor Version 2), we localized and quantified retinal fluid. Kappa coefficients for agreement between FA and OCT MNV types were 0.58 [0.52; 0.64] (type 1/occult), 0.46 [0.38; 0.55] (type 2/classic), and 0.53 [0.44; 0.62] (type 3/RAP). Significant differences in the volumes of intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED) were noted among MNV types (p < 0.0001). Pairwise comparisons revealed significant differences in IRF volumes across all lesion types except type 2 versus mixed type, in SRF between type 3 and other types, and in PED between type 2 and other lesions. In conclusion, there was moderate agreement between FA and OCT classifications, and notable differences in fluid distribution among OCT types, suggesting potential for AI-guided MNV recognition in clinical settings.

Machine learning has transformed ophthalmology, particularly in predictive and discriminatory models for vitreoretinal pathologies. However, generative modeling, especially generative adversarial networks (GANs), remains underexplored. GANs consist of two neural networks-the generator and discriminator-that work in opposition to synthesize highly realistic images. These synthetic images can enhance diagnostic accuracy, expand the capabilities of imaging technologies, and predict treatment responses. GANs have already been applied to fundus imaging, optical coherence tomography (OCT), and fluorescein autofluorescence (FA). Despite their potential, GANs face challenges in reliability and accuracy. This review explores GAN architecture, their advantages over other deep learning models, and their clinical applications in retinal disease diagnosis and treatment monitoring. Furthermore, we discuss the limitations of current GAN models and propose novel applications combining GANs with OCT, OCT-angiography, fluorescein angiography, fundus imaging, electroretinograms, visual fields, and indocyanine green angiography.

To evaluate the effects of short-acting cycloplegic agents, tropicamide and compound tropicamide, on ocular biological parameters and choroid thickness.

In this study, seventy pediatric subjects aged 6 to 13 years were randomly assigned to two groups: the tropicamide group and compound tropicamide group. Ocular biological parameters and choroidal thickness (CT) and subfoveal choroid thickness (SFCT) were measured in both groups and were retested 40 min after drug administration. The tropicamide eye drops were administered into the conjunctival sac every 5 min with 1 drop, for a total of 4 doses. Compound tropicamide was administered in the same way as tropicamide. Ocular biological parameters included refraction (spherical equivalent, SE), intraocular pressure (IOP), axial length (AL), anterior chamber depth (ACD), lens thickness (LT), central corneal thickness (CCT), and white to white (WTW). The CT is the regional inferior choroidal thickness of nine sectors centered on the macular fovea and automatically generated using an ETDRS grid. And the SFCT is the choroidal thickness at the subfoveal point of the macular region.

After application of tropicamide and compound tropicamide to induce the ciliary muscle paralysis, SE, AL, and LT decreased, while ACD, CCT, and WTW increased compared to baseline(all P values < 0.05). There was no significant change in IOP before and after cycloplegia (p > 0.05). The CT in the nasal quadrant before and after ciliary paralysis was significantly thinner than other areas, the CT in the temporal quadrant was significantly thicker than others, and the CT in the inner quadrant was higher than the CT in the outer quadrant. In the tropicamide group: CT was significantly increased in the remaining quadrants except the inner inferior(I) and outer superior(S) quadrants (p < 0.05), and SFCT was also significantly increased (p = 0.005). In the compound tropicamide group: there is a significant increase in CT outer superior(S) quadrant CT (p = 0.043). Increase in the mean values of CT and SFCT in the remaining quadrants was also observed, but the difference was not statistically significant (p > 0.05). Additionally, AL and SFCT were negatively correlated.

Some ocular biological parameters were altered after application of short-acting cycloplegic agent tropicamide and compound tropicamide to paralyze the ciliary muscle. Compared with compound tropicamide, tropicamide eye drops can reduce axial length while increasing choroid thickness.

Optical coherence tomography angiography (OCTA) is an emerging, non-invasive technique increasingly utilized for retinal vasculature imaging. Analysis of OCTA images can effectively diagnose retinal diseases, unfortunately, complex vascular structures within OCTA images possess significant challenges for automated segmentation. A novel, fully convolutional dense connected residual network is proposed to effectively segment the vascular regions within OCTA images. Firstly, a dual-branch structure Recurrent Residual Convolutional Neural Network (RRCNN) block is constructed utilizing RecurrentBlock and convolutional operations. Subsequently, the ResConvNeXt V2 Block is built as the backbone structure of the network. The output from the ResConvNeXt V2 Block is then fed into the side branch and the next ResConvNeXt V2 Block. Within the side branch, the Group Receptive Field Block (GRFB) processes the results from the previous and current layers. Ultimately, the side branch results are added to the backbone network outputs to produce the final segmentation. The model achieves superior performance. Experiments were conducted on the ROSSA and OCTA-500 datasets, yielding Dice scores of 91.88%, 91.72%, and 89.18% for the respective datasets, and accuracies of 98.31%, 99.02%, and 98.02%.

Optical coherence tomography angiography (OCTA) offers unparalleled capabilities for non-invasive detection of vessels. However, the lack of accurate models for light-tissue interaction in OCTA jeopardizes the development of the techniques to further extract quantitative information from the measurements. In this manuscript, we propose a Monte Carlo (MC)-based simulation method to precisely describe the signal formation of OCTA based on the fundamental theory of light-tissue interactions. A dynamic particle-fixed model is developed to depict the spatial-temporal behaviors of the tissue phantom: the particles are initialized and fixed in specific locations with wavelength-dependent scattering cross-sections and are allowed to travel over time. We then employ a full-spectrum MC engine to faithfully simulate the formation of OCT and OCTA images. A simulation on a vessel-mimicking phantom demonstrated that speckle characteristics in OCT as well as decorrelation maps in OCTA could be successfully reproduced. We further illustrate the usefulness of our method on the quantitative OCTA by extending it to simulate the gradual saturation of decorrelation in OCTA-based velocimetry. We believe our method will serve as a valuable tool for studying OCTA theory and inspire better solutions and metrics for non-invasive flow velocity measurement.

Optical coherence tomography angiography (OCTA) plays a crucial role in quantifying and analyzing retinal vascular diseases. However, the limited field of view (FOV) inherent in most commercial OCTA imaging systems poses a significant challenge for clinicians, restricting the possibility to analyze larger retinal regions of high resolution. Automatic stitching of OCTA scans in adjacent regions may provide a promising solution to extend the region of interest. However, commonly-used stitching algorithms face difficulties in achieving effective alignment due to noise, artifacts and dense vasculature present in OCTA images. To address these challenges, we propose a novel retinal OCTA image stitching network, named -Net, which integrates multi-scale representation learning and dynamic location guidance. In the first stage, an image registration network with a progressive multi-resolution feature fusion is proposed to derive deep semantic information effectively. Additionally, we introduce a dynamic guidance strategy to locate the foveal avascular zone (FAZ) and constrain registration errors in overlapping vascular regions. In the second stage, an image fusion network based on multiple mask constraints and adjacent image aggregation (AIA) strategies is developed to further eliminate the artifacts in the overlapping areas of stitched images, thereby achieving precise vessel alignment. To validate the effectiveness of our method, we conduct a series of experiments on two delicately constructed datasets, i.e., OPTOVUE-OCTA and SVision-OCTA. Experimental results demonstrate that our method outperforms other image stitching methods and effectively generates high-quality wide-field OCTA images, achieving a structural similarity index (SSIM) score of 0.8264 and 0.8014 on the two datasets, respectively.

The purpose of this study was to quantitatively evaluate the branching patterns and vascular fragmentation features in preclinical and early diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA).

OCTA metrics, including branch node number (BNN), branch node density (BND), end point number (EPN), end point density (EPD), fragmented vessel segment count (FVSC), and fragmented vascular length ratio (FVLR), were measured in foveal and parafoveal regions within superficial and deep vascular plexus (SVP and DVP) in the retina.

Compared to healthy control (HCs), both BNN and BND exhibited a significant decrease in individuals with mild DR across both retinal layers, and also in diabetes mellitus without DR (no DR) within DVP. EPD showed a significant increase in mild DR cases compared to HCs, except for the foveal region in SVP; however, EPN did not demonstrate a significant difference among the three groups. Increases in both FVSC and FVLR were significant across all areas and in both layers of the retina. Notably, these metrics showed more pronounced differentiation in the DVP than the SVP.

Foveal BND and BNN in DVP reveal vascular alterations indicative of preclinical DR. Indicators such as EPD, FVSC, and FVLR in DVP correlate with early DR changes and are useful for its early detection. These initial findings demonstrate the potential and benefits of these quantitative OCTA indices for delineating DR-associated alterations in the retinal microvasculature, indicating their potential clinical utility for improved DR screening.

To highlight the influence of preocular and ocular vascular circulatory dynamics on the vascular density (VD) of retinal capillary plexuses (RCPs) and choriocapillaris (CC) in patients with and without cardiovascular risk (CVR) factors.

A retrospective observational study in patients with and without CVR factors (type 1 and 2 diabetes, arterial hypertension, and hypercholesterolemia). Fluorescein (FA) and indocyanine (ICGA) angiography circulatory times were arterial time (FAAT), start (FAstartLF) and end (FAendLF) of laminar flow, and arterial time (ICGAAT), respectively. OCT angiography VDs were superficial (VDSCP) and deep (VDDCP) RCPs and CC (VDCC) VDs. Correlation and regression analysis were performed after adjusting for confounding factors.

177 eyes of 177 patients (mean age: 65.2 ± 15.9 years, n = 92 with and 85 without CVR) were included. VDSCP and VDDCP were significantly inversely correlated with FAAT, FAstartLF and FAendLF likewise VDCC with ICGAAT. Correlations were stronger in patients without CVR than with CVR. CVR, FAAT, FAstartLF and FAendLF were more strongly correlated with VDDCP than VDSCP. FAAT, FAstartLF and FAendLF significantly impacted VDSCP and VDDCP, likewise ICGAAT impacted VDDCP. VDDCP was most strongly impacted by FAAT and FAstartLF.

Ocular and pre-ocular circulatory dynamics significantly impacted RCPs and CC VDs, especially deep RCP.

The prevalence of diabetic retinopathy (DR) among the geriatric population poses significant challenges for early detection and management. Optical Coherence Tomography Angiography (OCTA) combined with Deep Learning presents a promising avenue for improving diagnostic accuracy in this vulnerable demographic. In this method, we propose an innovative approach utilizing OCTA images and Deep Learning algorithms to detect diabetic retinopathy in geriatric patients. We have collected 262 OCTA scans of 179 elderly individuals, both with and without diabetes, and trained a deep-learning model to classify retinopathy severity levels. Convolutional Neural Network (CNN) models: Inception V3, ResNet-50, ResNet50V2, VggNet-16, VggNet-19, DenseNet121, DenseNet201, EfficientNetV2B0, are trained to extract features and further classify them. Here we demonstrate:•The potential of OCTA and Deep Learning in enhancing geriatric eye care at the very initial stage.•The importance of technological advancements in addressing age-related ocular diseases and providing reliable assistance to clinicians for DR classification.•The efficacy of this approach in accurately identifying diabetic retinopathy stages, thereby facilitating timely interventions, and preventing vision loss in the elderly population.

Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder that affects the frontal and temporal lobes of the brain, leading to cognitive decline and personality changes. The objective of this cross-sectional study was to characterize angioarchitectural changes in the retina and choroid of individuals with FTD compared to cognitively normal controls using optical coherence tomography (OCT) and OCT angiography (OCTA).

Cross-sectional comparison of patients with FTD and controls with normal cognition. All participants underwent Mini-Mental State Examination (MMSE) at the time of imaging. Outcome measures included OCT parameters: retinal nerve fiber layer (RNFL) thickness, ganglion cell layer-inner plexiform layer (GC-IPL) thickness, central subfield thickness (CST), subfoveal choroidal thickness (SFCT), choroidal vascularity index (CVI); and OCTA superficial capillary plexus parameters: foveal avascular zone (FAZ) area, 3x3mm and 6x6mm macular perfusion density (PD) and vessel density (VD), 4.5x4.5mm peripapillary capillary perfusion density (CPD) and capillary flux index (CFI). Generalized estimating equation analysis was used to account for the inclusion of 2 eyes from the same participant.

29 eyes of 19 patients with FTD and 85 eyes of 48 controls were analyzed. In FTD, 3x3mm macular PD (p = 0.02) and VD (p = 0.02) and CFI (p = 0.01) were reduced compared to controls. There was no difference in average 4.5x4.5mm CPD, RNFL thickness, GC-IPL thickness, CST, SFCT, CVI, FAZ, or 6x6mm VD or PD between FTD and controls (all p > 0.05); however, there was a trend toward lower macular 6x6mm PD and VD in patients with FTD.

Decline of peripapillary and macular OCT and OCTA parameters merit further investigation as potential biomarkers for FTD detection. Noninvasive retinal and choroidal imaging may hold promise for earlier detection, and future longitudinal studies will clarify their role in monitoring of FTD.

Optical coherence tomography angiography (OCTA) is an emerging technique to investigate retinal and choroidal microvascular alterations in patients with systemic sclerosis (SSc). This systematic review and meta-analysis aimed to evaluate the features of retinal and choroidal microvasculature using OCTA among SSc patients.

The methodology of the study was based on PRISMA guidelines. PubMed, Scopus, Web of Science, and Embase were searched systematically on November 25, 2023, for relevant studies utilizing OCTA as the main diagnostic tool to assess the retinal and choroidal microvasculature in SSc patients versus healthy controls. Random-effect or fixed model meta-analysis was used based on the heterogeneity of studies.

Eleven observational comparative studies, including 366 patients with SSc and 350 healthy controls, conducted between 2020 and 2023, were included in this review. Meta-analysis findings revealed a significant decrease in vessel densities in both the superficial and deep capillary plexuses among SSc patients compared to controls. However, there were no significant differences observed in the foveal avascular zone area and choriocapillaris flow area between SSc patients and controls. Moreover, central macular thickness (CMT) consistently exhibited a decrease in SSc patients, while retinal nerve fiber layer thickness showed no significant differences. Although radial peripapillary capillary vessel density, subfoveal choroidal thickness, and cup/disk ratio yielded mixed results, with some studies indicating significant changes in the SSc group, meta-analysis could not be performed due to variations in the OCTA machines used across the included studies.

This systematic review demonstrates retinal and choroidal microvascular abnormalities in SSc using OCTA. Longitudinal studies are needed to understand how these abnormalities evolve over time in patients with SSc and whether these abnormalities correlate with the clinical features of SSc.

Retinal vasculature is the only vascular system in the human body that can be observed in a non-invasive manner, with a phenotype associated with a wide range of ocular, cerebral, and cardiovascular diseases. OCT and OCT angiography (OCTA) provide powerful imaging methods to visualize the three-dimensional morphological and functional information of the retina. In this study, based on OCT and OCTA multimodal inputs, a multitask convolutional neural network model was built to realize 3D segmentation of retinal blood vessels and disease classification for different retinal diseases, overcoming the limitations of existing methods that can only perform 2D analysis of OCTA. Two hundred thirty sets of OCT and OCTA data from 109 patients, including 138,000 cross-sectional images in normal and diseased eyes (age-related macular degeneration, retinal vein occlusion, and central serous chorioretinopathy), were collected from four commercial OCT systems for model training, validation, and testing. Experimental results verified that the proposed method was able to achieve a DICE coefficient of 0.956 for 3D segmentation of blood vessels and an accuracy of 91.49% for disease classification, and further enabled us to evaluate the 3D reconstruction of retinal vessels, explore the interlayer connections of superficial and deep vasculatures, and reveal the 3D quantitative vessel characteristics in different retinal diseases.

Optical Coherence Tomography Angiography Ratio Analysis (OCTARA) is capable of visualizing inner and outer retinal vascular plexuses, choriocapillaris, and larger choroidal vasculature in vivo without contrast injection. The aim of this study was to assess the intrasession repeatability of automated vessel density measurements using Triton Swept-Source Optical Coherence Tomography Angiography (OCTA) innovative algorithm OCTARA in retinal and choroidal vasculature.

To study population between 65-90 years old with no eye diseases. For each subject measurements were performed four times. The intraclass correlation coefficient and the coefficient of variation were calculated to analyze repeatability of the OCTARA automatically generated vessel density measurements.

A total of 35 eyes were included in the study. The intraclass correlation coefficient of the global vessel density in the superficial capillary plexus and the deep capillary plexus were 0.963 and 0.975, respectively, and the coefficient of variation were 5.4% and 4.4%, respectively. The intraclass correlation coefficient of the rest of the global measurements was indicative of good reliability with the exception of the deep choroid layer with an intraclass correlation coefficient of 0.6 indicative of moderate reliability.

Our results proved excellent repeatability of automated vessel density measurements in the superficial and deep capillary plexus layers in our cohort using a OCTARA algorithm indicating that it may be a reliable diagnostic tool. It also showed good reliability in choriocapillary and mid choroid layer. These findings may be of value in assessing the significance of differences in capillary density measurements over time and across different settings.

Endothelial dysfunction and microvascular remodeling underly the development and progression of a host of cardiovascular disease (CVD). However, current methods to assess coronary epicardial microvascular function are invasive, time-intensive, and costly. Optical coherence tomography angiography (OCTA) is an established technology within ophthalmology that provides a quick, noninvasive assessment of vascular structures within the retina. As a growing body of evidence reveals strong associations between the retinal changes on OCTA and the development and progression of CVD, OCTA may indeed be a surrogate test for end-organ dysfunction. OCTA has potential to enhance diagnostic performance, refine cardiovascular risk assessment, strengthen prognostication, and ultimately, improve patient care. We explore the current literature on OCTA in cardiovascular diseases to summarize the clinical utility of retinal OCTA imaging and discuss next-generation cardiovascular applications.

To use artificial intelligence to identify imaging biomarkers for anatomic and functional progression of lamellar macular hole (LMH) and elaborate a deep learning (DL) model based on OCT and OCT angiography (OCTA) for prediction of visual acuity (VA) loss in untreated LMHs.

Multicentric retrospective observational study.

Patients aged >18 years diagnosed with idiopathic LMHs with availability of good quality OCT and OCTA acquisitions at baseline and a follow-up >2 years were recruited.

A DL model based on soft voting of 2 separate models (OCT and OCTA-based respectively) was trained for identification of cases with VA loss >5 ETDRS letters (attributable to LMH progression only) during a 2-year follow-up. Biomarkers of anatomic and functional progression of LMH were evaluated with regression analysis, feature learning (support vector machine [SVM] model), and visualization maps.

Ellipsoid zone (EZ) damage, volumetric tissue loss (TL), vitreopapillary adhesion (VPA), epiretinal proliferation, central macular thickness (CMT), parafoveal vessel density (VD) and vessel length density (VLD) of retinal capillary plexuses, choriocapillaris (CC), and flow deficit density (FDD).

Functionally progressing LMHs (VA-PROG group, 41/139 eyes [29.5%]) showed higher prevalence of EZ damage, higher volumetric TL, higher prevalence of VPA, lower superficial capillary plexus (SCP), VD and VLD, and higher CC FDD compared with functionally stable LMHs (VA-STABLE group, 98/139 eyes [70.5%]). The DL and SVM models showed 92.5% and 90.5% accuracy, respectively. The best-performing features in the SVM were EZ damage, TL, CC FDD, and parafoveal SCP VD. Epiretinal proliferation and lower CMT were risk factors for anatomic progression only.

Deep learning can accurately predict functional progression of untreated LMHs over 2 years. The use of AI might improve our understanding of the natural course of retinal diseases. The integrity of CC and SCP might play an important role in the progression of LMHs.

The authors have no proprietary or commercial interest in any materials discussed in this article.

Age-related macular degeneration (AMD) is a retinal disorder characterized by central retinal (macular) damage. Approximately 10% to 20% of non-exudative AMD cases progress to the exudative form, which may result in rapid deterioration of central vision. Individuals with exudative AMD (eAMD) need prompt consultation with retinal specialists to minimize the risk and extent of vision loss. Traditional methods of diagnosing ophthalmic disease rely on clinical evaluation and multiple imaging techniques, which can be resource-consuming. Tests leveraging artificial intelligence (AI) hold the promise of automatically identifying and categorizing pathological features, enabling the timely diagnosis and treatment of eAMD.

To determine the diagnostic accuracy of artificial intelligence (AI) as a triaging tool for exudative age-related macular degeneration (eAMD).

We searched CENTRAL, MEDLINE, Embase, three clinical trials registries, and Data Archiving and Networked Services (DANS) for gray literature. We did not restrict searches by language or publication date. The date of the last search was April 2024.

Included studies compared the test performance of algorithms with that of human readers to detect eAMD on retinal images collected from people with AMD who were evaluated at eye clinics in community or academic medical centers, and who were not receiving treatment for eAMD when the images were taken. We included algorithms that were either internally or externally validated or both.

Pairs of review authors independently extracted data and assessed study quality using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool with revised signaling questions. For studies that reported more than one set of performance results, we extracted only one set of diagnostic accuracy data per study based on the last development stage or the optimal algorithm as indicated by the study authors. For two-class algorithms, we collected data from the 2x2 table whenever feasible. For multi-class algorithms, we first consolidated data from all classes other than eAMD before constructing the corresponding 2x2 tables. Assuming a common positivity threshold applied by the included studies, we chose random-effects, bivariate logistic models to estimate summary sensitivity and specificity as the primary performance metrics.

We identified 36 eligible studies that reported 40 sets of algorithm performance data, encompassing over 16,000 participants and 62,000 images. We included 28 studies (78%) that reported 31 algorithms with performance data in the meta-analysis. The remaining nine studies (25%) reported eight algorithms that lacked usable performance data; we reported them in the qualitative synthesis. Study characteristics and risk of bias Most studies were conducted in Asia, followed by Europe, the USA, and collaborative efforts spanning multiple countries. Most studies identified study participants from the hospital setting, while others used retinal images from public repositories; a few studies did not specify image sources. Based on four of the 36 studies reporting demographic information, the age of the study participants ranged from 62 to 82 years. The included algorithms used various retinal image types as model input, such as optical coherence tomography (OCT) images (N = 15), fundus images (N = 6), and multi-modal imaging (N = 7). The predominant core method used was deep neural networks. All studies that reported externally validated algorithms were at high risk of bias mainly due to potential selection bias from either a two-gate design or the inappropriate exclusion of potentially eligible retinal images (or participants). Findings Only three of the 40 included algorithms were externally validated (7.5%, 3/40). The summary sensitivity and specificity were 0.94 (95% confidence interval (CI) 0.90 to 0.97) and 0.99 (95% CI 0.76 to 1.00), respectively, when compared to human graders (3 studies; 27,872 images; low-certainty evidence). The prevalence of images with eAMD ranged from 0.3% to 49%. Twenty-eight algorithms were reportedly either internally validated (20%, 8/40) or tested on a development set (50%, 20/40); the pooled sensitivity and specificity were 0.93 (95% CI 0.89 to 0.96) and 0.96 (95% CI 0.94 to 0.98), respectively, when compared to human graders (28 studies; 33,409 images; low-certainty evidence). We did not identify significant sources of heterogeneity among these 28 algorithms. Although algorithms using OCT images appeared more homogeneous and had the highest summary specificity (0.97, 95% CI 0.93 to 0.98), they were not superior to algorithms using fundus images alone (0.94, 95% CI 0.89 to 0.97) or multimodal imaging (0.96, 95% CI 0.88 to 0.99; P for meta-regression = 0.239). The median prevalence of images with eAMD was 30% (interquartile range [IQR] 22% to 39%). We did not include eight studies that described nine algorithms (one study reported two sets of algorithm results) to distinguish eAMD from normal images, images of other AMD, or other non-AMD retinal lesions in the meta-analysis. Five of these algorithms were generally based on smaller datasets (range 21 to 218 participants per study) yet with a higher prevalence of eAMD images (range 33% to 66%). Relative to human graders, the reported sensitivity in these studies ranged from 0.95 and 0.97, while the specificity ranged from 0.94 to 0.99. Similarly, using small datasets (range 46 to 106), an additional four algorithms for detecting eAMD from other retinal lesions showed high sensitivity (range 0.96 to 1.00) and specificity (range 0.77 to 1.00).

Low- to very low-certainty evidence suggests that an algorithm-based test may correctly identify most individuals with eAMD without increasing unnecessary referrals (false positives) in either the primary or the specialty care settings. There were significant concerns for applying the review findings due to variations in the eAMD prevalence in the included studies. In addition, among the included algorithm-based tests, diagnostic accuracy estimates were at risk of bias due to study participants not reflecting real-world characteristics, inadequate model validation, and the likelihood of selective results reporting. Limited quality and quantity of externally validated algorithms highlighted the need for high-certainty evidence. This evidence will require a standardized definition for eAMD on different imaging modalities and external validation of the algorithm to assess generalizability.

We propose a new simple and cost-effective optical imaging technique, full-field amplitude speckle decorrelation angiography (FASDA), capable of visualizing skin microvasculature with high resolution, and sensitive to small, superficial vessels with slow blood flow and larger, deeper vessels with faster blood flow. FASDA makes use of a laser source with limited temporal coherence, can be implemented with cameras with conventional frame rates, and does not require raster scanning. The proposed imaging technique is based on the simultaneous evaluation of two metrics: the blood flow index, a contrast-based metric used in laser speckle contrast imaging, and the adaptive speckle decorrelation index (ASDI), a new metric that we defined based on the second-order autocorrelation function that considers the limited speckle modulation that occurs in partially-coherent imaging. We demonstrate excellent delineation of small, superficial vessels with slow blood flow in skin nevi using ASDI and larger, deeper vessels with faster blood flow using BFI, providing a powerful new tool for the imaging of microvasculature with significantly lower hardware complexity and cost than other optical imaging techniques.

We evaluated the optic disc microvasculature in healthy subjects and patients with optic nerve head drusen (ONHD), active papilledema, and acute nonarteritic anterior ischemic optic neuropathy (NAION) using optical coherence tomography angiography (OCTA).

This prospective, comparative case series included sixteen eyes with ONHD, thirty-one eyes with active papilledema, sixteen eyes with acute NAION, and thirty-two healthy eyes. The Optovue AngioVue OCT and OCTA Imaging System recorded peripapillary retinal nerve fiber layer (RNFL) thickness and vessel density maps from the radial peripapillary capillary (RPC) slab.

Average RNFL thicknesses were greater in eyes with ONHD, papilledema, and NAION compared to control eyes (all Ps < 0.001), but this parameter did not differ among patient groups. The mean peripapillary vessel density did not differ between the ONHD and control groups (P=1.000), nor between the NAION and papilledema groups (P=0.216). However, this value in the ONHD and control groups was significantly higher than in the NAION and papilledema groups (all Ps < 0.05).

RPC density is influenced during the progression of conditions such as ONHD, papilledema, and NAION. Although a decrease in vessel density values has been observed in cases of true disc edema, further research is necessary to assess the potential of OCTA in differentiating between true and pseudo-optic disc edema.

This study aims to examine vessel density changes in the optic nerve and macula following silicone oil removal (SOR) surgery in eyes with rhegmatogenous retinal detachment (RRD) at different time points by Optical Coherence Tomography Angiography (OCTA) in compared to the contralateral eye.

A total of 43 eyes from 43 patients with silicone oil in their eyes for 3-9 months underwent OCT-A using AngioVue and optic disc-associated vessel density (VD) and thickness, macular-associated VD and thickness, Foveal avascular zone (FAZ) area, FAZ perimeter (PERIM), Acircularity index (AI), vessel density within a 300 μm wide region of the FAZ were compared between eyes. OCTA scans were performed one week before SOR and one month and three months after SOR.

The mean age of participants was 52.8 years (SD = 15.85) and a median visual acuity was 0.8 (range: 0.5-1.0). Notably, male participants constituted 67.4% of the sample. The preoperative mean value BCVA (logMAR) of patients was 0.73, and 3 months post-oil removal was 0.7727. Regarding optic disc parameters, RNFL thickness and vessel density (VD) measurements Peripapillary, whole disc, inside disc, and Disc Angio (superior, Nasal, inferior, temporal) did not change. In analyzing macular thickness parameters, all of them (Whole and Fovea, parafoveal, and Perifovea) remained unchanged. Examining macular vessel density parameters revealed no significant changes across superficial and deep retinal layers. Finally, the comparison of the foveal avascular zone (FAZ) area and flow density (FD) parameters demonstrated consistent measurements with non-significant alterations observed in FAZ size (p = 0.6) and FD values (p = 0.49) over the monitored duration.

There was no change in peripapillary VD and macular vessel density of the superficial capillary plexus (SCP) and deep capillary plexus (DCP) after silicone oil removal. FAZ and full retinal thickness  remained stable 3 month after SOR.  Clinical trial number: Not applicable.

Retinal microcirculation alterations are early indicators of diabetic microvascular complications. Optical coherence tomography angiography (OCTA) is a noninvasive method to assess these changes. This study analyzes changes in retinal microcirculation in prediabetic patients during short-term increases in blood glucose using OCTA.

To investigate the changes in retinal microcirculation in prediabetic patients experiencing short-term increases in blood glucose levels using OCTA.

Fifty volunteers were divided into three groups: Group 1 [impaired fasting glucose (IFG) or impaired glucose tolerance (IGT)], Group 2 (both IFG and IGT), and a control group. Retinal microcirculation parameters, including vessel density (VD), perfusion density (PD), and foveal avascular zone (FAZ) metrics, were measured using OCTA. Correlations between these parameters and blood glucose levels were analyzed in both the fasting and postprandial states.

One hour after glucose intake, the central VD (P = 0.023), central PD (P = 0.026), and parafoveal PD (P < 0.001) were significantly greater in the control group than in the fasting group. In Group 1, parafoveal PD (P < 0.001) and FAZ circularity (P = 0.023) also increased one hour after glucose intake. However, no significant changes were observed in the retinal microcirculation parameters of Group 2 before or after glucose intake (P > 0.05). Compared with the control group, Group 1 had a larger FAZ area (P = 0.032) and perimeter (P = 0.018), whereas Group 2 had no significant differences in retinal microcirculation parameters compared with the control group (P > 0.05). Compared with Group 1, Group 2 had greater central VD (P = 0.013) and PD (P = 0.008) and a smaller FAZ area (P = 0.012) and perimeter (P = 0.010). One hour after glucose intake, Group 1 had a larger FAZ area (P = 0.044) and perimeter (P = 0.038) than did the control group, whereas Group 2 showed no significant differences in retinal microcirculation parameters compared with the control group (P > 0.05). Group 2 had greater central VD (P = 0.042) and PD (P = 0.022) and a smaller FAZ area (P = 0.015) and perimeter (P = 0.016) than Group 1. At fasting, central PD was significantly positively correlated with blood glucose levels (P = 0.044), whereas no significant correlations were found between blood glucose levels and OCTA parameters one hour after glucose intake.

A short-term increase in blood glucose has a more pronounced effect on retinal microcirculation in prediabetic patients with either IFG or IGT.

Dye-based angiography is the main imaging modality in evaluating the vasculature of the eye. Although most commonly used to assess retinal vasculature, it can also delineate normal and abnormal blood vessels in the anterior segment diseases-but is limited due to its invasive, time-consuming methods. Thus, anterior segment optical coherence tomography angiography (AS-OCTA) is a useful non-invasive modality capable of producing high-resolution images to evaluate the cornea and ocular surface vasculature. AS-OCTA has demonstrated the potential to detect and delineate blood vessels in the anterior segment with quality images comparable to dye-based angiography. AS-OCTA has a diverse range of applications for the cornea and ocular surface, such as objective assessment of corneal neovascularization and response to various treatments; diagnosis and evaluation of ocular surface squamous neoplasia; and evaluation of ocular surface disease including limbal stem cell deficiency and ischemia. Our review aims to summarize the new developments and clinical applications of AS-OCTA for the cornea and ocular surface.

Leber's Hereditary Optic Neuropathy (LHON) is a maternally inherited optic nerve disease primarily caused by mutations in mitochondrial DNA (mtDNA). The peak of onset is typically between 15 and 30 years, but variability exists. Misdiagnosis, often as inflammatory optic neuritis, delays treatment, compounded by challenges in timely genetic diagnosis. Given the availability of a specific treatment for LHON, its early diagnosis is imperative to ensure therapeutic appropriateness. This work gives an updated guidance about LHON differential diagnosis to clinicians dealing also with multiple sclerosi and neuromyelitis optica spectrtum disorders-related optic neuritis. LHON diagnosis relies on clinical signs and paraclinical evaluations. Differential diagnosis in the acute phase primarily involves distinguishing inflammatory optic neuropathies, considering clinical clues such as ocular pain, fundus appearance and visual recovery. Imaging analysis obtained with Optical Coherence Tomography (OCT) assists clinicians in early recognition of LHON and help avoiding misdiagnosis. Genetic testing for the three most common LHON mutations is recommended initially, followed by comprehensive mtDNA sequencing if suspicion persists despite negative results. We present and discuss crucial strategies for accurate diagnosis and management of LHON cases.

Glaucoma is the leading cause of irreversible blindness worldwide. It is an ocular disease characterized by an increase in intraocular pressure or, in some cases, normal intraocular pressure, which leads to optic nerve damage and progressive constriction of the visual field (VF). Primary Open-Angle Glaucoma (POAG) and Primary Angle-Closure Glaucoma (PACG) represent the predominant forms of glaucoma. Numerous hypotheses have been posited to elucidate the pathogenic mechanisms underlying these conditions. There is an emerging understanding of the distinct pathological processes that differentiate the various types of glaucoma. While some similarities in the mechanisms between PACG and POAG have been suggested, evidence indicates that there are also significant differences between the two. This review synthesizes the similarities and differences in the etiology of optic neuropathy caused by POAG and PACG, considering their respective pathophysiological mechanisms, the morphology of the optic disc and surrounding tissues, genetic characteristics, optical coherence tomography angiography, optical coherence tomography, and structural and functional features from VF examinations. These characteristics may contribute to a deeper comprehension of the underlying pathogenesis of glaucoma and enhance the management of different types of this ocular condition.

Optical Coherence Tomography (OCT)-based angiography (OCTA) is a high-resolution, high-speed, and non-invasive imaging method that can provide vascular mapping of subcutaneous tissue up to approximately 2 mm. In dermatology applications of OCTA, handheld probes are always designed with a piece of transparent but solid contact window placed at the end of the probe to directly contact the skin for achieving better focusing between the light source and the tissue, reducing noise caused by minor movements. The pressure between the contact window and the skin is usually uncontrollable, and high external pressure affects the quality of microvascular imaging by compressing the vessels and obstructing the underlying blood flow. Therefore, it is necessary to determine a pressure range to ensure that the vessels can be fully imaged in high-quality images. In this paper, two pressure sensors were added to the existing handheld OCT probe, and the imaging probe was fixed to a metal stand and adjusted vertically to change the pressure between the probe and the tested skin site, a gradient of roughly 4 kPa (with 1-2 kPa error) increase was applied in each experiment, and the impact of pressure to the vessel was calculated. The experiment involved a total of five subjects, three areas of which were scanned (palm, back of the hand, and forearm). The vessel density was calculated to evaluate the impact of external pressure on angiography. In addition, PSNR was calculated to ensure that the quality of different tests was at a similar level. The angiography showed the highest density (about 10%) when the pressure between the contact window on the probe and the test area was between 3 and 5 kPa. As the pressure increased, the vascular density decreased, and the rate of decrease varied in different test areas. After fitting all the data points according to the different sites, the slope of the fitted line, i.e., the rate of decrease in density per unit value of pressure, was found to be 4.05% at the palm site, 6.93% at the back of the hand, and 4.55% at the forearm site. This experiment demonstrates that the pressure between the skin and contact window is a significant parameter that cannot be ignored. It is recommended that in future OCTA data collection processes and probe designs, the impact of pressure on the experiment be considered.

This paper proposes a fully automated and unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs Random Field (MGRF) to detect the vascular system from retinal Optical Coherence Tomography Angiography (OCTA) images, which is a critical step in developing Computer-Aided Diagnosis (CAD) systems for detecting retinal diseases.

Using a new probabilistic model based on a Linear Combination of Discrete Gaussian (LCDG), the first level models the appearance of OCTA images and their spatially smoothed images. The parameters of the LCDG model are estimated using a modified Expectation Maximization (EM) algorithm. The second level models the maps of OCTA images, including the vascular system and other retina tissues, using MGRF with analytically estimated parameters from the input images. The proposed segmentation approach employs modified self-organizing maps as a MAP-based optimizer maximizing the joint likelihood and handles the Joint MGRF model in a new, unsupervised way. This approach deviates from traditional stochastic optimization approaches and leverages non-linear optimization to achieve more accurate segmentation results.

The proposed segmentation framework is evaluated quantitatively on a dataset of 204 subjects. Achieving 0.92 ± 0.03 Dice similarity coefficient, 0.69 ± 0.25 95-percentile bidirectional Hausdorff distance, and 0.93 ± 0.03 accuracy, confirms the superior performance of the proposed approach.

The conclusions drawn from the study highlight the superior performance of the proposed unsupervised and fully automated segmentation approach in detecting the vascular system from OCTA images. This approach not only deviates from traditional methods but also achieves more accurate segmentation results, demonstrating its potential in aiding the development of CAD systems for detecting retinal diseases.

To investigate associations between quantitative vascular measurements derived from intravenous fluorescein angiography (IVFA) and baseline characteristics on optical coherence tomography (OCT) in neovascular age-related macular degeneration (nAMD) patients.

The authors prospectively recruited patients with active choroidal neovascularization secondary to AMD over 50 years old, presenting to a single center in Toronto, Canada from 2017 to 2023. Ultra-widefield IVFA images were processed using the artificial intelligence RETICAD FAassist system to extract quantitative information on blood flow, perfusion, and blood-retinal-barrier (BRB) permeability. Associations between IVFA parameters with functional and anatomical outcomes were examined using univariable and multivariable regression models.

Eighty-one nAMD eyes and seven healthy control eyes were included. Compared with healthy controls, BRB permeability in the central and peripheral retina was significantly higher in nAMD patients (P < 0.001). On univariable analysis, BRB permeability measured centrally was significantly associated with central macular thickness (P = 0.035), whereas perfusion and blood flow measured centrally were significantly associated with macular volume (P = 0.043 and 0.037, respectively). On multivariable analysis, BRB permeability remained significantly associated with central macular thickness (P = 0.026).

Central BRB permeability measured on IVFA was significantly associated with baseline central macular thickness in nAMD patients. Future work should longitudinally explore associations between IVFA parameters and clinical characteristics in diverse nAMD populations.