Relationship between ischemic index, leakage index, and macular edema in branch retinal vein occlusion.

PURPOSE: To investigate the combined association of the ischemic index and leakage index with macular edema on ultra-widefield fluorescein angiography (UWFFA) in patients with branch retinal vein occlusion (BRVO). METHODS: Retrospective image analysis study. The leakage index and ischemic index were calculated using Fiji after aligning early and late UWFFA images. Differences in the ischemic index, leakage index, and central macular thickness (CMT) between ischemic and non-ischemic BRVO were compared. Moreover, the association between the ischemic index, leakage index, and macular edema was analyzed. RESULTS: Eighty-three patients with BRVO were enrolled, including 53 non-ischemic BRVO and 30 ischemic BRVO patients. No significant differences were observed in leakage index and CMT between ischemic BRVO and non-ischemic BRVO (all P > 0.05). In all included patients, CMT correlated with the panretina and all subregion leakage indexes (all P < 0.01), but not with the ischemic index (all P > 0.05). In the ischemic BRVO group, CMT showed a correlation with the leakage index in several regions, but not with the ischemic index. After adjusting for the ischemic index and other clinical features, CMT remained significantly correlated with the leakage index in all regions. CONCLUSION: The leakage index may be a more effective biomarker for monitoring BRVO-associated macular edema compared to the ischemic index. Further follow-up studies are warranted to validate these findings.

RELATIONSHIP BETWEEN RETINAL HEMORRHAGE ON GREEN AND RED CHANNELS OF ULTRA-WIDEFIELD FUNDUS IMAGES AND RETINAL PERFUSION IN ACUTE BRANCH RETINAL VEIN OCCLUSION.

PURPOSE: To explore the relationship between retinal hemorrhage in the green and red channels on ultra-widefield fundus images and the nonperfusion area (NPA) on ultra-widefield fundus fluorescein angiography in patients with acute branch retinal vein occlusion (BRVO). METHODS: This was a retrospective cross-sectional study with 96 patients, including 46 with ischemic BRVO and 50 with nonischemic BRVO. Correlation analysis between green channel hemorrhage (GCH), red channel hemorrhage (RCH), and NPA was performed. Panretina was divided into posterior and peripheral areas. RESULTS: Ischemic BRVO showed significantly higher GCH% and RCH% than nonischemic BRVO in the peripheral regions (both P < 0.001), whereas no significant differences were observed in the panretinal and posterior areas (all P > 0.05). Significant correlations were found between NPA% in the panretinal and peripheral areas and the corresponding GCH% and RCH% (all P < 0.01). However, no significant correlation was observed between posterior NPA% and posterior GCH% or RCH% (both P > 0.05). In addition, peripheral GCH% and RCH% were related to panretinal NPA% (r = 0.506, P < 0.001; r = 0.558, P < 0.001). CONCLUSION: Retinal hemorrhage on ultra-widefield fundus image was significantly associated with NPA, providing insights for assessing retinal perfusion status in acute BRVO patients.

Proliferative diabetic retinopathy and diabetic macular edema are two factors that increase macrophage-like cell density characterized by en face optical coherence tomography.

BACKGROUND: Macrophage-like cells (MLCs) located at the ILM were observed in live human retinas using adaptive optics optical coherence tomography (OCT) as well as clinically-used OCT. The study aimed to quantitatively analyzing MLCs at the vitreoretinal interface (VRI) in diabetic retinopathy (DR) using en face OCT and swept-source optical coherence tomography angiography (SS-OCTA). METHODS: 190 DR eyes were included in the study, with 70 proliferative diabetic retinopathy (PDR) eyes and 120 non- proliferative diabetic retinopathy (NPDR) eyes. Sixty-three eyes from normal subjects were included as controls. MLCs were visualized in a 5 µm en face OCT slab above the VRI centered on the fovea. Mann-Whitney U test and Kruskal-Wallis H test were used to compare the OCTA parameters and the MLC parameters among groups. We evaluated the MLC density among groups on binarized images after image processing. We also investigated the relationship between MLC density and other OCT parameters including retina thickness and vessel density (VD). RESULTS: The MLC density significantly increased in PDR eyes (PDR vs. NPDR, 8.97 (8.40) cells/mm2 vs.6.14 (8.78) cells/mm2, P = 0.013; PDR vs. normal, 8.97 (8.40) cells/mm2vs. 6.48 (6.71) cells/mm2, P = 0.027) and diabetic macular edema (DME) eyes (DME vs. without DME, 8.94 (8.26) vs.6.09 (9.00), P = 0.005). After adjusting for age and gender, MLC density in NPDR eyes negatively correlated to VD of deep capillary plexus (DCP) (P = 0.01). CONCLUSIONS: SS-OCTA is a non-invasive and simple method for the characterization of MLCs at the VRI. PDR and DME are two factors that increase MLC density. MLC density also correlated with VD.

Leakage index on ultra-widefield fluorescence angiography in different regions of retina and its correlation with cystoid macular edema in central retinal vein occlusion eyes.

PURPOSE: To investigate the relationship between leakage index on ultra-widefield fluorescence angiography (UWFFA) in different regions of retina and its correlation with cystoid macular edema (CME) in central retinal vein occlusion (CRVO) eyes. METHODS: Patients with naïve non-ischemic CRVO that had undergone UWFFA were identified. UWFFA images in the late phase were used to analyze the leakage index, which was performed by a semi-automatic method using ImageJ. The UWFFA images were subdivided into four regions by concentric circles centered on the macula for analysis. Optical coherence tomography (OCT) images were used to identify the presence of CME and obtain central macular thickness (CMT). RESULTS: A total of 57 eyes from 57 CRVO patients were analyzed in this study, including 43 eyes with CME and 14 eyes without CME. The leakage index in panretinal, peri-macular area (PMA), and near-peripheral area (NPA) was significantly different between eyes with CME and eyes without CME. Leakage index of PMA, NPA, mid-peripheral area (MPA), and panretinal area was significantly correlated with CMT, particularly the PMA. CONCLUSIONS: The distribution of leakage is different between patients with CME and patients without CME. The contribution of leakage index in different regions to CME was different, most predominant in PMA and NPA, and the closer to the center of the macula, the stronger the correlation between leakage index and CMT. A linear correlation was observed between CMT and the leakage index of panretinal area and all regions except far-peripheral area (FPA).

NEW INSIGHTS INTO THE ASSOCIATION BETWEEN CHOROIDAL VESSELS AND CHORIOCAPILLARIS IN NORMAL EYES.

PURPOSE: To determine the relationship between large-sized and medium-sized choroidal vessels and choriocapillaris using the three-dimensional choroidal vascularity index (3D CVI) and percentage of flow deficits (FD%). METHODS: Prospective observational study. The main outcome measures included choroidal volume parameters (3D CVI, mean choroidal thickness, total choroidal volume, choroidal luminal volume, and choroidal stromal volume), choriocapillaris parameters (FD%, average area of FD, and FD count), and age and axial length. RESULTS: A total of 63 healthy individuals with an average age of 40.60 ± 12.32 years were included in this study. Univariate analysis showed that FD% (R = 0.295, P = 0.019) and area of FD (R = 0.276, P = 0.028) were significantly positively associated with 3D CVI, and FD count was negatively associated with 3D CVI (R = -0.297, P = 0.018). After adjusting for age and axial length, a significant correlation between FD% and 3D CVI (R = 0.264, P = 0.039) and between area of FD and 3D CVI remained (R = 0.267, P = 0.037). However, no significant correlation was found between FD count and 3D CVI after adjusting for axial length (R = -0.220, P = 0.085). CONCLUSION: In healthy individuals, choroidal vessel dilatation as suggested by elevated 3D CVI may lead to decreased choriocapillaris perfusion, which was correlated with an enlarged area of FD in choriocapillaris.

Clinical characteristics of peripapillary hyperreflective ovoid mass-like structures in myopic children.

AIM: To describe the characteristics of peripapillary hyperreflective ovoid mass-like structure (PHOMS) in myopic children and to investigate factors associated with PHOMS. METHODS: This retrospective observational study included 101 eyes of 101 children (age ≤17y) with myopia. All included patients underwent comprehensive clinical examination. Optic nerve canal parameters, including disc diameter, optic nerve head (ONH) tilt angle, and border tissue angle were measured using serial enhanced-depth imaging spectral-domain optical coherence tomography (EDI-OCT). Based on the optic disc drusen consortium's definition of PHOMS, eyes were classified as PHOMS group and non-PHOMS group. PHOMS was categorized according to height. RESULTS: Sixty-seven (66.3%) eyes were found with PHOMS. Small PHOMS could only be detected by optical coherence tomography (OCT). Medium PHOMS could be seen with blurred optic disc borders corresponding to OCT. The most frequent location of PHOMS was at the nasosuperior (91%, 61 of 67 eyes) to ONH disc. The axial length and spherical equivalent were more myopic in the PHOMS group than in the non-PHOMS group (both P<0.001). ONH tilt angle was also significantly greater in PHOMS group than in non-PHOMS group [8.90 (7.16-10.54) vs 3.93 (3.09-5.25), P<0.001]. Border tissue angle was significantly smaller in PHOMS group than in non-PHOMS group [29.70 (20.90-43.81) vs 45.62 (35.18-60.45), P<0.001]. In the multivariable analysis, spherical equivalent (OR=3.246, 95%CI=1.209-8.718, P=0.019) and ONH tilt angle (OR=3.275, 95%CI=1.422-7.542, P=0.005) were significantly correlated with PHOMS. There was no disc diameter associated with PHOMS. In the linear regression analysis, border tissue angle was negatively associated with PHOMS height (ß=-2.227, P<0.001). CONCLUSION: PHOMS is associated with optic disc tilt and optic disc nasal shift in myopia. Disc diameter is not a risk factor for PHOMS. The changes in ONH caused by axial elongation facilitated an understanding of the mechanism of PHOMS.

Automatic Detection of 30 Fundus Diseases Using Ultra-Widefield Fluorescein Angiography with Deep Experts Aggregation.

INTRODUCTION: Inaccurate, untimely diagnoses of fundus diseases leads to vision-threatening complications and even blindness. We built a deep learning platform (DLP) for automatic detection of 30 fundus diseases using ultra-widefield fluorescein angiography (UWFFA) with deep experts aggregation. METHODS: This retrospective and cross-sectional database study included a total of 61,609 UWFFA images dating from 2016 to 2021, involving more than 3364 subjects in multiple centers across China. All subjects were divided into 30 different groups. The state-of-the-art convolutional neural network architecture, ConvNeXt, was chosen as the backbone to train and test the receiver operating characteristic curve (ROC) of the proposed system on test data and external test date. We compared the classification performance of the proposed system with that of ophthalmologists, including two retinal specialists. RESULTS: We built a DLP to analyze UWFFA, which can detect up to 30 fundus diseases, with a frequency-weighted average area under the receiver operating characteristic curve (AUC) of 0.940 in the primary test dataset and 0.954 in the external multi-hospital test dataset. The tool shows comparable accuracy with retina specialists in diagnosis and evaluation. CONCLUSIONS: This is the first study on a large-scale UWFFA dataset for multi-retina disease classification. We believe that our UWFFA DLP advances the diagnosis by artificial intelligence (AI) in various retinal diseases and would contribute to labor-saving and precision medicine especially in remote areas.

Distribution of leakage index using ultra-widefield fluorescein angiography in patients with non-ischemic branch retinal vein occlusion and its association with macular edema.

BACKGROUND: To investigate the distribution of leakage index in patients with non-ischemic branch retinal vein occlusion (BRVO) and its correlation with the severity of macular edema. METHODS: Retrospective observational study. Forty-five eyes of 45 patients with BRVO were included. Late ultra-widefield fluorescein angiography images of the affected eyes were processed and analyzed for their leakage index using Fiji software. The visible panretinal area was further divided into the peri­macular area (PMA), near-peripheral area (NPA), midperipheral area (MPA), and far-peripheral area (FPA). The relationship between the leakage index and central retinal thickness (CMT) was analyzed for the panretina and each subregion. RESULTS: The median (interquartile range) leakage indexes of the panretina, PMA, NPA, MPA, and FPA were 5.532% (7.667%), 23.127% (26.073%), 8.303% (16.807%), 1.588% (6.204%), and 0.408% (2.215%), respectively, with a mean CMT of 552.800 ± 183.335 µm. The CMT was positively correlated with the leakage index in the panretina, PMA, NPA, MPA and FPA (r = 0.468, 0.426, 0.463, 0.447, 0.320, respectively; all p < 0.05). CONCLUSIONS: The leakage index in non-ischemic BRVO patients is associated with macular edema severity. The leakage index has the potential to be a useful indicator for monitoring and guiding treatment of macular edema in BRVO patients.

Deep Learning for the Detection of Multiple Fundus Diseases Using Ultra-widefield Images.

INTRODUCTION: To design and evaluate a deep learning model based on ultra-widefield images (UWFIs) that can detect several common fundus diseases. METHODS: Based on 4574 UWFIs, a deep learning model was trained and validated that can identify normal fundus and eight common fundus diseases, namely referable diabetic retinopathy, retinal vein occlusion, pathologic myopia, retinal detachment, retinitis pigmentosa, age-related macular degeneration, vitreous opacity, and optic neuropathy. The model was tested on three test sets with data volumes of 465, 979, and 525. The performance of the three deep learning networks, EfficientNet-B7, DenseNet, and ResNet-101, was evaluated on the internal test set. Additionally, we compared the performance of the deep learning model with that of doctors in a tertiary referral hospital. RESULTS: Compared to the other two deep learning models, EfficientNet-B7 achieved the best performance. The area under the receiver operating characteristic curves of the EfficientNet-B7 model on the internal test set, external test set A and external test set B were 0.9708 (0.8772, 0.9849) to 1.0000 (1.0000, 1.0000), 0.9683 (0.8829, 0.9770) to 1.0000 (0.9975, 1.0000), and 0.8919 (0.7150, 0.9055) to 0.9977 (0.9165, 1.0000), respectively. On a data set of 100 images, the total accuracy of the deep learning model was 93.00%, the average accuracy of three ophthalmologists who had been working for 2 years and three ophthalmologists who had been working in fundus imaging for more than 5 years was 88.00% and 94.00%, respectively. CONCLUSION: High performance was achieved on all three test sets using our UWFI multidisease classification model with a small sample size and fast model inference. The performance of the artificial intelligence model was comparable to that of a physician with 2-5 years of experience in fundus diseases at a tertiary referral hospital. The model is expected to be used as an effective aid for fundus disease screening.

Increased Macrophage-like Cell Density in Retinal Vein Occlusion as Characterized by en Face Optical Coherence Tomography.

Objectives: to quantitatively analyze macrophage-like cells (MLCs) at the vitreoretinal interface in retinal vein occlusion (RVO) using swept-source optical coherence tomography angiography (SS-OCTA) and en face optical coherence tomography (OCT). Methods: The study included 72 RVO patients, with 43 acute patients and 29 chronic patients. For a normal control, 64 fellow eyes were included. MLCs were visualized in a 5 µm en face OCT slab above the vitreoretinal interface centered on the fovea. After semi-automatic binarization and quantification, we evaluated the MLC count and density among groups. We also investigated the MLC density and distribution relative to retinal edema. Results: Morphological changes and congregation of MLCs appeared in RVO eyes. The MLC density of both the acute and chronic groups was significantly higher than that of the control eyes (p < 0.001). In the acute group, the MLC density of the edematous region was lower than both the non-edematous region (p < 0.001) and the whole image (p < 0.01). The MLC density in acute eyes was negatively correlated to central fovea thickness (CFT) (r = −0.352, p < 0.05). The MLC density in chronic eyes was positively correlated to CFT and mean retina thickness (MRT) (r = 0.406, p < 0.05; r = 0.412, p < 0.05, respectively). Conclusions: SS-OCTA is a viable and simple method for the characterization of MLCs at the vitreoretinal interface. A significant increase in the MLC density in both acute and chronic eyes implicates the activation and recruitment of MLCs in RVO and that the MLC density and distribution can be affected by retinal edema.

Quantitative Assessment of Three-Dimensional Choroidal Vascularity and Choriocapillaris Flow Signal Voids in Myopic Patients Using SS-OCTA.

PURPOSE: To compare the choroidal vascularity of large- and middle-sized choroidal vessels and choriocapillaris (CC) perfusion in patients with different degrees of myopia using swept-source optical coherence tomography angiography (SS-OCTA). METHODS: One hundred and thirteen people with myopia were enrolled. SS-OCTA was performed to analyze the choroidal vascularity and CC perfusion. Three-dimensional (3D) choroidal vascularity index (CVI) and choroidal luminal volumes (LV) were obtained by artificial intelligence segmentation of the choroidal lumen in Volume OCT images. CC perfusion was assessed by flow signal voids (FSVs). RESULTS: In the macular, multiple linear regression model showed that choroidal thickness (CT), total choroidal volume, LV, and choroidal stromal volume were negatively correlated with axis length (AL), respectively (all p < 0.001). Three dimensional CVI was negatively associated with AL (p < 0.05). FSV% was positively correlated with age only (p < 0.001). Additionally, after adjustment for age and AL, FSV% had a significant negative correlation with CT (p < 0.05). CONCLUSION: Choroidal vascularity decreases gradually with increasing severity of myopia. The decrease of CC blood perfusion was related to a higher severity of myopia and the thinning of choroid.

Observation of Peripapillary Choroidal Vascularity in Natural Disease Course and After Gene Therapy for Leber's Hereditary Optic Neuropathy.

Purpose: To compare peripapillary choroidal vascularity among Leber's Hereditary Optic Neuropathy (LHON) patients at different stages of natural course and healthy controls using optical coherence tomography (OCT), and to evaluate peripapillary choroidal vascularity changes in LHON patients before and after gene therapy. Methods: 57 LHON patients and 15 healthy controls were enrolled in this prospective clinical study. LHON patients were divided into three duration groups based on stage of disease progression. Both patients and healthy controls underwent OCT scans focused on the optic disc at baseline with Heidelberg Spectralis, and patients underwent OCT at 1, 3, and 6 months after gene therapy. OCT images were converted and binarized using ImageJ software. Choroidal thickness (CT), total choroidal area (TCA), and choroidal vascularity index (CVI) in each quadrant of OCT images were measured to evaluate peripapillary choroidal vascularity. Results: At baseline, the average CT was not significantly different between LHON patients at different stages and between healthy controls (P = 0.468). Although average TCA and average CVI were slightly higher in LHON patients at different stages than in healthy controls, the difference was not statistically significant (P = 0.282 and 0.812, respectively). After gene therapy, The average TCA at 1 month after gene therapy was significantly higher than that before gene therapy (P = 0.003), while no significant differences were found in the average CT or average CVI in LHON patients before and 1,3 and 6 months after gene therapy using pairwise comparisons (all P > 0.05). Conclusions: No significant difference was found in choroidal vascularity of LHON patients at different stages and healthy controls. Choroidal vascularity seems to stay stable after gene therapy.

Association of Subregional Quantitative Ultra-widefield Fluorescence Angiography Characteristics With the Occurrence of Diabetic Macular Edema and Proliferative Diabetic Retinopathy.

Purpose: To explore the relationships of region-specific properties of ultra-widefield fluorescence angiography (UWFFA) images with two adverse outcomes, diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR), and also the severity of diabetic retinopathy (DR). Methods: A cross-sectional observational study was performed to retrospectively analyze UWFFA images of patients with DR. All patients underwent UWFFA and optical coherence tomography examination. Leakage index and microaneurysm (MA) count were measured using Trainable Weka Segmentation, a machine learning algorithm, and ischemic index (ISI) was measured manually. The correlation between UWFFA parameters and severity of DR was analyzed, and receiver operating characteristic curves were used to estimate their diagnostic value for DME and PDR. Results: A total of 108 eyes from 108 patients with DR (mean age of 56.04 ± 8.85 years) were analyzed. As the severity of DR increased, the ISI and leakage index of the panretina and all subregions increased. Panretinal MA count and leakage index were significantly higher in eyes with DME than those without DME (p = 0.044 and 0.001, respectively). Leakage index and ISI were significantly higher in eyes with PDR than those without PDR in both panretinal and subregion-specific measurements (all p < 0.05). Throughout the retina and specifically in the posterior area (PoA), the leakage index had a higher diagnostic value for DME than ISI or MA count (all p < 0.05). The diagnostic value of MA count for PDR was lower than that of ISI and leakage index (all p < 0.05). Conclusion: The ISI, leakage index, and MA count in the PoA and panretina correlated with the severity of DR, especially the posterior parameter. The leakage index was more valuable than ISI and MA count in determining the occurrence of DME. ISI and leakage index were better predictors of PDR.

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

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

Noninvasive Identification of Immune-Related Biomarkers in Hepatocellular Carcinoma.

Primary liver carcinoma is one of the most common malignant tumors with a poor prognosis. This study aims to uncover the potential mechanisms and identify core biomarkers of hepatocellular carcinoma (HCC). The HCC gene expression profile GSE49515 was chosen to analyze the differentially expressed genes from purified RNA of peripheral blood mononuclear cells, including 10 HCC patients and 10 normal individuals. GO and KEGG pathway analysis and PPI network were used, and the enrichment of the core genes out of 15 hub genes was evaluated using GEPIA and GSEA, respectively. We employed flow cytometry to count mononuclear cells to verify our opinions. In this analysis, 344 DEGs were captured, including 188 upregulated genes and 156 downregulated genes; besides that, 15 hub genes were identified. GO analysis and KEGG analysis showed the DEGs were particularly involved in immune response, antigen processing and presentation, and infection and inflammation. The PPI network uncovered 2 modules were also mainly involved in immune response. In conclusion, our analysis disclosed the immune subversion was the major signature of HCC associated closely with JUN, VEGFA, TNFSF10, and TLR4, which could be novel noninvasive biomarkers in peripheral blood and targets for early diagnosis and therapy of HCC.