Predictive Performance of an Updated Polygenic Risk Score for Age-Related Macular Degeneration.

PURPOSE: A recent genome-wide association study of age-related macular degeneration (AMD) identified new AMD-associated risk variants. These variants now can be incorporated into an updated polygenic risk score (PRS). This study aimed to assess the performance of an updated PRS, PRS2023, in an independent cohort of older individuals with retinal imaging data and to compare performance with an older PRS, PRS2016. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 4175 participants of European ancestry, 70 years of age or older, with genotype and retinal imaging data. METHODS: We used logistic regression models and area under the receiver operating characteristic curve (AUC) to assess the performance of PRS2023 compared with PRS2016. AMD status and severity were graded using color fundus photography. MAIN OUTCOME MEASURES: Association of PRS2023 and PRS2016 with AMD risk at baseline. RESULTS: At enrollment among 4175 participants, 2605 participants (62.4%) had no AMD and 853 participants (20.4%), 671 participants (16.1%), and 46 participants (1.1%) had early, intermediate, and late-stage AMD, respectively. More than 27% of the participants with a high PRS2023 (top quartile) had intermediate or late-stage AMD, compared with < 15% for those in the middle 2 quartiles and less than 13% for those in the lowest quartile. Both PRS2023 and PRS2016 were associated significantly with AMD after adjustment for age, sex, smoking status, and lipid levels, with increasing odds ratios (ORs) for worsening AMD grades. PRS2023 outperformed PRS2016 (P = 0.03 for all AMD and P = 0.03 for late AMD, DeLong test comparing AUC). PRS2023 was associated with late-stage AMD with an adjusted OR of 5.05 (95% confidence interval [CI], 3.41-7.47) per standard deviation. The AUC of a model containing conventional or nongenetic risk factors and PRS2023 was 91% (95% CI, 87%-95%) for predicting late-stage AMD, which improved 12% over the model without the PRS (AUC, 79%; P < 0.001 for difference). CONCLUSIONS: A new PRS, PRS2023, for AMD outperforms a previous PRS and predicts increasing risk for late-stage AMD (with stronger association for more severe imaging-confirmed AMD grades). Our findings have clinical implications for the improved prediction and risk stratification of AMD. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Application effect of an artificial intelligence-based fundus screening system: evaluation in a clinical setting and population screening.

BACKGROUND: To investigate the application effect of artificial intelligence (AI)-based fundus screening system in real-world clinical environment. METHODS: A total of 637 color fundus images were included in the analysis of the application of the AI-based fundus screening system in the clinical environment and 20,355 images were analyzed in the population screening. RESULTS: The AI-based fundus screening system demonstrated superior diagnostic effectiveness for diabetic retinopathy (DR), retinal vein occlusion (RVO) and pathological myopia (PM) according to gold standard referral. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of three fundus abnormalities were greater (all > 80%) than those for age-related macular degeneration (ARMD), referable glaucoma and other abnormalities. The percentages of different diagnostic conditions were similar in both the clinical environment and the population screening. CONCLUSIONS: In a real-world setting, our AI-based fundus screening system could detect 7 conditions, with better performance for DR, RVO and PM. Testing in the clinical environment and through population screening demonstrated the clinical utility of our AI-based fundus screening system in the early detection of ocular fundus abnormalities and the prevention of blindness.

Drusen morphometrics on optical coherence tomography in eyes with age-related macular degeneration and normal aging.

PURPOSE: To compare drusen size metrics (apical height and basal width) on optical coherence tomography (OCT) B-scans with their size assessed on color photos in eyes with age-related macular degeneration (AMD) and normal aging. METHODS: A total of 508 drusen were evaluated in this analysis. Flash color fundus photos (CFP), infrared reflectance (IR) images, and OCT B-scans obtained at the same visit were evaluated. Individual drusen were identified on CFPs and the diameters of the drusen were measured in planimetric grading software. CFPs were manually registered to the IR image with their corresponding OCT volume. After confirming correspondence between the CFP and OCT, the apical height and basal width of the same drusen were measured on OCT B-scans. RESULTS: Drusen were divided into small, medium, large, and very large categories based on their diameter on the CFP images (< 63, 63 to 124, 125 to 249, and [Formula: see text] 250 µm, respectively). The OCT apical height of small drusen on CFP ranged from 20 to 31 µm, while medium drusen ranged from 31 to 46 µm, large drusen ranged from 45 µm to 111 µm, and very large drusen ranged from 55 µm to 208 µm. The OCT basal width measured < 99 µm in small drusen, from 99 to 143 µm in medium drusen, from 141 to 407 µm in large drusen, and > 209 µm in very large drusen. CONCLUSION: Drusen of different size categories on color photographs may also be separated according to their apical height and basal width on OCT. The apical height and basal width ranges defined in this analysis may be of value in the design of an OCT-based grading scale for AMD.

Histology and clinical imaging lifecycle of black pigment in fibrosis secondary to neovascular age-related macular degeneration.

PURPOSE: Melanotic cells with large spherical melanosomes, thought to originate from retinal pigment epithelium (RPE), are found in eyes with neovascular age-related macular degeneration (nvAMD). To generate hypotheses about RPE participation in fibrosis, we correlate histology to clinical imaging in an eye with prominent black pigment in fibrotic scar secondary to nvAMD. METHODS: Macular findings in a white woman with untreated inactive subretinal fibrosis due to nvAMD in her right eye were documented over 9 years with color fundus photography (CFP), fundus autofluorescence (FAF) imaging, and optical coherence tomography (OCT). After death (age 90 years), this index eye was prepared for light and electron microscopy to analyze 7 discrete zones of pigmentation in the fibrotic scar. In additional donor eyes with nvAMD, we determined the frequency of black pigment (n = 36 eyes) and immuno-labeled for retinoid, immunologic, and microglial markers (RPE65, CD68, Iba1, TMEM119; n = 3 eyes). RESULTS: During follow-up of the index eye, black pigment appeared and expanded within a hypoautofluorescent fibrotic scar. The blackest areas correlated to melanotic cells (containing large spherical melanosomes), some in multiple layers. Pale areas had sparse pigmented cells. Gray areas correlated to cells with RPE organelles entombed in the scar and multinucleate cells containing sparse large spherical melanosomes. In 94% of nvAMD donor eyes, hyperpigmentation was visible. Certain melanotic cells expressed some RPE65 and mostly CD68. Iba1 and TMEM119 immunoreactivity, found both in retina and scar, did not co-localize with melanotic cells. CONCLUSION: Hyperpigmentation in CFP results from both organelle content and optical superimposition effects. Black fundus pigment in nvAMD is common and corresponds to cells containing numerous large spherical melanosomes and superimposition of cells containing sparse large melanosomes, respectively. Melanotic cells are molecularly distinct from RPE, consistent with a process of transdifferentiation. The subcellular source of spherical melanosomes remains to be determined. Detailed histology of nvAMD eyes will inform future studies using technologies for spatially resolved molecular discovery to generate new therapies for fibrosis. The potential of black pigment as a biomarker for fibrosis can be investigated in clinical multimodal imaging datasets.

Automated detection of severe diabetic retinopathy using deep learning method.

PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR with lesion recognition based on color fundus photography. METHODS: The Kaggle public dataset for DR grading is used in the project, including 53,576 fundus photos in the test set, 28,101 in the training set, and 7,025 in the validation set. We randomly select 4,192 images for lesion annotation. Inception V3 structure is adopted as the classification algorithm. Both 299 × 299 pixel images and 896 × 896 pixel images are used as the input size. ROC curve, AUC, sensitivity, specificity, and their harmonic mean are used to evaluate the performance of the models. RESULTS: The harmonic mean and AUC of the model of 896 × 896 input are higher than those of the 299 × 299 input model. The sensitivity, specificity, harmonic mean, and AUC of the method with 896 × 896 resolution images as input for severe DR are 0.925, 0.907, 0.916, and 0.968, respectively. The prediction error mainly occurs in moderate NPDR, and cases with more hard exudates and cotton wool spots are easily predicted as severe cases. Cases with preretinal hemorrhage and vitreous hemorrhage are easily identified as severe cases, and IRMA is the most difficult lesion to recognize. CONCLUSIONS: We have studied the intelligent diagnosis of severe DR based on color fundus photography. This artificial intelligence-based technology offers a possibility to increase the accessibility and efficiency of severe DR screening.

AI-driven generalized polynomial transformation models for unsupervised fundus image registration.

We introduce a novel AI-driven approach to unsupervised fundus image registration utilizing our Generalized Polynomial Transformation (GPT) model. Through the GPT, we establish a foundational model capable of simulating diverse polynomial transformations, trained on a large synthetic dataset to encompass a broad range of transformation scenarios. Additionally, our hybrid pre-processing strategy aims to streamline the learning process by offering model-focused input. We evaluated our model's effectiveness on the publicly available AREDS dataset by using standard metrics such as image-level and parameter-level analyzes. Linear regression analysis reveals an average Pearson correlation coefficient (R) of 0.9876 across all quadratic transformation parameters. Image-level evaluation, comprising qualitative and quantitative analyzes, showcases significant improvements in Structural Similarity Index (SSIM) and Normalized Cross Correlation (NCC) scores, indicating its robust performance. Notably, precise matching of the optic disc and vessel locations with minimal global distortion are observed. These findings underscore the potential of GPT-based approaches in image registration methodologies, promising advancements in diagnosis, treatment planning, and disease monitoring in ophthalmology and beyond.

Refined image quality assessment for color fundus photography based on deep learning.

Purpose: Color fundus photography is widely used in clinical and screening settings for eye diseases. Poor image quality greatly affects the reliability of further evaluation and diagnosis. In this study, we developed an automated assessment module for color fundus photography image quality assessment using deep learning. Methods: A total of 55,931 color fundus photography images from multiple centers in Shanghai and the public database were collected and annotated as training, validation, and testing data sets. The pre-diagnosis image quality assessment module based on the multi-task deep neural network was designed. The detailed criterion of color fundus photography image quality including three subcategories with three levels of grading was applied to improve precision and objectivity. The auxiliary tasks such as the localization of the optic nerve head and macula, the classification of laterality, and the field of view were also included to assist the quality assessment. Finally, we validated our module internally and externally by evaluating the area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, and quadratic weighted Kappa. Results: The "Location" subcategory achieved area under the receiver operating characteristic curves of 0.991, 0.920, and 0.946 for the three grades, respectively. The "Clarity" subcategory achieved area under the receiver operating characteristic curves of 0.980, 0.917, and 0.954 for the three grades, respectively. The "Artifact" subcategory achieved area under the receiver operating characteristic curves of 0.976, 0.952, and 0.986 for the three grades, respectively. The accuracy and Kappa of overall quality reach 88.15% and 89.70%, respectively, on the internal set. These two indicators on the external set were 86.63% and 88.55%, respectively, which were very close to that of the internal set. Conclusions: This work showed that our deep module was able to evaluate the color fundus photography image quality using more detailed three subcategories with three grade criteria. The promising results on both internal and external validation indicated the strength and generalizability of our module.

Interreader and Intermodality Variability in Macular Atrophy Quantification in Neovascular Age-related Macular Degeneration: Comparison of 6 Imaging Modalities.

PURPOSE: Macular atrophy is a common complication in neovascular age-related macular degeneration (AMD) and is associated with poorer visual outcomes. This study evaluated interreader and intermodality variability in measuring macular atrophy in previously treated neovascular AMD eyes without exudation using 6 imaging modalities. DESIGN: Prospective, cohort study. PARTICIPANTS: Thirty participants with previously treated neovascular AMD showing no signs of exudation at the time of enrollment and exhibiting macular atrophy. METHODS: During the same clinic visit, patients were imaged using 6 different imaging modalities: color fundus photography (CFP; Clarus, Carl Zeiss Meditec), near-infrared imaging (NIR; Spectralis, Heidelberg Engineering), structural OCT (Spectralis, Heidelberg Engineering), green fundus autofluorescence (GAF; Clarus, Carl Zeiss Meditec), blue fundus autofluorescence (BAF; Spectralis, Heidelberg Engineering), and pseudocolor imaging (MultiColor; Spectralis, Heidelberg Engineering). Two readers independently measured the macular atrophy area. MAIN OUTCOME MEASURES: Interreader and intermodality agreement. RESULTS: The 95% coefficient of repeatability was 5.98 mm2 for CFP, 4.46 mm2 for MultiColor, 3.90 mm2 for BAF, 3.92 mm2 for GAF, 4.86 mm2 for NIR, and 3.55 mm2 for OCT. Similarly, the coefficient of variation was lowest for OCT-based grading at 0.08 and highest for NIR-based grading at 0.28. Accordingly, the intraclass correlation coefficient was 0.742 for CFP, 0.805 for MultiColor, 0.857 for BAF, 0.850 for GAF, 0.755 for NIR, and 0.917 for OCT. The 6 different imaging modalities presented measurements with different mean values, with only a limited number of comparisons not significantly different between the instruments, although measurements were correlated. The largest size of macular atrophy was measured with structural OCT-based grading (median = 4.65 mm2; interquartile range [IQR] = 4.78 mm2) and the smallest was with CFP-based grading (median = 3.86 mm2; IQR = 5.06 mm2). Inconsistencies arose from various factors. CONCLUSIONS: In patients with neovascular AMD, macular atrophy measurements vary significantly depending on the imaging technique used. Color fundus photography-based assessments yielded the smallest macular atrophy sizes, whereas structural OCT-based assessments produced the largest. These discrepancies stem from both the inherent limitations of each modality in assessing retinal pigment epithelial atrophy and factors related to neovascularization, such as the coexistence of fibrosis. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Clinical application of multicolor scanning laser ophthalmology in diagnosis and grading of central retinal artery occlusion.

Purpose: To characterize features of central retinal artery occlusion (CRAO) using multicolor (MC) imaging and to assess the differences in CRAO grading between color fundus photography (CFP) and MC image qualitatively and quantitatively. Methods: We conducted a prospective, cross-sectional study in the Department of Ophthalmology of Renmin Hospital of Wuhan University. In total, 86 acute CRAO patients were included. Spectral-domain optical coherence tomography (SD-OCT), CFP, and MC examinations were taken at baseline. Based on the findings of these three examinations, CRAO was divided into three grades (incomplete, subtotal, and total). Based on OCT grading criteria, we qualitatively compared the ability of grading CRAO by CFP and MC. CRAO patient's visual acuity (VA) was obtained from the initial visit. The retinal thickness was measured by SD-OCT. Superficial capillary plexus (SCP) and deep capillary plexus (DCP) were obtained from optical coherence tomography angiography (OCTA) examinations. Quantitative data were compared across the three acute CRAO subgroups and against three examination findings. Results: MC image had significantly higher power of acute CRAO detection than CFP (P = 0.03). In the same group of CRAO patients, there was no significant difference in VA when comparing OCT with the MC grading system or with the CFP grading system (all P > 0.05). Significant differences in VA were found between the three CRAO subgroups only under MC grading (P = 0.016). In incomplete CRAO patients, significant differences were found in central fovea thickness (CFT) when comparing OCT with the CFP grading system (P = 0.019). In the same group of CRAO patients, there was no significant difference in retinal thickness when comparing OCT with the MC grading system (All P > 0.05). Significance differences in CFT (P < 0.001), innermost retinal layer (IMRL; P < 0.01), middle retinal layer (MRL; P < 0.001), and outer retinal layer (ORL; P = 0.021) were found between the three CRAO subgroups by MC grading. Vessel density of SCP showed a statistically increased as the severity of three CRAO subgroups (P = 0.03), whereas DCP did not have significant differences (P = 0.745). Comparisons were made between the OCT grading method and the MC and CFP grading methods; there is no significant difference in vessel density of SCP and DCP (All P > 0.05). Conclusion: The images obtained by MC are superior to those obtained by CFP in CRAO grading, retinal thickness, and vessel density measurement. MC imaging may be more capable of CRAO grading than OCT. We recommend MC imaging to determine CRAO severity to guide disease treatment and predict visual prognosis.

Association between polygenic risk for schizophrenia and retinal morphology: A cross-sectional analysis of the United Kingdom Biobank.

We examined the relationship between genetic risk for schizophrenia (SZ), using polygenic risk scores (PRSs), and retinal morphological alterations. Retinal structural and vascular indices derived from optical coherence tomography (OCT) and color fundus photography (CFP) and PRSs for SZ were analyzed in N = 35,024 individuals from the prospective cohort study, United Kingdom Biobank (UKB). Results indicated that macular ganglion cell-inner plexiform layer (mGC-IPL) thickness was significantly inversely related to PRS for SZ, and this relationship was strongest within higher PRS quintiles and independent of potential confounders and age. PRS, however, was unrelated to retinal vascular characteristics, with the exception of venular tortuosity, and other retinal structural indices (macular retinal nerve fiber layer [mRNFL], inner nuclear layer [INL], cup-to-disc ratio [CDR]). Additionally, the association between greater PRS and reduced mGC-IPL thickness was only significant for participants in the 40-49 and 50-59 age groups, not those in the 60-69 age group. These findings suggest that mGC-IPL thinning is associated with a genetic predisposition to SZ and may reflect neurodevelopmental and/or neurodegenerative processes inherent to SZ. Retinal microvasculature alterations, however, may be secondary consequences of SZ and do not appear to be associated with a genetic predisposition to SZ.

Comparison of Color Fundus Photography and Multicolor Fundus Imaging for Detection of Lesions in Diabetic Retinopathy and Retinal Vein Occlusion.

Purpose: To evaluate the agreement between conventional fundus photography (CFP) and multicolor fundus imaging (MFI) for the detection of lesions of diabetic retinopathy (DR) and retinal vein occlusion (RVO). Methods: Cross-sectional analysis of eyes with DR or RVO who underwent CFP and MFI. All images were independently analyzed by two observers (O1 and O2), and the evaluated lesions were classified as "present" or "absent". Then, a paired comparison between both exams of the same eye was performed, to assess which made it easier to detect the lesions. Results: Considering DR, the agreement was substantial for cotton wool spots and photocoagulation scars for both observers (O1: κ=0.75 and κ=0.67; O2: κ=0.71 and κ=0.64, respectively) and for hard exudates for O1 (κ=0.80). These lesions were detected more frequently on MFI. Regarding RVO, the agreement was considered substantial for venous sheathing by O1 (κ=0.64) and moderate for optociliary shunts by O2 (κ=0.60). Optociliary shunts were detected more frequently in CPF by both observers and venous sheathing on MFI by O1. For microaneurysms, retinal hemorrhages, retinal neovascularization, and proliferative membranes, in DR, and retinal hemorrhages, venous engorgement, and retinal neovascularization in RVO, the agreement was almost perfect (κ>0.82). In the paired analysis, both observers considered that, in DR, microaneurysms and retinal hemorrhages were easier to detect on CFP and that retinal neovascularization, cotton wool spots, and photocoagulation scars were easier to identify on MFI. Regarding RVO, optocilliary shunts were easier to identify on CFP and venous engorgement on MFI. Conclusion: The agreement of MFI and CFP was substantial to almost perfect for most lesions. MFI seems better to detect cotton wool spots and photocoagulations scars in DR and venous sheathing in RVO. Optocilliary shunts seem easier to detect on CFP.

Vitreoretinal Specialist Use of Ancillary Testing: An IRIS® Registry Analysis.

Purpose: To investigate patterns of ancillary imaging testing among vitreoretinal specialists for patients with vitreoretinal disease in the United States (US). Methods: Optical coherence tomography (OCT), color fundus photography (CFP), and fluorescein angiography (FA), ordered by vitreoretinal specialists and documented within the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) between 01 January 2018 and 31 December 2020, were retrospectively assessed. Trends in imaging modality choice were analyzed by payer type, geographic region, and practice type. Sub-analyses were conducted according to categorization of vitreoretinal specialists into those treating a high versus low volume of patients with neovascular age-related macular degeneration (nAMD). Results: OCT was the most common imaging modality used, followed by CFP and FA. Following normalization, the highest volume of OCT procedures performed were identified among Medicare Advantage and Medicare Fee-for-Service beneficiaries, within the South of the US, and at medium and large practices. Minimal differences were observed for CFP and FA volume across payer types and regions. Across practice types, the largest volume of CFP and FA procedures were identified in small and private equity owned practices, respectively. Vitreoretinal specialists with a high nAMD volume more frequently performed OCT than those with a low nAMD volume. Conclusion: Vitreoretinal specialists demonstrated a strong preference for OCT, with real-world associations according to payer type, geographic location, and practice type. Volume of nAMD patients seen impacted the likelihood of specialists ordering OCTs.

OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing.

Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operators, systemic imperfections, or patient-related causes. Optimal retinal image quality is mandated for accurate medical diagnoses and automated analyses. Herein, we leveraged the Optimal Transport (OT) theory to propose an unpaired image-to-image translation scheme for mapping low-quality retinal CFPs to high-quality counterparts. Furthermore, to improve the flexibility, robustness, and applicability of our image enhancement pipeline in the clinical practice, we generalized a state-of-the-art model-based image reconstruction method, regularization by denoising, by plugging in priors learned by our OT-guided image-to-image translation network. We named it as regularization by enhancing (RE). We validated the integrated framework, OTRE, on three publicly available retinal image datasets by assessing the quality after enhancement and their performance on various downstream tasks, including diabetic retinopathy grading, vessel segmentation, and diabetic lesion segmentation. The experimental results demonstrated the superiority of our proposed framework over some state-of-the-art unsupervised competitors and a state-of-the-art supervised method.

Retromode Imaging Technology for Detecting Drusen-Like Deposits in Healthy Adults.

PURPOSE: To investigate the ability of retromode imaging technology to visualize drusen-like deposits (DLDs) in the macular region of healthy individuals without retinal diseases. Additionally, the correlation between subject age and the density of DLDs was assessed and their topographic distribution was evaluated. DESIGN: Prospective, observational, cross-sectional study SUBJECTS: Healthy volunteers (aged ≥ 35 years) without macular diseases. METHODS: This study evaluated macular images in healthy adults using color fundus photography (FP) and retromode imaging. Two masked graders counted the number of DLDs identifiable with each modality. The standardized ETDRS concentric rings were adopted to divide DLDs based on their topographic distribution. MAIN OUTCOME MEASURES: Comparison of the number of DLDs detected with each imaging modality. The association between DLDs and age. The topographic distribution of macular DLDs with retromode imaging. RESULTS: The study included 91 eyes of 52 healthy volunteers (mean ± standard deviation age, 57.9 ± 10.9 years; range, 36-82 years). Overall, at least 1 DLD was present in 63.74% of eyes on color FP and 96.71% on retromode. Retromode imaging allowed detection of significantly more DLDs compared with color FP within the ETDRS grid (median [interquartile range], 4 [1-14] vs. 0 [0-0] respectively; P < 0.001). The density of DLDs was higher in the outer and inner rings compared with the central subfield (relative risk [RR], 16.70; 95% confidence interval [CI], 10.3-27.3 vs. RR 17.1; 95% CI, 10.5-27.6, respectively). Age was significantly correlated with DLDs density in all 3 sectors (all P < 0.05). CONCLUSIONS: Retromode technology allowed the detection of a significantly higher number of DLDs compared with FP in the macula of healthy individuals. This noninvasive imaging modality could be used to investigate the effect of the aging process on the macula, fostering a better understanding of the pathophysiology of age-related macular diseases. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Multimodal Ophthalmic Imaging in Spinocerebellar Ataxia Type 7.

The aim of this case series and narrative literature review is to highlight the importance of multimodal imaging in the ophthalmological examination of patients with spinocerebellar ataxia type 7 and provide a summary of the most relevant imaging techniques. Three patients with SCA7 were included in this case series. A literature review revealed twenty-one publications regarding ocular manifestations of SCA7, and the most relevant aspects are summarized. The role of different imaging techniques in the follow-up of SCA7 patients is analyzed, including color vision testing, corneal endothelial topography, color fundus photography (CFP) and autofluorescence, near infrared reflectance imaging, spectral domain optical coherence tomography (SDOCT), visual field examination, and electrophysiological tests. SDOCT provides a rapid and non-invasive imaging evaluation of disease progression over time. Additional examination including NIR imaging can provide further information on photoreceptor alteration and subtle disruption of the RPE, which are not evident with CFP at an early stage. Electrophysiological tests provide essential results on the state of cone and rod dystrophy, which could be paramount in guiding future genetic therapies. Multimodal imaging is a valuable addition to comprehensive ophthalmological examination in the diagnosis and management of patients with SCA7.

Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM.

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in developed countries. Identifying patients at high risk of progression to late AMD, the sight-threatening stage, is critical for clinical actions, including medical interventions and timely monitoring. Recently, deep-learning-based models have been developed and achieved superior performance for late AMD prediction. However, most existing methods are limited to the color fundus photography (CFP) from the last ophthalmic visit and do not include the longitudinal CFP history and AMD progression during the previous years' visits. Patients in different AMD subphenotypes might have various speeds of progression in different stages of AMD disease. Capturing the progression information during the previous years' visits might be useful for the prediction of AMD progression. In this work, we propose a Contrastive-Attention-based Time-aware Long Short-Term Memory network (CAT-LSTM) to predict AMD progression. First, we adopt a convolutional neural network (CNN) model with a contrastive attention module (CA) to extract abnormal features from CFPs. Then we utilize a time-aware LSTM (T-LSTM) to model the patients' history and consider the AMD progression information. The combination of disease progression, genotype information, demographics, and CFP features are sent to T-LSTM. Moreover, we leverage an auto-encoder to represent temporal CFP sequences as fixed-size vectors and adopt k-means to cluster them into subphenotypes. We evaluate the proposed model based on real-world datasets, and the results show that the proposed model could achieve 0.925 on area under the receiver operating characteristic (AUROC) for 5-year late-AMD prediction and outperforms the state-of-the-art methods by more than 3%, which demonstrates the effectiveness of the proposed CAT-LSTM. After analyzing patient representation learned by an auto-encoder, we identify 3 novel subphenotypes of AMD patients with different characteristics and progression rates to late AMD, paving the way for improved personalization of AMD management. The code of CAT-LSTM can be found at GitHub.

Evaluation of an Artificial Intelligence System for the Detection of Diabetic Retinopathy in Chinese Community Healthcare Centers.

Objective: To evaluate the sensitivity and specificity of a Comprehensive Artificial Intelligence Retinal Expert (CARE) system for detecting diabetic retinopathy (DR) in a Chinese community population. Methods: This was a cross-sectional, diagnostic study. Participants with a previous diagnosis of diabetes from three Chinese community healthcare centers were enrolled in the study. Single-field color fundus photography was obtained and analyzed by the AI system and two ophthalmologists. Primary outcome measures included the sensitivity, specificity, positive predictive value, and negative predictive value with their 95% confidence intervals (CIs) of the AI system in detecting DR and diabetic macular edema (DME). Results: In this study, 443 subjects (848 eyes) were enrolled, and 283 (63.88%) were men. The mean age was 52.09 (11.51) years (range 18-82 years); 266 eyes were diagnosed with any DR, 233 with more-than-mild diabetic retinopathy (mtmDR), 112 with vision-threatening diabetic retinopathy (vtDR), and 57 with DME. The image ability of the AI system was as high as 99.06%, whereas its sensitivity and specificity varied significantly in detecting DR with different severities. The sensitivity/specificity to detect any DR was 75.19% (95%CI 69.47-80.17)/93.99% (95%CI 91.65-95.71), mtmDR 78.97% (95%CI 73.06-83.90)/92.52% (95%CI 90.07-94.41), vtDR 33.93% (95%CI 25.41-43.56)/97.69% (95%CI 96.25-98.61), and DME 47.37% (95%CI 34.18-60.91)/93.99% (95%CI 91.65-95.71). Conclusions: This multicenter cross-sectional diagnostic study noted the safety and reliability of the CARE system for DR (especially mtmDR) detection in Chinese community healthcare centers. The system may effectively solve the dilemma faced by Chinese community healthcare centers: due to the lack of ophthalmic expertise of primary physicians, DR diagnosis and referral are not timely.

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

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

Advanced retinal imaging and applications for clinical practice: A consensus review.

Imaging is an integral part of the evaluation and management of retinal disorders. Each imaging modality has its own unique capabilities and can show a different aspect or perspective of disease. Multimodal retinal imaging provides a wealth of substantive and insightful information; however, the integration of all this complex data can be overwhelming. We discuss the applications and the strengths and limitations of the many different retinal imaging tools that are approved for clinical use. These modalities include color fundus photography, widefield imaging, fundus autofluorescence, near infrared reflectance, optical coherence tomography angiography, and en face optical coherence tomography. We also cover the advantages and disadvantages of a multimodal approach.

Assessment of the Classification of Age-Related Macular Degeneration Severity from the Northern Ireland Sensory Ageing Study Using a Measure of Dark Adaptation.

Purpose: To assess the differences in rod-mediated dark adaptation (RMDA) between different grades of age-related macular degeneration (AMD) severity using an OCT-based criterion compared with those of AMD severity using the Beckman color fundus photography (CFP)-based classification and to assess the association between the presence of subretinal drusenoid deposits (SDDs) and RMDA at different grades of AMD severity using an OCT-based classification. Design: Cross-sectional study. Participants: Participants from the Northern Ireland Sensory Ageing study (Queen's University Belfast). Methods: Complete RMDA (rod-intercept time [RIT]) data, CFP, and spectral-domain OCT images were extracted. Participants were stratified into 4 Beckman groups (omitting late-stage AMD) and 3 OCT-based groups. The presence and stage of SDDs were identified using OCT. Main Outcome Measures: Rod-intercept time data (age-corrected). Results: Data from 459 participants (median [interquartile range] age, 65 [59-71] years) were stratified by both the classifications. Subretinal drusenoid deposits were detected in 109 eyes. The median (interquartile range) RMDA for the Beckman classification (Beckman 0-3, with 3 being intermediate age-related macular degeneration [iAMD]) groups was 6.0 (4.5-8.7), 6.6 (4.7-10.5), 5.7 (4.4-7.4), and 13.2 (6-21.1) minutes, respectively. OCT classifications OCT0-OCT2 yielded different median (interquartile range) values: 5.8 (4.5-8.5), 8.4 (5.2-13.3), and 11.1 (5.3-20.1) minutes, respectively. After correcting for age, eyes in Beckman 3 (iAMD) had statistically significantly worse RMDA than eyes in the other Beckman groups (P ≤ 0.005 for all), with no statistically significant differences between the other Beckman groups. Similarly, after age correction, eyes in OCT2 had worse RMDA than eyes in OCT0 (P ≤ 0.001) and OCT1 (P < 0.01); however, there was no statistically significant difference between eyes in OCT0 and eyes in OCT1 (P = 0.195). The presence of SDDs was associated with worse RMDA in OCT2 (P < 0.01) but not in OCT1 (P = 0.285). Conclusions: Eyes with a structural definition of iAMD have delayed RMDA, regardless of whether a CFP- or OCT-based criterion is used. In this study, after correcting for age, the RMDA did not differ between groups of eyes defined to have early AMD or normal aging, regardless of the classification. The presence of SDDs has some effect on RMDA at different grades of AMD severity.