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Purpose: The relationship between retinal morphology, as assessed by optical coherence tomography (OCT), and retinal function in microperimetry (MP) has not been well studied, despite its increasing importance as an essential functional endpoint for clinical trials and emerging therapies in retinal diseases. Normative databases of healthy ageing eyes are largely missing from literature., Methods: Healthy subjects above 50 years were examined using two MP devices, MP-3 (NIDEK) and MAIA (iCare). An identical grid, encompassing 45 stimuli was used for retinal sensitivity (RS) assessment. Deep-learning-based algorithms performed automated segmentation of ellipsoid zone (EZ), outer nuclear layer (ONL), ganglion cell layer (GCL) and retinal nerve fibre layer (RNFL) from OCT volumes (Spectralis, Heidelberg). Pointwise co-registration between each MP stimulus and corresponding location on OCT was performed via registration algorithm. Effect of age, eccentricity and layer thickness on RS was assessed by mixed effect models., Results: Three thousand six hundred stimuli from twenty eyes of twenty patients were included. Mean patient age was 68.9 ± 10.9 years. Mean RS for the first exam was 28.65 ± 2.49 dB and 25.5 ± 2.81 dB for MP-3 and MAIA, respectively. Increased EZ thickness, ONL thickness and GCL thickness were significantly correlated with increased RS (all p < 0.001). Univariate models showed lower RS with advanced age and higher eccentricity (both p < 0.05)., Conclusion: This work provides reference values for healthy age-related EZ and ONL-thicknesses without impairment of visual function and evidence for RS decrease with eccentricity and increasing age. This information is crucial for interpretation of future clinical trials in disease., (© 2024 The Author(s). Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Background/aims: To determine the suitability of functional MRI (fMRI) as an objective measure of macular function following therapeutic intervention; conventional psychophysical measures rely heavily on patient compliance., Methods: Twenty patients with neovascular age-related macular degeneration (nAMD) were studied with high-resolution fMRI, visual acuity, reading accuracy and speed, contrast sensitivity (CS) and microperimetry (MP) before and after 3 monthly intravitreal injections of ranibizumab. Population-receptive field retinotopic maps calculated from fMRI data were compared with psychophysical measures and optical coherence tomography., Results: Best-corrected visual acuity (BCVA) responders (≥5 letters) showed an increase of 29.5% in activated brain area, while non-responders showed a decrease of 0.8%. Radial histograms over eccentricity allowed quantification of the absolute number of significant voxels and thus differences before and after treatment. Responders showed increases in foveal (α<0.5°) activation, while non-responders did not. Absence of intraretinal fluid and preservation of outer retinal layers was associated with higher numbers of active V1 voxels and better BCVA. Higher voxel numbers were associated with improved reading performance and, less marked, with BCVA, CS and MP., Conclusion: The data show that retinotopic mapping using fMRI can successfully be applied objectively to evaluate the therapeutic response in nAMD patients treated with anti-vascular endothelial growth factor therapy. This demonstrates the ability of retinotopic mapping to provide an objective assessment of functional recovery at a cortical level; the technique can therefore be applied, in other degenerative macular diseases, to the assessment of potential therapeutic interventions such as gene therapy or cell replacement therapy., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2025. No commercial re-use. See rights and permissions. Published by BMJ Group.)

Purpose: To assess the anatomic and functional outcomes in eyes with diabetic macular edema (DME) switched from intravitreal aflibercept to faricimab in a real-world setting., Methods: Retrospective, interventional consecutive case series. Patients with DME were switched from aflibercept to faricimab and categorized based on central subfield thickness (CST) 4 weeks after last aflibercept injection into responding DME (rDME, CST reduction >20% or CST ≤ 250 µm) and nonresponding DME (nrDME, CST unchanged or increased). Patients received a loading dose of two monthly faricimab injections followed by a treat-and-extend regimen. Differences in response between rDME and nrDME were analyzed based on injection interval, change in CST, and visual acuity (VA) 12 weeks postswitch., Results: Fifty-two eyes of 40 patients met inclusion criteria (rDME: n = 26, nrDME: n = 26). Baseline and week 12: VA (logMAR) rDME 0.29 ± 0.23 and 0.22 ± 0.28, nrDME 0.42 ± 0.32 and 0.36 ± 0.29; CST (µm) rDME 370 ± 99 and 288 ± 80, nrDME 384 ± 85 and 380 ± 129. After 12 weeks, 54% rDME and 25% nrDME eyes showed a CST decrease of >20% or CST ≤ 250 µm. Forty-six percent rDME and 50% nrDME eyes had a ±20% CST change, 25% of nrDME eyes had a >20% CST increase, and 73% of rDME eyes and 47% of nrDME eyes reached an extended interval of 8 weeks or longer after 12 weeks., Conclusions: Most DME eyes previously responding or not responding to aflibercept experienced a reduction or stabilization of DME after 12 weeks of faricimab treatment. rDME showed a better anatomic response, and treatment intervals could be extended earlier and longer than nrDME.

Objective: To analyze the presence and morphologic characteristics of drusenoid pigment epithelial detachments (DPEDs) in spectral-domain optical coherence tomography (SD-OCT) in Caucasian patients with early and intermediate age-related macular degeneration (AMD) as well as the influence of these characteristics on best-corrected visual acuity (BCVA) and disease progression., Design: Prospective observational cohort study., Participants: 89 eyes of 56 patients with early and intermediate AMD., Methods: Examinations consisted of BCVA, SD-OCT, and indocyanine green angiography. Evaluated parameters included drusen type, mean drusen height and -volume, the presence of DPED, DPED maximum height, -maximum diameter, -volume, topographic location, the rate of DPED collapse, and the development of macular neovascularization (MNV) or geographic atrophy (GA)., Results: DPED maximum height (162.34 µm ± 75.70 μm, p = 0.019) was significantly associated with the development of GA and MNV. For each additional 100 μm in maximum height, the odds of developing any late AMD (GA or MNV) increased by 2.23 (95% CI = 1.14-4.35). The presence of DPED (44 eyes, p = 0.01), its volume (0.20 mm ± 0.20 mm, p = 0.01), maximum diameter (1860.87 μm ± 880.74 μm, p = 0.03), maximum height (p < 0.001) and topographical location in the central millimetre (p = 0.004) of the Early Treatment Diabetic Retinopathy Study (ETDRS)-Grid were significantly correlated with BCVA at the last follow-up (0.15logMAR ± 0.20logMAR; Snellen equivalent approximately 20/28). DPEDs occurred significantly less in the outer quadrants than in the central millimetre and inner quadrants of ETDRS-Grid (all p values < 0.001)., Conclusions: The height of drusen and DPEDs is a biomarker that is significantly associated with the development of late AMD and visual loss. DPEDs affect predominantly the center and inner quadrants of the ETDRS-Grid., Competing Interests: Footnotes and Disclosure G.S.R. has received grant funding from RetInSight and speaker fees from Apellis. U.S.-E is a scientific consultant for Apellis, has received grant funding from Genentech, Kodiak, Novartis, Apellis, and RetInSight and has received patents/royalty from RetInSight. The rest of the authors indicate no financial support or conflicts of interest. All authors attest that they meet the current ICMJE criteria for authorship., (Copyright © 2023 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.)

Background and Objective: Despite the promising capabilities of 3D transformer architectures in video analysis, their application to high-resolution 3D medical volumes encounters several challenges. One major limitation is the high number of 3D patches, which reduces the efficiency of the global self-attention mechanisms of transformers. Additionally, background information can distract vision transformers from focusing on crucial areas of the input image, thereby introducing noise into the final representation. Moreover, the variability in the number of slices per volume complicates the development of models capable of processing input volumes of any resolution while simple solutions like subsampling may risk losing essential diagnostic details., Methods: To address these challenges, we introduce an end-to-end transformer-based framework, variable length feature aggregator transformer rollout (VLFATRollout), to classify volumetric data. The proposed VLFATRollout enjoys several merits. First, the proposed VLFATRollout can effectively mine slice-level fore-background information with the help of transformer's attention matrices. Second, randomization of volume-wise resolution (i.e. the number of slices) during training enhances the learning capacity of the learnable positional embedding (PE) assigned to each volume slice. This technique allows the PEs to generalize across neighboring slices, facilitating the handling of high-resolution volumes at the test time., Results: VLFATRollout was thoroughly tested on the retinal optical coherence tomography (OCT) volume classification task, demonstrating a notable average improvement of 5.47% in balanced accuracy over the leading convolutional models for a 5-class diagnostic task. These results emphasize the effectiveness of our framework in enhancing slice-level representation and its adaptability across different volume resolutions, paving the way for advanced transformer applications in medical image analysis. The code is available at https://github.com/marziehoghbaie/VLFATRollout/., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Neurovascular coupling impairment and inner retinal layer thinning are early detectable retinal changes in diabetes, and both worsen during progression of diabetic retinopathy (DR). However, direct interactions between these features have not been investigated so far. Therefore, we aimed to analyze associations between the retinal functional hyperemic response to light stimulation and the thickness of individual neuroretinal layers in eyes with early non-proliferative DR., Methods: Thirty patients with type 1 diabetes featuring mild (n = 15) or moderate (n = 15) non-proliferative DR and 14 healthy subjects were included in this cross-sectional study. Retinal vessel diameters were measured before and during illumination with flickering light using a dynamic vessel analyzer. Individual layer thickness in the macula was analyzed from spectral domain optical coherence tomography., Results: Flicker light-induced vessel dilation was significantly reduced in patients compared to healthy controls (veins: 3.0% vs. 6.1%, p < 0.001; arteries: 1.3% vs. 5.1%, p = 0.005). Univariately, the response in retinal veins of diabetes patients correlated significantly with ganglion cell layer (GCL) thickness (r = 0.46, p = 0.010), and negatively with hemoglobin A1c (HbA1c) levels (r=-0.41, p = 0.023) and age (r=-0.38, p = 0.037), but not with baseline diameters, glucose levels, or diabetes duration. In a multiple regression model only GCL thickness (p = 0.017, β = 0.42) and HbA1c (p = 0.045, β=-0.35) remained significantly associated with the vascular flicker light response., Conclusion: The results indicate that thinner GCL and worse glycemic control both contribute to reduced retinal neurovascular coupling in patients with clinical signs of DR. Progression of neurovascular dysfunction in DR might be related to structural degeneration of the neurovascular complex in the inner retina., Competing Interests: Declarations. Ethical approval: Approval was obtained from the ethics committee of the Medical University of Vienna. The procedures used in this study adhere to the tenets of the Declaration of Helsinki. Consent to participate: Informed consent was obtained from all individual participants included in the study. Financial interests: Ursula Schmidt-Erfurth is a scientific consultant for Heidelberg Engineering; all other authors have no competing financial interests in relation to the work described., (© 2024. The Author(s).)

The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising patient numbers accompanied by ongoing developments of therapeutic approaches. Concurrent advances in imaging modalities provide eye care professionals with a large amount of data for each patient. Furthermore, with continuous progress in therapeutics, there is an unmet need for reliable structural and functional biomarkers in clinical trials and practice to optimize personalized patient care and evaluate individual responses to treatment. A fast and objective solution is Artificial intelligence (AI), which has revolutionized assessment of AMD in all disease stages. Reliable and validated AI-algorithms can aid to overcome the growing number of patients, visits and necessary treatments as well as maximize the benefits of multimodal imaging in clinical trials. Therefore, there are ongoing efforts to develop and validate automated algorithms to unlock more information from datasets allowing automated assessment of disease activity and disease progression. This review aims to present selected AI algorithms, their development, applications and challenges regarding assessment and prediction of AMD progression., Competing Interests: Competing interests SF, KB, SR: No financial disclosures. GSR: Apellis (C), Bayer (C), RetInSight (F), Roche (C), Boehringer Ingelheim (C). US-E: Abbvie (C), Apellis Pharmaceuticals (F, C), Aviceda (C), Complement therapeutics (C), Galimedix (C), Genentech (F), Janssen (C), Heidelberg Engineering (C, F), Kodiak (F), Kriya (C), Novartis (F), ONL (C), Roche (C, F), RetInSight (C), Stealth Therapeutics (C), Topcon (F, C)., (© 2024. The Author(s).)

To examine the morphological impact of deep learning (DL)-quantified biomarkers on point-wise sensitivity (PWS) using microperimetry (MP) and optical coherence tomography (OCT) in intermediate AMD (iAMD). Patients with iAMD were examined by OCT (Spectralis). DL-based algorithms quantified ellipsoid zone (EZ)-thickness, hyperreflective foci (HRF) and drusen volume. Outer nuclear layer (ONL)-thickness and subretinal drusenoid deposits (SDD) were quantified by human experts. All patients completed four MP examinations using an identical custom 45 stimuli grid on MP-3 (NIDEK) and MAIA (CenterVue). MP stimuli were co-registered with corresponding OCT using image registration algorithms. Multivariable mixed-effect models were calculated. 3.600 PWS from 20 eyes of 20 patients were analyzed. Decreased EZ thickness, decreased ONL thickness, increased HRF and increased drusen volume had a significant negative effect on PWS (all p < 0.001) with significant interaction with eccentricity (p < 0.001). Mean PWS was 26.25 ± 3.43 dB on MP3 and 22.63 ± 3.69 dB on MAIA. Univariate analyses revealed a negative association of PWS and SDD (p < 0.001). Subclinical changes in EZ integrity, HRF and drusen volume are quantifiable structural biomarkers associated with reduced retinal function. Topographic co-registration between structure on OCT volumes and sensitivity in MP broadens the understanding of pathognomonic biomarkers with potential for evaluation of quantifiable functional endpoints., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Purpose: Growing interest in microperimetry (MP) or fundus-controlled perimetry as a targeted psychometric testing method in geographic atrophy (GA) is warranted because of the disease subclinical/extrafoveal appearance or preexisting foveal loss with visual acuity becoming unreliable. We provide comprehensive pointwise test-retest repeatability reference values on the most widely used MP devices and combine them with targeted testing in areas of retinal pigment epithelium (RPE) as well as photoreceptor (PR) integrity loss, guiding the interpretation of sensitivity loss during the long-term follow-up of patients with GA., Design: Prospective reliability study., Methods: Patients with GA underwent consecutive testing on CenterVue (iCare) MAIA and NIDEK MP3 devices. Obtained pointwise sensitivity (PWS) measurements were spatially coregistered to an optical coherence tomography volume scan acquired during the same visit. Areas with RPE and PR integrity loss, drusen, and PR thickness as well as the volume of hyperreflective foci where identified and quantified using a set of validated deep learning-based algorithms. Test-retest repeatability was assessed according to areas defined by biomarker-specific morphologic changes using Bland-Altmann coefficients of repeatability. Furthermore, the interdevice correlation, the repeatability of scotoma point detection, and any potential effects on fixation stability were assessed., Results: Nine hundred stimuli per device from 20 subjects were included. Identical overall PWS test-retest variance could be detected for MAIA (±6.57) and MP3 (±6.59). PR integrity loss was associated with a higher test-retest variance on both devices (MAIA, P = .002; MP3, P < .001). Higher coefficients of repeatability for stimuli in areas presenting RPE loss (±10.99 vs ±5.34) or hyperreflective foci (±9.21 vs ±6.25) could only be detected on MP3 examinations (P < .001 and P = .01, respectively). An excellent intradevice correlation (MAIA 0.94 [0.93-0.95], MP3 0.94 [0.94-0.95]) and a good mean interdevice correlation (0.84 [0.53-0.92]) were demonstrated. The chosen device, run order, or absence of foveal sparing had no significant effect on fixation stability., Conclusion: Areas presenting automatically quantified PR integrity loss with and without underlying RPE loss are associated with higher test-retest variance for both MAIA and MP3. These findings are crucial for an accurate interpretation of GA progression during long-term follow-up and the planning of future trials with MP testing as functional study endpoint., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: To quantify ellipsoid zone (EZ) loss during anti-VEGF therapy for neovascular age-related macular degeneration (nAMD) and correlate these findings with nAMD disease activity using artificial intelligence-based algorithms., Methods: Spectral domain optical coherence tomography (Spectralis, Heidelberg Engineering) images from nAMD treatment-naïve patients from the Fight Retinal Blindness! (FRB!) Registry from Zürich, Switzerland were processed at baseline and over 3 years of follow-up. An approved deep learning algorithm (Fluid Monitor, RetInSight) was used to automatically quantify intraretinal fluid (IRF), subretinal fluid (SRF) and pigment epithelial detachment (PED). An ensemble U-net deep learning algorithm was used to automated quantify EZ integrity based on EZ layer thickness. The impact of fluid volumes on EZ thickness and late-stages outcomes were calculated using Wilcoxon rank-sum tests, a linear mixed model and a longitudinal panel regression model., Results: Two hundred and eleven eyes from 158 patients were included. The mean ± SD EZ loss area in the central 6 mm was 1.81 ± 2.68 mm 2 at baseline and reached 6.21 ± 6.15 mm 2 at month 36. Higher fluid volumes (top 25%) of IRF and PED in the central 1 and 6 mm of the macula were significantly associated with more advanced EZ thinning and loss compared to the low fluid volume subgroup. The high SRF subgroup in the linear regression model showed no statistically significant association with EZ integrity in the central macula; however, the longitudinal analysis revealed an increased EZ thickness with no additional loss., Conclusions: Intraretinal fluid and PED volumes and their resolution pattern have an impact on alteration of the underlying EZ layer. AI-supported quantifications are helpful in quantifying early signs of macular atrophy and providing individual risk profiles as a basis for tailored therapies for optimized visual outcomes., (© 2024 The Author(s). Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Purpose: The progression of geographic atrophy (GA) secondary to age-related macular degeneration is highly variable among individuals. Prediction of the progression is critical to identify patients who will benefit most from the first treatments currently approved. The aim of this study was to investigate the value and difference in predictive power between ophthalmologists and artificial intelligence (AI) in reliably assessing individual speed of GA progression., Design: Prospective, expert and AI comparison study., Participants: Eyes with natural progression of GA from a prospective study (NCT02503332)., Methods: Ophthalmologists predicted yearly growth speed of GA as well as selected the potentially faster-growing lesions from 2 eyes based on fundus autofluorescence (FAF), near-infrared reflectance (NIR), and OCT. A deep learning algorithm predicted progression solely on the baseline OCT (Spectralis, Heidelberg Engineering)., Main Outcome Measures: Accuracy, weighted κ, and concordance index (c-index) between the prediction made by ophthalmology specialists, ophthalmology residents, and the AI algorithm., Results: A total of 134 eyes of 134 patients from a phase II clinical trial were included; among them, 53 were from the sham arm, and 81 were from untreated fellow eyes. Four ophthalmologists performed 2880 gradings. Human experts reached an accuracy of 0.37, 0.43, and 0.41 and a κ of 0.06, 0.16, and 0.18 on FAF, NIR + OCT, and FAF + NIR + OCT, respectively. On a pairwise comparison task, human experts achieved a c-index of 0.62, 0.59, and 0.60. Automated AI-based analysis reached an accuracy of 0.48 and κ of 0.23 on the first task, and c-index of 0.69 on the second task solely utilizing OCT imaging., Conclusions: Prediction of individual progression will become an important task for patient counseling, most importantly with the treatments becoming available. Human gradings improved with the availability of OCT. However, automated AI performed better than ophthalmologists in several comparisons. Artificial intelligence-supported decisions improve clinical precision, access to timely care for the community, and socioeconomic feasibility in the management of the leading cause of irreversible vision loss., Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials discussed in this article., (Copyright © 2024 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Self-supervised learning has become the cornerstone of building generalizable and transferable artificial intelligence systems in medical imaging. In particular, contrastive representation learning techniques trained on large multi-modal datasets have demonstrated impressive capabilities of producing highly transferable representations for different downstream tasks. In ophthalmology, large multi-modal datasets are abundantly available and conveniently accessible as modern retinal imaging scanners acquire both 2D fundus images and 3D optical coherence tomography (OCT) scans to assess the eye. In this context, we introduce a novel multi-modal contrastive learning-based pipeline to facilitate learning joint representations for the two retinal imaging modalities. After self-supervised pre-training on 153,306 scan pairs, we show that such a pre-training framework can provide both a retrieval system and encoders that produce comprehensive OCT and fundus image representations that generalize well for various downstream tasks on three independent external datasets, explicitly focusing on clinically pertinent prediction tasks. In addition, we show that interchanging OCT with lower-cost fundus imaging can preserve the predictive power of the trained models., (© 2024. The Author(s).)

Purpose of Review: This review aims to address the recent advances of artificial intelligence (AI) in the context of clinical management of geographic atrophy (GA), a vision-impairing late-stage manifestation of age-related macular degeneration (AMD)., Recent Findings: Recent literature shows substantial advancements in the development of AI systems to segment GA lesions on multimodal retinal images, including color fundus photography (CFP), fundus autofluorescence (FAF) and optical coherence tomography (OCT), providing innovative solutions to screening and early diagnosis. Especially, the high resolution and 3D-nature of OCT has provided an optimal source of data for the training and validation of novel algorithms. The use of AI to measure progression in the context of newly approved GA therapies, has shown that AI methods may soon be indispensable for patient management. To date, while many AI models have been reported on, their implementation in the real-world has only just started. The aim is to make the benefits of AI-based personalized treatment accessible and far-reaching., Summary: The most recent advances (pearls) and challenges (pitfalls) associated with AI methods and their clinical implementation in the context of GA will be discussed., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Regulatory approval of the first two therapeutic substances for the management of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) is a major breakthrough following failure of numerous previous trials. However, in the absence of therapeutic standards, diagnostic tools are a key challenge as functional parameters in GA are hard to provide. The majority of anatomical biomarkers are subclinical, necessitating advanced and sensitive image analyses. In contrast to fundus autofluorescence (FAF), optical coherence tomography (OCT) provides high-resolution visualization of neurosensory layers, including photoreceptors, and other features that are beyond the scope of human expert assessment. Artificial intelligence (AI)-based methodology strongly enhances identification and quantification of clinically relevant GA-related sub-phenotypes. Introduction of OCT-based biomarker analysis provides novel insight into the pathomechanisms of disease progression and therapeutic, moving beyond the limitations of conventional descriptive assessment. Accordingly, the Food and Drug Administration (FDA) has provided a paradigm-shift in recognizing ellipsoid zone (EZ) attenuation as a primary outcome measure in GA clinical trials. In this review, the transition from previous to future GA classification and management is described. With the advent of AI tools, diagnostic and therapeutic concepts have changed substantially in monitoring and screening of GA disease. Novel technology combined with pathophysiological knowledge and understanding of the therapeutic response to GA treatments, is currently opening the path for an automated, efficient and individualized patient care with great potential to improve access to timely treatment and reduce health disparities., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

To evaluate the intra- and interdevice repeatability of microperimetry (MP) assessments in patients with diabetic macular edema (DME) two consecutive MP testings (45 fovea-centered stimuli, 4-2 staircase strategy) were performed using MP3 (NIDEK, Aichi, Japan) and MAIA (CenterVue, Padova, Italy), respectively. Intraretinal fluid (IRF) and ellipsoid zone (EZ) thickness were automatically segmented by published deep learning algorithms. Hard exudates (HEs) were annotated semi-automatically and disorganization of retinal inner layers (DRIL) was segmented manually. Point-to-point registration of MP stimuli to corresponding spectral-domain OCT (Spectralis, Heidelberg Engineering, Germany) locations was performed for both devices. Repeatability was assessed overall and in areas of disease-specific OCT biomarkers using Bland-Altmann coefficients of repeatability (CoR). A total of 3600 microperimetry stimuli were tested in 20 eyes with DME. Global CoR was high using both devices (MP3: ± 6.55 dB, MAIA: ± 7.69 dB). Higher retest variances were observed in stimuli with IRF (MP3: CoR ± 7.4 dB vs. ± 6.0 dB, p = 0.001, MAIA: CoR ± 9.2dB vs. ± 6.8 dB, p = 0.002) and DRIL on MP3 (CoR ± 6.9 dB vs. ± 3.2 dB, p < 0.001) compared to stimuli without. Repeatabilities were reduced in areas with thinner EZ layers (both p < 0.05). Fixation (Fuji classification) was relatively unstable independent of device and run. These findings emphasize taking higher caution using MP in patients with DME., (© 2024. The Author(s).)

Objective: To investigate the effect of macular fluid volumes (subretinal fluid [SRF], intraretinal fluid [IRF], and pigment epithelium detachment [PED]) after initial treatment on functional and structural outcomes in neovascular age-related macular degeneration in a real-world cohort from Fight Retinal Blindness!, Methods: Treatment-naive neovascular age-related macular degeneration patients from Fight Retinal Blindness! (Zürich, Switzerland) were included. Macular fluid on optical coherence tomography was automatically quantified using an approved artificial intelligence algorithm. Follow-up of macular fluid, number of anti-vascular endothelial growth factor treatments, effect of fluid volumes after initial treatment (high, top 25%; low, bottom 75%) on best-corrected visual acuity, and development of macular atrophy and fibrosis was investigated over 48 months., Results: A total of 209 eyes (mean age, 78.3 years) were included. Patients with high IRF volumes after initial treatment differed by -2.6 (p = 0.021) and -7.4 letters (p = 0.007) at months 12 and 48, respectively. Eyes with high IRF received significantly more treatments (+1.6 [p < 0.001] and +5.3 [p = 0.002] at months 12 and 48, respectively). Patients with high SRF or PED had comparable best-corrected visual acuity outcomes but received significantly more treatments for SRF (+2.4 [p < 0.001] and +11.4 [p < 0.001] at months 12 and 48, respectively) and PED (+1.2 [p = 0.001] and +7.8 [p < 0.001] at months 12 and 48, respectively)., Discussion: Patients with high macular fluid after initial treatment are at risk of losing vision that may not be compensable with higher treatment frequency for IRF. Higher treatment frequency for SRF and PED may result in comparable treatment outcomes. Quantification of macular fluid in all compartments is essential to detect eyes at risk of aggressive disease., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-efficient downstream image analysis. However, the direct application of conventional contrastive methods to medical datasets introduces two domain-specific issues. Firstly, several image transformations which have been shown to be crucial for effective contrastive learning do not translate from the natural image to the medical image domain. Secondly, the assumption made by conventional methods, that any two images are dissimilar, is systematically misleading in medical datasets depicting the same anatomy and disease. This is exacerbated in longitudinal image datasets that repeatedly image the same patient cohort to monitor their disease progression over time. In this paper we tackle these issues by extending conventional contrastive frameworks with a novel metadata-enhanced strategy. Our approach employs widely available patient metadata to approximate the true set of inter-image contrastive relationships. To this end we employ records for patient identity, eye position (i.e. left or right) and time series information. In experiments using two large longitudinal datasets containing 170,427 retinal optical coherence tomography (OCT) images of 7912 patients with age-related macular degeneration (AMD), we evaluate the utility of using metadata to incorporate the temporal dynamics of disease progression into pretraining. Our metadata-enhanced approach outperforms both standard contrastive methods and a retinal image foundation model in five out of six image-level downstream tasks related to AMD. We find benefits in both a low-data and high-data regime across tasks ranging from AMD stage and type classification to prediction of visual acuity. Due to its modularity, our method can be quickly and cost-effectively tested to establish the potential benefits of including available metadata in contrastive pretraining., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Purpose: Given the similarities between the retinal and coronary microvasculature, the retina holds promising potential to serve as a non-invasive screening tool for coronary artery disease (CAD). We aimed to develop novel inner ellipse-based metrics and discern whether foveal avascular zone (FAZ) alterations can serve as indicators for CAD presence and severity., Methods: Patients admitted to the Department of Cardiology who underwent coronary angiography were included. This resulted in an inclusion of 212 patients, of which 73 had no CAD. During the same visit, 6 × 6-mm (nominal size) fovea-centered optical coherence tomography angiography images of both eyes were acquired. The Gensini score (GS) was utilized to quantify CAD severity. Six known FAZ shape metrics were assessed and three novel biomarkers based on the inner ellipse were defined: absolute inner ellipse difference, Hausdorff distance, and Chamfer distance., Results: Eight out of nine metrics showed significant associations with the GS in the left eye. However, significant differences across three CAD severity groups were only demonstrated by the novel metrics. Utilizing the Chamfer distance, age, and sex, patients with and without CAD could be distinguished with an average area under the curve (AUC) of 0.89 (95% confidence interval [CI], 0.84-0.95). Moreover, three CAD severity groups could be discerned with a macro average AUC of 0.77 (95% CI, 0.72-0.84)., Conclusions: A comprehensive assessment of FAZ shape descriptors was performed, and a strong association with CAD was found. The inner ellipse-based biomarkers especially demonstrated high predictive abilities for CAD presence and severity.

With the approval of the first two substances for the treatment of geographic atrophy (GA) secondary to age-related macular degeneration (AMD), a standardized monitoring of patients treated with complement inhibitors in clinical practice is needed. Optical coherence tomography (OCT) provides high-resolution access to the retinal pigment epithelium (RPE) and neurosensory layers, such as the ellipsoid zone (EZ), which further enhances the understanding of disease progression and therapeutic effects in GA compared to conventional fundus autofluorescence (FAF). In addition, artificial intelligence-based methodology allows the identification and quantification of GA-related pathology on OCT in an objective and standardized manner. The purpose of this study was to comprehensively evaluate automated OCT monitoring for GA compared to reading center-based manual FAF measurements in the largest successful phase 3 clinical trial data of complement inhibitor therapy to date. Automated OCT analysis of RPE loss showed a high and consistent correlation to manual GA measurements on conventional FAF. EZ loss on OCT was generally larger than areas of RPE loss, supporting the hypothesis that EZ loss exceeds underlying RPE loss as a fundamental pathophysiology in GA progression. Automated OCT analysis is well suited to monitor disease progression in GA patients treated in clinical practice and clinical trials., (© 2024. The Author(s).)

The lack of reliable biomarkers makes predicting the conversion from intermediate to neovascular age-related macular degeneration (iAMD, nAMD) a challenging task. We develop a Deep Learning (DL) model to predict the future risk of conversion of an eye from iAMD to nAMD from its current OCT scan. Although eye clinics generate vast amounts of longitudinal OCT scans to monitor AMD progression, only a small subset can be manually labeled for supervised DL. To address this issue, we propose Morph-SSL, a novel Self-supervised Learning (SSL) method for longitudinal data. It uses pairs of unlabelled OCT scans from different visits and involves morphing the scan from the previous visit to the next. The Decoder predicts the transformation for morphing and ensures a smooth feature manifold that can generate intermediate scans between visits through linear interpolation. Next, the Morph-SSL trained features are input to a Classifier which is trained in a supervised manner to model the cumulative probability distribution of the time to conversion with a sigmoidal function. Morph-SSL was trained on unlabelled scans of 399 eyes (3570 visits). The Classifier was evaluated with a five-fold cross-validation on 2418 scans from 343 eyes with clinical labels of the conversion date. The Morph-SSL features achieved an AUC of 0.779 in predicting the conversion to nAMD within the next 6 months, outperforming the same network when trained end-to-end from scratch or pre-trained with popular SSL methods. Automated prediction of the future risk of nAMD onset can enable timely treatment and individualized AMD management.

Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent family of SSL that extract similar representations of two augmented views of an image while pushing away others in the representation space as negatives. However, the state-of-the-art contrastive methods require large batch sizes and augmentations designed for natural images that are impractical for 3D medical images. To address these limitations, we propose a new longitudinal SSL method, 3DTINC, based on non-contrastive learning. It is designed to learn perturbation-invariant features for 3D optical coherence tomography (OCT) volumes, using augmentations specifically designed for OCT. We introduce a new non-contrastive similarity loss term that learns temporal information implicitly from intra-patient scans acquired at different times. Our experiments show that this temporal information is crucial for predicting progression of retinal diseases, such as age-related macular degeneration (AMD). After pretraining with 3DTINC, we evaluated the learned representations and the prognostic models on two large-scale longitudinal datasets of retinal OCTs where we predict the conversion to wet-AMD within a six-month interval. Our results demonstrate that each component of our contributions is crucial for learning meaningful representations useful in predicting disease progression from longitudinal volumetric scans.

Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are the main cause of blindness and the number of patients suffering from retinal diseases is constantly increasing. At the same time, regular imaging using high-resolution modalities in a standardised and reproducible manner generates immense amounts of data that can hardly be processed by human experts. In addition, ophthalmology is constantly experiencing new developments and breakthroughs that require a re-evaluation of patient management in routine clinical practice. AI is able to analyse these volumes of data efficiently and objectively and also provide new insights into disease progression and therapeutic mechanisms by identifying relevant biomarkers. AI can make a significant contribution to screening, classification and prognosis of various retinal diseases and can ultimately be a clinical decision support system, that significantly reduces the burden on both everyday clinical practice and the healthcare system, by making more efficient use of costly and time-consuming resources., Competing Interests: Ursula Schmidt-Erfurth: Scientific Consultant: Apellis, Aviceda, Complementtherapeutix, Heidelberg Engineering, Novartis, ONL, RetInSight, Roche, Topcon Contract Research to the Medical University of Vienna: Apellis, Genentech, KodiakJulia Mai: Consultancy: Apellis, Roche, (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objective: To investigate the localization, distribution, and type of central microaneurysms (MAs) and their relationship with retinal vascular alterations in patients with retinal vein occlusion (RVO)., Methods: In this cross-sectional study, ultra-widefield color fundus photography (UWF-CF), standard and single-capture 65° widefield (WF) optical coherence tomography angiography (OCTA) were performed in consecutive patients with RVO treated at the Department of Ophthalmology and Optometry, Medical University of Vienna. UWF-CF, en face and B-Scans in 6 mm × 6 mm OCTA were examined for detection of MAs. Nonperfusion areas (NPA) and collateral vessels (CV) were evaluated on WF-OCTA, ghost vessels (GV), and tortuous vessels (TV) on UWF-CF., Results: One-hundred-and-twelve patients were included in the study, and data from 59 eyes of 59 patients with disease duration longer than 3 months, good image quality, and without relevant ocular comorbidities were eligible for statistical analysis. Fifty-six of 59 (94.9%) patients were previously treated with anti-vascular endothelial growth factor agents for macular edema, 31 of 59 (52.5%) patients presented with MAs in the central 6 mm and 60 MAs were found in total using multimodal imaging. There was no statistically significant difference in the greatest diameter of fluid-associated versus non-fluid-associated MAs (p = 0.53). Eyes with MAs were associated with CV, TV, and GV (χ 2 -test; p < 0.001, p = 0.0498, and p = 0.001). Median NPA was 27.3 mm 2 (quartiles 1.3-62.8 mm 2 ) in eyes with MAs and 0 mm 2 (quartiles 0-36.2 mm 2 ) in eyes without MAs (Mann-Whitney-U-test; p = 0.018)., Conclusion: MAs were associated with extensive NPA, the presence of CV, GV, and TV. There was no correlation between the diameter of the MA and the adjacent intraretinal fluid in our predominantly pretreated RVO study patients., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

To investigate quantitative associations between AI-assessed disease activity and optical coherence tomography angiography (OCTA)-derived parameters in patients with neovascular age-related macular degeneration (nAMD) undergoing anti-VEGF therapy. OCTA and SD-OCT images obtained from multicenter, randomized study data were evaluated. A deep learning algorithm (RetInSight) was used to detect and quantify macular fluid on SD-OCT. Mixed effects models were applied to evaluate correlations between fluid volumes, macular neovascularization (MNV)-type and OCTA-derived MNV parameters; lesion size (LS) and vessel area (NVA). 230 patients were included. A significant positive correlation was observed between SRF and NVA (estimate = 199.8 nl/mm 2 , p = 0.023), while a non-significant but negative correlation was found between SRF and LS (estimate = - 71.3 nl/mm 2 , p = 0.126). The presence of Type I and Type II MNV was associated with significantly less intraretinal fluid (IRF) compared to Type III MNV (estimate type I:- 52.1 nl, p = 0.019; estimate type II:- 51.7 nl, p = 0.021). A significant correlation was observed between pigment epithelial detachment (PED) and the interaction between NVA and LS (estimate:28.97 nl/mm 2 ; p = 0.012). Residual IRF at week 12 significantly correlated to baseline NVA (estimate:38.1 nl/mm 2 ; p = 0.015) and LS (estimate:- 22.6 nl/mm 2 ; p = 0.012). Fluid in different compartments demonstrated disparate associations with MNV OCTA features. While IRF at baseline was most pronounced in type III MNV, residual IRF was driven by neovascular MNV characteristics. Greater NVA in proportion to LS was associated with higher amounts of SRF and PED. The correlation between these parameters may represent MNV maturation and can be used as a biomarker for resolution of disease activity. AI-based OCT analysis allows for a deeper understanding of neovascular disease in AMD and the potential to adjust therapeutic strategies to optimize outcomes through precision medicine., (© 2024. The Author(s).)

Objectives: This study aims to provide a comprehensive analysis of ocular biometric parameters in pediatric patients with cataracts to optimize surgical outcomes. By evaluating various biometric data, we seek to enhance the decision-making process for intraocular lens (IOL) placement, particularly with advanced technologies like femtosecond lasers. Methods: This retrospective comparative study included pediatric patients with cataracts who underwent ocular biometric measurements and cataract extraction with anterior vitrectomy at the Medical University of Vienna between January 2019 and December 2021. Parameters measured included corneal diameter (CD), axial length (AL), corneal thickness (CT) and flat and steep keratometry (Kf and Ks). The study explored the correlations between these parameters and IOL placement. Results: A total of 136 eyes from 68 pediatric patients were included in the study. Significant positive correlations were found between corneal diameter, age and AL. The mean CD was 11.4 mm, mean AL was 19.5 mm, CT was 581.2 ± 51.8 µm, Kf was 7.76 ± 0.55 mm and Ks 7.41 ± 0.59 mm, respectively. Older pediatric patients with larger corneal diameters and longer ALs were more likely to receive in-the-bag IOL implantation. Conversely, younger patients often required alternative IOL placements or remained aphakic. Our data indicated that over 95% of the study population and all patients aged one year and older had a corneal diameter of 10 mm or larger. Conclusions: Detailed ocular biometric analysis is crucial for optimizing both surgical outcomes and postoperative care in pediatric cataract patients. The positive correlations between CD, age and AL underline the importance of individualized surgical planning tailored to each patient's unique anatomical features. Additionally, our findings suggest that the use of a femtosecond laser is both feasible and safe for pediatric patients aged one year and older, potentially offering enhanced surgical precision and improved outcomes.

Purpose: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images., Design: Post hoc longitudinal image analysis., Participants: Patients with GA due to age-related macular degeneration from 2 prospective randomized phase III clinical trials (OAKS and DERBY)., Methods: Deep learning-based segmentation of RPE loss and PR degeneration, defined as loss of the ellipsoid zone (EZ) layer on OCT, over 24 months., Main Outcome Measures: Change in the mean area of RPE loss and EZ loss over time in the pooled sham arms and the pegcetacoplan monthly (PM)/pegcetacoplan every other month (PEOM) treatment arms., Results: A total of 897 eyes of 897 patients were included. There was a therapeutic reduction of RPE loss growth by 22% and 20% in OAKS and 27% and 21% in DERBY for PM and PEOM compared with sham, respectively, at 24 months. The reduction on the EZ level was significantly higher with 53% and 46% in OAKS and 47% and 46% in DERBY for PM and PEOM compared with sham at 24 months. The baseline EZ-RPE difference had an impact on disease activity and therapeutic response. The therapeutic benefit for RPE loss increased with larger EZ-RPE difference quartiles from 21.9%, 23.1%, and 23.9% to 33.6% for PM versus sham (all P < 0.01) and from 13.6% (P = 0.11), 23.8%, and 23.8% to 20.0% for PEOM versus sham (P < 0.01) in quartiles 1, 2, 3, and 4, respectively, at 24 months. The therapeutic reduction of EZ loss increased from 14.8% (P = 0.09), 33.3%, and 46.6% to 77.8% (P < 0.0001) between PM and sham and from 15.9% (P = 0.08), 33.8%, and 52.0% to 64.9% (P < 0.0001) between PEOM and sham for quartiles 1 to 4 at 24 months., Conclusions: Deep learning-based OCT analysis objectively identifies and quantifies PR and RPE degeneration in GA. Reductions in further EZ loss on OCT are even higher than the effect on RPE loss in phase 3 trials of pegcetacoplan treatment. The EZ-RPE difference has a strong impact on disease progression and therapeutic response. Identification of patients with higher EZ-RPE loss difference may become an important criterion for the management of GA secondary to AMD., Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references., (Copyright © 2024 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Deep learning algorithms have allowed the automation of segmentation for many biomarkers in retinal OCTs, enabling comprehensive clinical research and precise patient monitoring. These segmentation algorithms predominantly rely on supervised training and specialised segmentation networks, such as U-Nets. However, they require segmentation annotations, which are challenging to collect and require specialized expertise. In this paper, we explore leveraging 3D self-supervised learning based on image restoration techniques, that allow to pretrain 3D networks with the aim of improving segmentation performance. We test two methods, based on image restoration and denoising. After pretraining on a large 3D OCT dataset, we evaluate our weights by fine-tuning them on two challenging fluid segmentation datasets utilising different amount of training data. The chosen methods are easy to set up while providing large improvements for fluid segmentation, enabling the reduction of the amount of required annotation or an increase in the performance. Overall, the best results were obtained for denoising-based SSL methods, with higher results on both fluid segmentation datasets as well as faster pretraining durations., Competing Interests: Ursula Schmidt-Erfurth: Genentech (F), Kodiak (F), Novartis (F), Apellis (F,C), RetinSight (F,P). Hrvoje Bogunović: Heidelberg Engineering (F), Apellis (F)., (© 2024 Optica Publishing Group.)

Purpose: To investigate differences in volume and distribution of the main exudative biomarkers across all types and subtypes of macular neovascularization (MNV) using artificial intelligence (AI)., Design: Cross-sectional study., Methods: An AI-based analysis was conducted on 34,528 OCT B-scans consisting of 281 (250 unifocal, 31 multifocal) MNV3, 55 MNV2, and 121 (30 polypoidal, 91 non-polypoidal) MNV1 treatment-naive eyes. Means (SDs), medians and heat maps of cystic intraretinal fluid (IRF), subretinal fluid (SRF), pigment epithelial detachments (PED), and hyperreflective foci (HRF) volumes, as well as retinal thickness (RT) were compared among MNV types and subtypes., Results: MNV3 had the highest mean IRF with 291 (290) nL, RT with 357 (49) µm, and HRF with 80 (70) nL, P ≤ .05. MNV1 showed the greatest mean SRF with 492 (586) nL, whereas MNV3 exhibited the lowest with 218 (382) nL, P ≤ .05. Heat maps showed IRF confined to the center, whereas SRF was scattered in all types. SRF, HRF, and PED were more distributed in the temporal macular half in MNV3. Means of IRF, HRF, and PED were higher in the multifocal than in the unifocal MNV3 with 416 (309) nL,114 (95) nL, and 810 (850) nL, P ≤ .05. Compared to the non-polypoidal subtype, the polypoidal subtype had greater means of SRF with 695 (718) nL, HRF 69 (63) nL, RT 357 (45) µm, and PED 1115 (1170) nL, P ≤ .05., Conclusions: This novel quantitative AI analysis shows that SRF is a biomarker of choroidal origin in MNV1, whereas IRF, HRF, and RT are retinal biomarkers in MNV3. Polypoidal MNV1 and multifocal MNV3 present with higher exudation compared to other subtypes., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate change in retinal layers 18 months after femtosecond laser-assisted cataract surgery (LCS) and manual cataract surgery (MCS) in a representative age-related cataract population using artificial intelligence (AI)-based automated retinal layer segmentation., Methods: This was a prospective, randomized and intraindividual-controlled study including 60 patients at the Medical University of Vienna, Austria. Bilateral same-day LCS and MCS were performed in a randomized sequence. To provide insight into the development of cystoid macular oedema (CME), retinal layer thickness was measured pre-operatively and up to 18 months post-operatively in the central 1 mm, 3 mm and 6 mm., Results: Fifty-six patients completed all follow-up visits. LCS compared to MCS did not impact any of the investigated retinal layers at any follow-up visit (p > 0.05). For the central 1 mm, a significant increase in total retinal thickness (TRT) was seen after 1 week followed by an elevated plateau thereafter. For the 3 mm and 6 mm, TRT increased only after 3 weeks and 6 weeks and decreased again until 18 months. TRT remained significantly increased compared to pre-operative thickness (p < 0.001). Visual acuity remained unaffected by the macular thickening and no case of CME was observed. Inner nuclear layer (INL) and outer nuclear layer (ONL) were the main causative layers for the total TRT increase. Photoreceptors (PR) declined 1 week after surgery but regained pre-operative values 18 months after surgery., Conclusion: Low-energy femtosecond laser pre-treatment did not influence thickness of the retinal layers in any topographic zone compared to manual high fluidic phacoemulsification. TRT did not return to pre-operative values 18 months after surgery. The causative layers for subclinical development of CME were successfully identified., (© 2024 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Purpose: In this study, differences in retinal feature visualization of high-resolution optical coherence tomography (OCT) devices were investigated with different axial resolutions in quantifications of retinal pigment epithelium and photoreceptors (PRs) in intermediate age-related macular degeneration., Methods: Patients were imaged with standard SPECTRALIS HRA + OCT and the investigational High-Res OCT device (both by Heidelberg Engineering, Heidelberg, Germany). Drusen, retinal pigment epithelium, and PR layers were segmented using validated artificial intelligence-based algorithms followed by manual corrections. Thickness and drusen maps were computed for all patients. Loss and thickness measurements were compared between devices, drusen versus nondrusen areas, and early treatment diabetic retinopathy study subfields using mixed-effects models., Results: Thirty-three eyes from 28 patients with intermediate age-related macular degeneration were included. Normalized PR integrity loss was significantly higher with 4.6% for standard OCT compared with 2.5% for High-Res OCT. The central and parafoveal PR integrity loss was larger than the perifoveal loss (P < 0.05). Photoreceptor thickness was increased on High-Res OCT and in nondrusen regions (P < 0.001). Retinal pigment epithelium appeared thicker on standard OCT and above drusen (P < 0.01)., Conclusion: Our study shows that High-Res OCT is able to identify the condition of investigated layers in intermediate age-related macular degeneration with higher precision. This improved in vivo imaging technology might promote our understanding of the pathophysiology and progression of age-related macular degeneration., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Opthalmic Communications Society, Inc.)

Purpose: To evaluate 2-year efficacy, durability, and safety of the bispecific antibody faricimab, which inhibits both angiopoietin-2 and VEGF-A., Design: TENAYA (ClinicalTrials.gov identifier, NCT03823287) and LUCERNE (ClinicalTrials.gov identifier, NCT03823300) were identically designed, randomized, double-masked, active comparator-controlled phase 3 noninferiority trials., Participants: Treatment-naive patients with neovascular age-related macular degeneration (nAMD) 50 years of age or older., Methods: Patients were randomized (1:1) to intravitreal faricimab 6.0 mg up to every 16 weeks (Q16W) or aflibercept 2.0 mg every 8 weeks (Q8W). Faricimab fixed dosing based on protocol-defined disease activity at weeks 20 and 24 up to week 60, followed up to week 108 by a treat-and-extend personalized treatment interval regimen., Main Outcome Measures: Efficacy analyses included change in best-corrected visual acuity (BCVA) from baseline at 2 years (averaged over weeks 104, 108, and 112) and proportion of patients receiving Q16W, every 12 weeks (Q12W), and Q8W dosing at week 112 in the intention-to-treat population. Safety analyses included ocular adverse events (AEs) in the study eye through study end at week 112., Results: Of 1326 patients treated across TENAYA/LUCERNE, 1113 (83.9%) completed treatment (n = 555 faricimab; n = 558 aflibercept). The BCVA change from baseline at 2 years was comparable between faricimab and aflibercept groups in TENAYA (adjusted mean change, +3.7 letters [95% confidence interval (CI), +2.1 to +5.4] and +3.3 letters [95% CI, +1.7 to +4.9], respectively; mean difference, +0.4 letters [95% CI, -1.9 to +2.8]) and LUCERNE (adjusted mean change, +5.0 letters [95% CI, +3.4 to +6.6] and +5.2 letters [95% CI, +3.6 to +6.8], respectively; mean difference, -0.2 letters [95% CI, -2.4 to +2.1]). At week 112 in TENAYA and LUCERNE, 59.0% and 66.9%, respectively, achieved Q16W faricimab dosing, increasing from year 1, and 74.1% and 81.2%, achieved Q12W or longer dosing. Ocular AEs in the study eye were comparable between faricimab and aflibercept groups in TENAYA (55.0% and 56.5% of patients, respectively) and LUCERNE (52.9% and 47.5% of patients, respectively) through week 112., Conclusions: Treat-and-extend faricimab treatment based on nAMD disease activity maintained vision gains through year 2, with most patients achieving extended dosing intervals., Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (Copyright © 2024 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To compare detection rates of microaneurysms (MAs) on high-speed megahertz optical coherence tomography angiography (MHz-OCTA), fluorescein angiography (FA) and colour fundus photography (CF) in patients with diabetic retinopathy (DR)., Methods: For this exploratory cross-sectional study, MHz-OCTA data were acquired with a swept-source OCT prototype (A-scan rate: 1.7 MHz), and FA and CF imaging was performed using Optos® California. MA count was manually evaluated on en face MHz-OCTA/FA/CF images within an extended ETDRS grid. Detectability of MAs visible on FA images was evaluated on corresponding MHz-OCTA and CF images. MA distribution and leakage were correlated with detectability on OCTA and CF imaging., Results: 47 eyes with severe DR (n = 12) and proliferative DR (n = 35) were included. MHz-OCTA and CF imaging detected on average 56% and 36% of MAs, respectively. MHz-OCTA detection rate was significantly higher than CF (p < 0.01). The combination of MHz-OCTA and CF leads to an increased detection rate of 70%. There was no statistically significant association between leakage and MA detectability on OCTA (p = 0.13). For CF, the odds of detecting leaking MAs were significantly lower than non-leaking MAs (p = 0.012). Using MHz-OCTA, detection of MAs outside the ETDRS grid was less likely than MAs located within the ETDRS grid (outer ring, p < 0.01; inner ring, p = 0.028). No statistically significant difference between rings was observed for CF measurements., Conclusions: More MAs were detected on MHz-OCTA than on CF imaging. Detection rate was lower for MAs located outside the macular region with MHz-OCTA and for leaking MAs with CF imaging. Combining both non-invasive modalities can improve MA detection., (© 2023 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic retinopathy and maculopathy. Diabetic macular edema, proliferative diabetic retinopathy, and diabetic macular ischemia pose a threat to visual acuity. Artificial intelligence can play an increasingly more important role in making the diagnosis and the treatment regimen of maculopathies in everyday clinical practice in the future. It can be used to automatically detect and quantify pathological parameters of the retina. The aim is to improve patient care in the clinical routine using so-called clinical decision support systems with personalized treatment algorithms. This review article outlines the current research regarding new biomarkers in diabetic maculopathy using optical coherence tomography (OCT) and OCT angiography (OCT-A)., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

To compare the effectiveness and safety of scleral buckling and pars plana vitrectomy in treating retinal detachment without posterior vitreous detachment. A total of 88 eyes of 83 patients with retinal detachment without prior posterior vitreous detachment were investigated retrospectively. Group A comprised patients who underwent scleral buckling (n = 47) and Group B (n = 36) patients who were treated with pars plana vitrectomy. Anatomical success, postoperative visual acuity, and ocular adverse events were evaluated. The primary and final anatomical success rate showed a nonsignificant difference (p = 0.465 and p = 0.37 respectively). No significant difference was observed in the reoperation rate or development of epiretinal membrane between the groups (p = 0.254 and p = 0.254 respectively). However, scleral buckling resulted in significantly better visual acuity at the last follow-up (0.12 ± 0.23) compared to pars plana vitrectomy (0.37 ± 0.46, p = 0.001). The incidence of cataract progression was also significantly higher in the pars plana vitrectomy group (46%) compared to the scleral buckling group (10%, p < 0.001). Scleral buckling and pars plana vitrectomy show similar success rates in treating retinal detachment without vitreous detachment. However, due to less cataract progression and better visual acuity outcomes, scleral buckling is recommended for these cases. Determining vitreous status before surgery is crucial for optimal outcomes., (© 2024. The Author(s).)

Purpose: To evaluate the postoperative outcome of strabismus surgery performed in children aged 1-6 years by investigating the change of the preoperative angle of deviation (AOD), elevation in adduction, best-corrected visual acuity (BCVA) and refractive error., Methods: Retrospective chart review of 62 children who received strabismus surgery between January 2018 and December 2021 at the Department of Ophthalmology and Optometry of the Medical University of Vienna. Age, sex, type of strabismus, AOD, BCVA, refractive error and visual acuity were evaluated with respect to the postoperative outcome., Results: Mean follow-up was 13.55 ± 11.38 months with a mean age of 3.94 ± 1.97 years (range: 1.0-6.0) at time of surgery. 74.19% of patients (n = 46) had isolated or combined esotropia, 12.90% (n = 8) had isolated or combined exotropia and 12.90% (n = 8) had isolated strabismus sursoadductorius. Mean preoperative AOD of 15.69 ± 16.91°/15.02 ± 14.88° (near/distance) decreased to 4.00 ± 9.18°/4.83 ± 7.32° (near/distance) at final follow-up (p < 0.001). BCVA improved from 0.26 ± 0.26/0.25 ± 0.23 (left/right) to 0.21 ± 0.25/0.20 ± 0.23 (left/right) (p = 0.038). There was no significant change regarding refractive error (p = 0.109) or elevation in adduction (p = 0.212). Success rate which was defined as a residual AOD of less than 10° was 74.19% (n = 46). In 3.23% (n = 2) retreatment was necessary., Conclusion: Strabismus surgery in infants was shown to have a satisfactory outcome with a low retreatment rate. Surgical success rate was not linked to age, sex, type of strabismus or the preoperative parameters AOD, refractive error and visual acuity in this study., (© 2024. The Author(s).)

Purpose: Investigating the sequence of morphological changes preceding outer plexiform layer (OPL) subsidence, a marker preceding geographic atrophy, in intermediate AMD (iAMD) using high-precision artificial intelligence (AI) quantifications on optical coherence tomography imaging., Methods: In this longitudinal observational study, individuals with bilateral iAMD participating in a multicenter clinical trial were screened for OPL subsidence and RPE and outer retinal atrophy. OPL subsidence was segmented on an A-scan basis in optical coherence tomography volumes, obtained 6-monthly with 36 months follow-up. AI-based quantification of photoreceptor (PR) and outer nuclear layer (ONL) thickness, drusen height and choroidal hypertransmission (HT) was performed. Changes were compared between topographic areas of OPL subsidence (AS), drusen (AD), and reference (AR)., Results: Of 280 eyes of 140 individuals, OPL subsidence occurred in 53 eyes from 43 individuals. Thirty-six eyes developed RPE and outer retinal atrophy subsequently. In the cohort of 53 eyes showing OPL subsidence, PR and ONL thicknesses were significantly decreased in AS compared with AD and AR 12 and 18 months before OPL subsidence occurred, respectively (PR: 20 µm vs. 23 µm and 27 µm [P < 0.009]; ONL, 84 µm vs. 94 µm and 98 µm [P < 0.008]). Accelerated thinning of PR (0.6 µm/month; P < 0.001) and ONL (0.8 µm/month; P < 0.001) was observed in AS compared with AD and AR. Concomitant drusen regression and hypertransmission increase at the occurrence of OPL subsidence underline the atrophic progress in areas affected by OPL subsidence., Conclusions: PR and ONL thinning are early subclinical features associated with subsequent OPL subsidence, an indicator of progression toward geographic atrophy. AI algorithms are able to predict and quantify morphological precursors of iAMD conversion and allow personalized risk stratification.

Macular neovascularization type 3 (MNV3) is a multifactorial disease with distinct epidemiological, clinical, pathomorphological and topographical characteristics. This review of the literature discusses the latest experimental and clinical outcomes that could explain the pathogenesis of retinal neovascularization. Although patients with MNV3 are usually older than those with MNV1 or 2, their lesions do not coexist with, precede, or follow other types in the same eye. The regional distribution of MNV3 lesions is characterized as confined to the parafoveal macula without any involvement of the rod-free foveal area. Focal outer retinal atrophy and choroidal non-perfusion are the main structural features that occur prior to the development of retinal neovascularization. Also, histological and experimental studies of MNV3 and other non-neovascular age-related macular degeneration diseases complicated with MNV3-like lesions strongly suggest rod degeneration contributes to the pathogenesis. Therefore, the retinal neovascularization in MNV3 has a different pathogenesis from the choroidal neovascularization in MNV1 and 2 and emerging evidence indicates that choroidal non-prefusion and rod degeneration play a key role in the pathogenesis of MNV3. Accordingly, we suggest a sequence of pathological events that start with choroidal non-perfusion due to advanced age followed by hypoxia of the outer retina at the parafoveal area. This induces a remarkable degeneration of rods that triggers the growth of retinal neovascularization due to the imbalance of the angiogenic factors in the outer retina., (© 2024. The Author(s).)

Aim: To predict antivascular endothelial growth factor (VEGF) treatment requirements, visual acuity and morphological outcomes in neovascular age-related macular degeneration (nAMD) using fluid quantification by artificial intelligence (AI) in a real-world cohort., Methods: Spectral-domain optical coherence tomography data of 158 treatment-naïve patients with nAMD from the Fight Retinal Blindness! registry in Zurich were processed at baseline, and after initial treatment using intravitreal anti-VEGF to predict subsequent 1-year and 4-year outcomes. Intraretinal and subretinal fluid and pigment epithelial detachment volumes were segmented using a deep learning algorithm (Vienna Fluid Monitor, RetInSight, Vienna, Austria). A predictive machine learning model for future treatment requirements and morphological outcomes was built using the computed set of quantitative features., Results: Two hundred and two eyes from 158 patients were evaluated. 107 eyes had a lower median (≤7) and 95 eyes had an upper median (≥8) number of injections in the first year, with a mean accuracy of prediction of 0.77 (95% CI 0.71 to 0.83) area under the curve (AUC). Best-corrected visual acuity at baseline was the most relevant predictive factor determining final visual outcomes after 1 year. Over 4 years, half of the eyes had progressed to macular atrophy (MA) with the model being able to distinguish MA from non-MA eyes with a mean AUC of 0.70 (95% CI 0.61 to 0.79). Prediction for subretinal fibrosis reached an AUC of 0.74 (95% CI 0.63 to 0.81)., Conclusions: The regulatory approved AI-based fluid monitoring allows clinicians to use automated algorithms in prospectively guided patient treatment in AMD. Furthermore, retinal fluid localisation and quantification can predict long-term morphological outcomes., Competing Interests: Competing interests: UMS-E: Scientific consultancy for Genentech, Novartis, Roche, Heidelberg Engineering, Kodiak, RetInSight, Topcon. HB: Grants from Heidelberg Engineering and Apellis. Speaker fees from Bayer, Roche and Apellis. DB: Scientific consultancy, grants and speaker fees for Bayer and Novartis. GSR: Grant from RetInSight.VM, OL, PF, MBN: No financial support or conflicts of interest., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To compare the visibility and accessibility of the outer retina in neovascular age-related macular degeneration (nAMD) between 2 OCT devices., Methods: In this prospective, cross-sectional exploratory study, differences in thickness and loss of individual outer retinal layers in eyes with nAMD and in age-matched healthy eyes between a next-level High-Res OCT device and the conventional SPECTRALIS OCT (both Heidelberg Engineering GmbH, Heidelberg, Germany) were analyzed. Eyes with nAMD and at least 250 nL of retinal fluid, quantified by an approved deep-learning algorithm (Fluid Monitor, RetInSight, Vienna, Austria), fulfilled the inclusion criteria. The outer retinal layers were segmented using automated layer segmentation and were corrected manually. Layer loss and thickness were compared between both devices using a linear mixed-effects model and a paired t test., Results: Nineteen eyes of 17 patients with active nAMD and 17 healthy eyes were included. For nAMD eyes, the thickness of the retinal pigment epithelium (RPE) differed significantly between the devices (25.42 μm [95% CI, 14.24-36.61] and 27.31 μm [95% CI, 16.12-38.50] for high-resolution OCT and conventional OCT, respectively; p = 0.033). Furthermore, a significant difference was found in the mean relative external limiting membrane loss (p = 0.021). However, the thickness of photoreceptors, RPE integrity loss, and photoreceptor integrity loss did not differ significantly between devices in the central 3 mm. In healthy eyes, a significant difference in both RPE and photoreceptor thickness between devices was shown (p < 0.001)., Conclusion: Central RPE thickness was significantly thinner on high-resolution OCT compared with conventional OCT images explained by superior optical separation of the RPE and Bruch's membrane., Competing Interests: Footnotes and Disclosures Gregor Sebastian Reiter received grant support from RetInSight. Hrvoje Bogunovic received grant support from RetInSight and Apellis and as a speaker for Apellis, Roche, and Bayer. Ursula Schmidt-Erfurth served as a scientific consultant for Boehringer, Heidelberg Engineering, Kodiak, Roche (F), and Apellis Pharmaceuticals; received grants from Boehringer (C), Genentech (F), Heidelberg Engineering (F), Janssen, Kodiak (F, C), Novartis (F), Roche (F), RetInSight (F, C), and Apellis Pharmaceuticals (F, C); as a speaker for Apellis, Roche; and received meeting support from Apellis. The remaining authors have no disclosures., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate microvascular intereye differences in diabetic patients with same-stage diabetic retinopathy (DR) in both eyes as assessed using optical coherence tomography angiography (OCTA)., Methods: In this cross-sectional study, fovea-centered swept-source 6 × 6 mm OCTA scans were acquired using a 200 kHz OCTA device. Vessel density (VD) and fractal dimension were calculated on binarized, vessel-segmented images in the superficial capillary plexus (SCP) and deep capillary plexus (DCP). Foveal avascular zone (FAZ) area (FAZA) and perimeter (FAZP) was measured and FAZ circularity (FAZC) calculated. Absolute difference (δabs) and asymmetry index between eyes was assessed and compared across DR stages. Differences of VD, FD, and FAZ parameters between left and right eye were evaluated using linear mixed models., Results: A total of 336 eyes of 168 diabetic patients without DR and with DR stages ranging from mild nonproliferative to proliferative DR were included for analysis. The intereye comparison revealed significantly lower VD in the SCP (estimate [95% CI] = -0.009 [-0.01; -0.006], P < 0.01), as well as a significantly lower FD in the SCP (-0.007 [-0.009; -0.005], P < 0.01) of the left compared to the right eye. FAZC of the left compared to the right eye was lower in eyes without DR, moderate DR, and PDR (P < 0.05). FAZ δabs and asymmetry index were higher in more advanced disease stages (P < 0.05)., Conclusions: OCTA metrics provide important information on the retinal microvasculature in systemic diseases such as DR. Our results reveal a significant intereye difference with lower VD and FD in the SCP as well as higher FAZ impairment of the left compared to the right eye.

Purpose: The subsidence of the outer plexiform layer (OPL) is an important imaging biomarker on optical coherence tomography (OCT) associated with early outer retinal atrophy and a risk factor for progression to geographic atrophy in patients with intermediate age-related macular degeneration (AMD). Deep neural networks (DNNs) for OCT can support automated detection and localization of this biomarker., Methods: The method predicts potential OPL subsidence locations on retinal OCTs. A detection module (DM) infers bounding boxes around subsidences with a likelihood score, and a classification module (CM) assesses subsidence presence at the B-scan level. Overlapping boxes between B-scans are combined and scored by the product of the DM and CM predictions. The volume-wise score is the maximum prediction across all B-scans. One development and one independent external data set were used with 140 and 26 patients with AMD, respectively., Results: The system detected more than 85% of OPL subsidences with less than one false-positive (FP)/scan. The average area under the curve was 0.94 ± 0.03 for volume-level detection. Similar or better performance was achieved on the independent external data set., Conclusions: DNN systems can efficiently perform automated retinal layer subsidence detection in retinal OCT images. In particular, the proposed DNN system detects OPL subsidence with high sensitivity and a very limited number of FP detections., Translational Relevance: DNNs enable objective identification of early signs associated with high risk of progression to the atrophic late stage of AMD, ideally suited for screening and assessing the efficacy of the interventions aiming to slow disease progression.

The approval of complement inhibitory therapeutic agents for the treatment of geographic atrophy (GA) has highlighted the need for reliable and reproducible measurement of disease progression and therapeutic efficacy. Due to its availability and imaging characteristics optical coherence tomography (OCT) is the method of choice. Using OCT analysis based on artificial intelligence (AI), the therapeutic efficacy of pegcetacoplan was demonstrated at the levels of both the retinal pigment epithelium (RPE) and photoreceptors (PR). Cloud-based solutions that enable monitoring of GA are already available., (© 2024. The Author(s).)

Purpose: We introduce a deep learning-based biomarker proposal system for the purpose of accelerating biomarker discovery in age-related macular degeneration (AMD)., Design: Retrospective analysis of a large data set of retinal OCT images., Participants: A total of 3456 adults aged between 51 and 102 years whose OCT images were collected under the PINNACLE project., Methods: Our system proposes candidates for novel AMD imaging biomarkers in OCT. It works by first training a neural network using self-supervised contrastive learning to discover, without any clinical annotations, features relating to both known and unknown AMD biomarkers present in 46 496 retinal OCT images. To interpret the learned biomarkers, we partition the images into 30 subsets, termed clusters, that contain similar features. We conduct 2 parallel 1.5-hour semistructured interviews with 2 independent teams of retinal specialists to assign descriptions in clinical language to each cluster. Descriptions of clusters achieving consensus can potentially inform new biomarker candidates., Main Outcome Measures: We checked if each cluster showed clear features comprehensible to retinal specialists, if they related to AMD, and how many described established biomarkers used in grading systems as opposed to recently proposed or potentially new biomarkers. We also compared their prognostic value for late-stage wet and dry AMD against an established clinical grading system and a demographic baseline model., Results: Overall, both teams independently identified clearly distinct characteristics in 27 of 30 clusters, of which 23 were related to AMD. Seven were recognized as known biomarkers used in established grading systems, and 16 depicted biomarker combinations or subtypes that are either not yet used in grading systems, were only recently proposed, or were unknown. Clusters separated incomplete from complete retinal atrophy, intraretinal from subretinal fluid, and thick from thin choroids, and, in simulation, outperformed clinically used grading systems in prognostic value., Conclusions: Using self-supervised deep learning, we were able to automatically propose AMD biomarkers going beyond the set used in clinically established grading systems. Without any clinical annotations, contrastive learning discovered subtle differences between fine-grained biomarkers. Ultimately, we envision that equipping clinicians with discovery-oriented deep learning tools can accelerate the discovery of novel prognostic biomarkers., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2024 by the American Academy of Ophthalmology.)

Geographic atrophy (GA) is an advanced and irreversible form of age-related macular degeneration (AMD). Chronic low grade inflammation is thought to act as an initiator of this degenerative process, resulting in loss of photoreceptors (PRs), retinal pigment epithelium (RPE) and the underlying choriocapillaris. This review examined the challenges of clinical trials to date which have sought to treat GA, with particular reference to the successful outcome of C3 complement inhibition. Currently, optical coherence tomography (OCT) seems to be the most suitable method to detect GA and monitor the effect of treatment. In addition, the merits of using novel anatomical endpoints in detecting GA expansion are discussed. Although best-corrected visual acuity is commonly used to monitor disease in GA, other tests to determine visual function are explored. Although not widely available, microperimetry enables quantification of retinal sensitivity (RS) and macular fixation behaviour related to fundus characteristics. There is a spatial correlation between OCT/fundus autofluorescence evaluation of PR damage outside the area of RPE loss and RS on microperimetry, showing important associations with visual function. Standardisation of testing by microperimetry is necessary to enable this modality to detect AMD progression. Artificial intelligence (AI) analysis has shown PR layers integrity precedes and exceeds GA loss. Loss of the ellipsoid zone has been recognised as a primary outcome parameter in therapeutic trials for GA. The integrity of the PR layers imaged by OCT at baseline has been shown to be an important prognostic indicator. AI has the potential to be invaluable in personalising care and justifying treatment intervention., Competing Interests: Competing interests: SV: consultant to AbbVie, Apellis, Bayer, Novartis, Hoffman La Roche and Zeiss. AL: consultant to Allergan, Bayer, Beyeonics, ForSight Labs, Notal Vision, Novartis and Roche. LO’T: consultant to Novartis and Bayer. UMS-E: contract research for Roche, Novartis, Apellis, RetInSight. Scientific consultancy for Boehringer, AbbVie, Novartis, Roche, RetInSight, Heidelberg Engineering and Stealth Bio Therapeutics. DZ: Consultant to AbbVie, Bayer, Novartis and Hoffman La Roche. UC: consultant to Apellis, Boehringer Ingelheim, Iveric and Hoffman La Roche., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

In this retrospective longitudinal observational study, data from one site of the Fight Retinal Blindness! Registry (University of Zurich, Switzerland) was used to investigate the quantity and distribution of recurrent fluid in neovascular age-related macular degeneration (nAMD). Study eye eligibility required treatment-naïve nAMD, receiving at least three anti-vascular endothelial growth factor injections, followed by a treatment discontinuation of at least six months and subsequence fluid recurrence. To quantify fluid, a regulatory approved deep learning algorithm (Vienna Fluid Monitor, RetInSight, Vienna, Austria) was used. Fifty-six eyes of 56 patients with a mean age of 76.29 ± 6.58 years at baseline fulfilled the inclusion criteria. From baseline to the end of the first treatment-free interval, SRF volume had decreased significantly (58.0 nl (IQR 10-257 nl) to 8.73 nl (IQR 1-100 nl), p < 0.01). The quantitative increase in IRF volume from baseline to the end of the first treatment-free interval was not statistically significant (1.35 nl (IQR 0-107 nl) to 5.18 nl (IQR 0-24 nl), p = 0.13). PED also did not reach statistical significance (p = 0.71). At the end of the second treatment discontinuation there was quantitatively more IRF (17.3 nl) than SRF (3.74 nl). In conclusion, discontinuation of treatment with anti-VEGF therapy may change the fluid pattern in nAMD., Competing Interests: Schmidt-Erfurth: Grants: Boehringer, Genentech, Heidelberg Engineering, Janssen, Kodiak, Novartis, Roche, RetInSight, Apellis Pharmaceuticals; Consulting fees: Boehringer, Heidelberg Engineering, Kodiak, Roche, Apellis Pharmaceuticals; Honoraria for lectures: Apellis, Roche; Support for attending meetings: Apellis. Reiter: Grants: RetInSight; Consulting fees: Bayer. Bogunovic: Grants: RetInsSight. Barthelmes: Scientific Consultant: Alcon, Novartis, Bayer; Lecture fees: Bayer. Prenner: none. Fuchs: none. Coulibaly: none. Leingang: none., (© 2024 The Authors. Published by Elsevier Ltd.)

Artificial intelligence (AI) has emerged as a transformative technology across various fields, and its applications in the medical domain, particularly in ophthalmology, has gained significant attention. The vast amount of high-resolution image data, such as optical coherence tomography (OCT) images, has been a driving force behind AI growth in this field. Age-related macular degeneration (AMD) is one of the leading causes for blindness in the world, affecting approximately 196 million people worldwide in 2020. Multimodal imaging has been for a long time the gold standard for diagnosing patients with AMD, however, currently treatment and follow-up in routine disease management are mainly driven by OCT imaging. AI-based algorithms have by their precision, reproducibility and speed, the potential to reliably quantify biomarkers, predict disease progression and assist treatment decisions in clinical routine as well as academic studies. This review paper aims to provide a summary of the current state of AI in AMD, focusing on its applications, challenges, and prospects., (© 2024. The Author(s).)

Automated lesion detection in retinal optical coherence tomography (OCT) scans has shown promise for several clinical applications, including diagnosis, monitoring and guidance of treatment decisions. However, segmentation models still struggle to achieve the desired results for some complex lesions or datasets that commonly occur in real-world, e.g. due to variability of lesion phenotypes, image quality or disease appearance. While several techniques have been proposed to improve them, one line of research that has not yet been investigated is the incorporation of additional semantic context through the application of anomaly detection models. In this study we experimentally show that incorporating weak anomaly labels to standard segmentation models consistently improves lesion segmentation results. This can be done relatively easy by detecting anomalies with a separate model and then adding these output masks as an extra class for training the segmentation model. This provides additional semantic context without requiring extra manual labels. We empirically validated this strategy using two in-house and two publicly available retinal OCT datasets for multiple lesion targets, demonstrating the potential of this generic anomaly guided segmentation approach to be used as an extra tool for improving lesion detection models., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Hrvoje Bogunovic reports financial support was provided by FWF Austrian Science Fund (grant number FG 9-N). Hrvoje Bogunovic reports a relationship with Heidelberg Engineering Inc that includes: funding grants. Ursula Schmidt-Erfurth reports a relationship with Genentech, Novartis, Roche, Heidelberg Engineering, Kodiak, RetInSight that includes: consulting or advisory. Hrvoje Bogunovic is editorial board member of the Medical Image Analysis journal., (Copyright © 2024. Published by Elsevier B.V.)

The use of multimodal imaging has led to significant improvements in the diagnosis and treatment of many diseases. Similar to clinical practice, some works have demonstrated the benefits of multimodal fusion for automatic segmentation and classification using deep learning-based methods. However, current segmentation methods are limited to fusion of modalities with the same dimensionality (e.g., 3D + 3D, 2D + 2D), which is not always possible, and the fusion strategies implemented by classification methods are incompatible with localization tasks. In this work, we propose a novel deep learning-based framework for the fusion of multimodal data with heterogeneous dimensionality (e.g., 3D + 2D) that is compatible with localization tasks. The proposed framework extracts the features of the different modalities and projects them into the common feature subspace. The projected features are then fused and further processed to obtain the final prediction. The framework was validated on the following tasks: segmentation of geographic atrophy (GA), a late-stage manifestation of age-related macular degeneration, and segmentation of retinal blood vessels (RBV) in multimodal retinal imaging. Our results show that the proposed method outperforms the state-of-the-art monomodal methods on GA and RBV segmentation by up to 3.10% and 4.64% Dice, respectively.

Background/objectives: To analyse short-term changes of mean photoreceptor thickness (PRT) on the ETDRS-grid after vitrectomy and membrane peeling in patients with epiretinal membrane (ERM)., Subjects/methods: Forty-eight patients with idiopathic ERM were included in this prospective study. Study examinations comprised best-corrected visual acuity (BCVA) and optical coherence tomography (OCT) before surgery, 1 week (W1), 1 month (M1) and 3 months (M3) after surgery. Mean PRT was assessed using an automated algorithm and correlated with BCVA and central retinal thickness (CRT)., Results: Regarding PRT changes of the study eye in comparison to baseline values, a significant decrease at W1 in the 1 mm, 3 mm and 6 mm area (all p-values < 0.001), at M1 (p = 0.009) and M3 (p = 0.019) in the central 1 mm area, a significant increase at M3 in the 6 mm area (p < 0.001), but no significant change at M1 in the 3 mm and 6 mm area and M3 in the 3 mm area (all p-values > 0.05) were observed. BCVA increased significantly from baseline to M3 (0.3LogMAR-0.15LogMAR, Snellen equivalent = 20/40-20/28 respectively; p < 0.001). There was no correlation between baseline PRT and BCVA at any visit after surgery, nor between PRT and BCVA at any visit (all p-values > 0.05). Decrease in PRT in the 1 mm (p < 0.001), 3 mm (p = 0.013) and 6 mm (p = 0.034) area after one week correlated with the increase in CRT (449.9 µm-462.2 µm)., Conclusions: Although the photoreceptor layer is morphologically affected by ERMs and after their surgical removal, it is not correlated to BCVA. Thus, patients with photoreceptor layer alterations due to ERM may still benefit from surgery and achieve good functional rehabilitation thereafter., (© 2023. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)