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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: 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: Growing interest in microperimetry (MP) or fundus-controlled perimetry (FCP) as targeted psychometric testing method in geographic atrophy (GA) is warranted due to the disease subclinical/extra-foveal 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 GA patients., Design: Prospective reliability study METHODS: Patients with GA underwent consecutive testing on CenterVue (iCare) MAIA and NIDEK MP3 devices. Obtained PWS measurements were spatially co-registered to an optical coherence tomography (OCT) 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 (HRF) 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 (CoR). Furthermore, the inter-device correlation, the repeatability of scotoma point detection as well as any potential effects on fixation stability were assessed., Results: 900 stimuli per device from twenty 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=0.002; MP3: p<0.001). Higher CoR for stimuli in areas presenting RPE loss (±10.99 vs ±5.34) or HRF (±9.21 vs ±6.25) could only be detected on MP3 examinations (p<0.001 and p=0.01, respectively). An excellent intra-device correlation (MAIA: 0.94[0.93-0.95] MP3: 0.94[0.94-0.95]) and a good mean inter-device correlation (0.84[0.53-0.92]) could be 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 microperimetry testing as functional study endpoint., Competing Interests: Conflicts of interest none, (Copyright © 2024. Published by Elsevier Inc.)

Purpose: The progression of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) 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 the investigation of the value and difference in predictive power between ophthalmologists and artificial intelligence (AI) to reliably assess 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 selecting the potentially faster growing lesions from two eyes based on fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). A deep learning algorithm predicted progression solely on the baseline OCT (Spectralis, Heidelberg Engineering, Germany)., Main Outcome Measures: Accuracy, weighted kappa (κ), and concordance index (c-index) between the prediction made by ophthalmology specialists, ophthalmology residents and the AI., Results: A total of 134 eyes of 134 patients from a phase II clinical trial were included, among those 53 were from the sham arm and 81 from untreated fellow eyes. 2880 gradings were performed by four ophthalmologists. Human experts reached an accuracy of 0.37, 0.43, 0.41 and a κ of 0.06, 0.16, 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 a κ of 0.23 on the first task, and a 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 treatments becoming available. Human gradings improved with the availability of OCT. However, automated AI performed better than ophthalmologists in several comparisons. AI-supported decisions improve clinical precision, access to timely care for the community, and socioeconomic feasibility in the management of the leading cause for irreversible vision loss., (Copyright © 2024. Published by Elsevier 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.)

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).)

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.)

Purpose: To evaluate the surgically induced astigmatism over a 6-month follow-up period in patients who underwent scleral IOL fixation using an acrylic single-piece IOL with special haptics designed for sutureless scleral fixation., Methods: We conducted a prospective longitudinal study at a single site with a single surgeon. We included patients who received transscleral IOL implantation following the Carlevale technique and were followed up post-operatively for 24 weeks. We measured the patient's refraction at baseline, week 12 and week 24 using the best corrected visual acuity at 4 m (EDTRS chart). We performed corneal tomography at every visit using an anterior segment optical coherence tomography (AS-OCT). We evaluated surgically induced astigmatism (SIA) and refraction during each follow-up visit and compared them to baseline. We then assessed changes in SIA over time., Results: In total, 27 eyes of 27 patients consisting of 16 female and 11 male individuals were evaluated. The mean patient age was 71 ± 11.7 years, mean axial length was 24.30 ± 1.47 mm (range: 21.4-27.23) and mean white-to-white distance was 12.07 ± 0.40 mm (range: 11.4-12.7). The mean SIA decreased from 1.78 ± 0.96D at week 1 significantly to 0.80 ± 0.55D at week 12 (p < 0.001) and then stayed unchanged around 0.82 ± 0.72D at week 24 (p = 1.0)., Conclusions: The scleral fixated Carlevale IOL and its implantation procedure were found to result in a predictable SIA of <1D after 24 weeks. However, the axis orientation of the SIA appeared to be random, making it unsuitable for implementation in toric IOL calculations., (© 2024 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

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.)

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 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: 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.

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: 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.

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).)

Purpose: To assess retinal function in areas of presumed fibrosis due to neovascular age-related macular degeneration (nAMD), using multimodal imaging and structure-function correlation. Design: Cross-sectional observational study. Methods: 30 eyes of 30 consecutive patients with nAMD with a minimum history of one year of anti-vascular endothelial growth factor therapy were included. Each patient underwent microperimetry (MP), color fundus photography (CFP), standard spectral-domain-based OCT (SD-OCT), and polarization sensitive-OCT (PS-OCT) imaging. PS-OCT technology can depict retinal fibrosis based on its birefringence. CFP, SD-OCT, and PS-OCT were evaluated independently for the presence of fibrosis at the corresponding MP stimuli locations. MP results and morphologic findings in CFP, SD-OCT, and PS-OCT were co-registered and analyzed using mixed linear models. Results: In total, 1350 MP locations were evaluated to assess the functional impact of fibrosis according to a standardized protocol. The estimated means of retinal areas with signs of fibrosis were 12.60 db (95% confidence interval: 10.44-14.76) in CFP, 11.60 db (95% COI: 8.84-14.36) in OCT, and 11.02 db (95% COI 8.10-13.94) in PS-OCT. Areas evaluated as subretinal fibrosis in three (7.2 db) or two (10.1 db) modalities were significantly correlated with a lower retinal sensitivity than a subretinal fibrosis observed in only one (15.3 db) or none (23.3 db) modality ( p < 0.001). Conclusions: CFP, SD-OCT and PS-OCT are all suited to detect areas of reduced retinal sensitivity related to fibrosis, however, a multimodal imaging approach provides higher accuracy in the identification of areas with low sensitivity in MP (i.e., impaired retinal function), and thereby improves the detection rate of subretinal fibrosis in nAMD.

Objective: To identify the individual progression of geographic atrophy (GA) lesions from baseline OCT images of patients in routine clinical care., Design: Clinical evaluation of a deep learning-based algorithm., Subjects: One hundred eighty-four eyes of 100 consecutively enrolled patients., Methods: OCT and fundus autofluorescence (FAF) images (both Spectralis, Heidelberg Engineering) of patients with GA secondary to age-related macular degeneration in routine clinical care were used for model validation. Fundus autofluorescence images were annotated manually by delineating the GA area by certified readers of the Vienna Reading Center. The annotated FAF images were anatomically registered in an automated manner to the corresponding OCT scans, resulting in 2-dimensional en face OCT annotations, which were taken as a reference for the model performance. A deep learning-based method for modeling the GA lesion growth over time from a single baseline OCT was evaluated. In addition, the ability of the algorithm to identify fast progressors for the top 10%, 15%, and 20% of GA growth rates was analyzed., Main Outcome Measures: Dice similarity coefficient (DSC) and mean absolute error (MAE) between manual and predicted GA growth., Results: The deep learning-based tool was able to reliably identify disease activity in GA using a standard OCT image taken at a single baseline time point. The mean DSC for the total GA region increased for the first 2 years of prediction (0.80-0.82). With increasing time intervals beyond 3 years, the DSC decreased slightly to a mean of 0.70. The MAE was low over the first year and with advancing time slowly increased, with mean values ranging from 0.25 mm to 0.69 mm for the total GA region prediction. The model achieved an area under the curve of 0.81, 0.79, and 0.77 for the identification of the top 10%, 15%, and 20% growth rates, respectively., Conclusions: The proposed algorithm is capable of fully automated GA lesion growth prediction from a single baseline OCT in a time-continuous fashion in the form of en face maps. The results are a promising step toward clinical decision support tools for therapeutic dosing and guidance of patient management because the first treatment for GA has recently become available., 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.)

Microperimetry (MP) is a psychometric examination combining retinal imaging and functional sensitivity testing with an increasing importance due to its potential use as clinical study outcome. We investigated the repeatability of pointwise retinal sensitivity (PWS) on the most advanced commercially available MP devices under their standard setting in a healthy aging population. Two successive MP examinations on both MP-3 (NIDEK CO., Ltd., Gamagori, Japan) and MAIA (CenterVue S.p.A. (iCare), Padova, Italy) were performed on healthy aging subjects in a randomized order. PWS repeatability was analysed for different macular regions and age groups using Bland-Altmann coefficients of repeatability (CoR). A total of 3600 stimuli from 20 healthy individuals with a mean age of 70 (11) years were included. Mean CoR in dB were ±4.61 for MAIA and ±4.55 for MP-3 examinations. A lower repeatability (p=0.005) was detected in the central millimetre on MAIA examinations. Higher subject age was associated with a lower repeatability of PWS on both devices (both p=0.003). Intra-device correlation was good (MAIA: 0.79 [0.76-0.81]; MP-3: 0.72 [0.68-0.76]) whereas a moderate mean inter-device correlation (0.6 [0.55-0.65]) could be detected. In conclusion, older subjects and the foveal region are associated with a worse pointwise repeatability., (© 2024. The Author(s).)

Objective: Treatment decisions in neovascular age-related macular degeneration (nAMD) are mainly based on subjective evaluation of OCT. The purpose of this cross-sectional study was to provide a comparison of qualitative and quantitative differences between OCT devices in a systematic manner., Design: Prospective, cross-sectional study., Subjects: One hundred sixty OCT volumes, 40 eyes of 40 patients with nAMD., Methods: Patients from clinical practice were imaged with 4 different OCT devices during one visit: (1) Spectralis Heidelberg; (2) Cirrus; (3) Topcon Maestro2; and (4) Topcon Triton. Intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED) were manually annotated in all cubes by trained human experts to establish fluid measurements based on expert-reader annotations. Intraretinal fluid, SRF, and PED volume were quantified in nanoliters (nL). Bland-Altman plots were created to analyze the agreement of measurements in the central 1 and 6 mm. The Friedman test was performed to test for significant differences in the central 1, 3, and 6 mm., Main Outcome Measures: Intraretinal fluid, SRF, and PED volume., Results: In the central 6 mm, there was a trend toward higher IRF and PED volumes in Spectralis images compared with the other devices and no differences in SRF volume. In the central 1 mm, the standard deviation of the differences ranged from ± 3 nL to ± 6 nL for IRF, from ± 3 nL to ± 4 nL for SRF, and from ± 7 nL to ± 10 nL for PED in all pairwise comparisons. Manually annotated IRF and SRF volumes showed no significant differences in the central 1 mm., Conclusions: Fluid volume quantification achieved excellent reliability in all 3 retinal compartments on images obtained from 4 OCT devices, particularly for clinically relevant IRF and SRF values. Although fluid volume quantification is reliable in all 4 OCT devices, switching OCT devices might lead to deviating fluid volume measurements with higher agreement in the central 1 mm compared with the central 6 mm, with highest agreement for SRF volume in the central 1 mm. Understanding device-dependent differences is essential for expanding the interpretation and implementation of pixel-wise fluid volume measurements in clinical practice and in clinical trials., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2023 by the American Academy of Ophthalmology.)

Objectives: To evaluate the quantitative impact of drusen and hyperreflective foci (HRF) volumes on mesopic retinal sensitivity in non-exudative age-related macular degeneration (AMD)., Methods: In a standardized follow-up scheme of every three months, retinal sensitivity of patients with early or intermediate AMD was assessed by microperimetry using a custom pattern of 45 stimuli (Nidek MP-3, Gamagori, Japan). Eyes were consecutively scanned using Spectralis SD-OCT (20° × 20°, 1024 × 97 × 496). Fundus photographs obtained by the MP-3 allowed to map the stimuli locations onto the corresponding OCT scans. The volume and mean thickness of drusen and HRF within a circle of 240 µm centred at each stimulus point was determined using automated AI-based image segmentation algorithms., Results: 8055 individual stimuli from 179 visits from 51 eyes of 35 consecutive patients were matched with the respective OCT images in a point-to-point manner. The patients mean age was 76.85 ± 6.6 years. Mean retinal sensitivity at baseline was 25.7 dB. 73.47% of all MP-spots covered drusen area and 2.02% of MP-spots covered HRF. A negative association between retinal sensitivity and the volume of underlying drusen (p < 0.001, Estimate -0.991 db/µm 3 ) and HRF volume (p = 0.002, Estimate -5.230 db/µm 3 ) was found. During observation time, no eye showed conversion to advanced AMD., Conclusion: A direct correlation between drusen and lower sensitivity of the overlying photoreceptors can be observed. For HRF, a small but significant correlation was shown, which is compromised by their small size. Biomarker quantification using AI-methods allows to determine the impact of sub-clinical features in the progression of AMD., (© 2023. The Author(s).)

Real-world retinal optical coherence tomography (OCT) scans are available in abundance in primary and secondary eye care centres. They contain a wealth of information to be analyzed in retrospective studies. The associated electronic health records alone are often not enough to generate a high-quality dataset for clinical, statistical, and machine learning analysis. We have developed a deep learning-based age-related macular degeneration (AMD) stage classifier, to efficiently identify the first onset of early/intermediate (iAMD), atrophic (GA), and neovascular (nAMD) stage of AMD in retrospective data. We trained a two-stage convolutional neural network to classify macula-centered 3D volumes from Topcon OCT images into 4 classes: Normal, iAMD, GA and nAMD. In the first stage, a 2D ResNet50 is trained to identify the disease categories on the individual OCT B-scans while in the second stage, four smaller models (ResNets) use the concatenated B-scan-wise output from the first stage to classify the entire OCT volume. Classification uncertainty estimates are generated with Monte-Carlo dropout at inference time. The model was trained on a real-world OCT dataset, 3765 scans of 1849 eyes, and extensively evaluated, where it reached an average ROC-AUC of 0.94 in a real-world test set., (© 2023. The Author(s).)

With the prospect of available therapy for geographic atrophy in the near future and consequently increasing patient numbers, appropriate management strategies for the clinical practice are needed. Optical coherence tomography (OCT) as well as automated OCT analysis using artificial intelligence algorithms provide optimal conditions for assessing disease activity as well as the treatment response for geographic atrophy through a rapid, precise and resource-efficient evaluation., (© 2023. The Author(s).)

Purpose: To investigate the progression of geographic atrophy secondary to nonneovascular age-related macular degeneration in early and later stage lesions using artificial intelligence-based precision tools., Design: Retrospective analysis of an observational cohort study., Subjects: Seventy-four eyes of 49 patients with ≥ 1 complete retinal pigment epithelial and outer retinal atrophy (cRORA) lesion secondary to age-related macular degeneration were included. Patients were divided between recently developed cRORA and lesions with advanced disease status., Methods: Patients were prospectively imaged by spectral-domain OCT volume scans. The study period encompassed 18 months with scheduled visits every 6 months. Growth rates of recent cRORA-converted lesions were compared with lesions in an advanced disease status using mixed effect models., Main Outcome Measures: The progression of retinal pigment epithelial loss (RPEL) was considered the primary end point. Secondary end points consisted of external limiting membrane disruption and ellipsoid zone loss. These pathognomonic imaging biomarkers were quantified using validated deep-learning algorithms. Further, the ellipsoid zone/RPEL ratio was analyzed in both study cohorts., Results: Mean (95% confidence interval [CI]) square root progression of recently converted lesions was 79.68 (95% CI, -77.14 to 236.49), 68.22 (95% CI, -101.21 to 237.65), and 84.825 (95% CI, -124.82 to 294.47) mm/half year for RPEL, external limiting membrane loss, and ellipsoid zone loss respectively. Mean square root progression of advanced lesions was 131.74 (95% CI, -22.57 to 286.05), 129.96 (95% CI, -36.67 to 296.59), and 116.84 (95% CI, -90.56 to 324.3) mm/half year for RPEL, external limiting membrane loss, and ellipsoid zone loss, respectively. RPEL (P = 0.038) and external limiting membrane disruption (P = 0.026) progression showed significant differences between the 2 study cohorts. Further recent converters had significantly (P < 0.001) higher ellipsoid zone/RPEL ratios at all time points compared with patients in an advanced disease status (1.71 95% CI, 1.12-2.28 vs. 1.14; 95% CI, 0.56-1.71)., Conclusion: Early cRORA lesions have slower growth rates in comparison to atrophic lesions in advanced disease stages. Differences in growth dynamics may play a crucial role in understanding the pathophysiology of nonneovascular age-related macular degeneration and for the interpretation of clinical trials in geographic atrophy. Individual disease monitoring using artificial intelligence-based quantification paves the way toward optimized geographic atrophy management., Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials discussed in this article., (Copyright © 2023 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: Previous studies have identified a link between optical coherence tomography (OCT)-derived and OCT angiography (OCTA)-based parameters in patients with neovascular AMD (nAMD); the latter may serve as direct biomarkers for macular neovascularization (MNV) activity. The aim of this study was to assess the individual influence of retinal thickness (RT) as well as intra- and sub-retinal fluid (IRF, SRF) presence on the treatment response over time as assessed by previously identified OCTA-derived MNV vascular parameters., Methods: During the first 3 months of anti-VEGF therapy patients were prospectively followed. RT, SRF and IRF were determined from SSOCT/A (PlexElite, Zeiss) images and using the semi-automated AngioTool software, vessel area (VA), total vessel length (TVL), total number of junctions (TNJ), junction density (JD), vessel density (VD) as well as MNV area were exported. IRF and SRF were identified manually on OCT volume scans .The associations between RT, IRF, and SRF and SSOCTA vascular parameters were analyzed using linear mixed models., Results: 31 eyes of 31 patients with treatment-naïve and OCTA-positive nAMD MNV were included in this analysis. VA, TVL, TNJ, and MNV area show a statistically significant change over time in response to anti-VEGF treatment, even after correcting for the presence of SRF, IRF, or RT (all p  < 0.05). This is not the case for JD and VD (both p  > 0.05)., Conclusions: OCTA-based parameters VA, TVL, TNJ, and MNVarea show a strong response to anti-VEGF therapy over time, independent of the presence of IRF, SRF or RT. We conclude that the above listed OCTA parameters could contribute to our understanding of MNV biology and to guide individualized treatment in the future., Trial Registry: The authors confirm that all ongoing and related trials are registered. ClinicalTrials.gov Number: NCT02521142.

In patients with age-related macular degeneration (AMD), the risk of progression to late stages is highly heterogeneous, and the prognostic imaging biomarkers remain unclear. We propose a deep survival model to predict the progression towards the late atrophic stage of AMD. The model combines the advantages of survival modelling, accounting for time-to-event and censoring, and the advantages of deep learning, generating prediction from raw 3D OCT scans, without the need for extracting a predefined set of quantitative biomarkers. We demonstrate, in an extensive set of evaluations, based on two large longitudinal datasets with 231 eyes from 121 patients for internal evaluation, and 280 eyes from 140 patients for the external evaluation, that this model improves the risk estimation performance over standard deep learning classification models., Competing Interests: Gregor Reiter: RetInSight (F). Robyn H. Guymer: Bayer (C), Novartis (C), Roche Genentech (C), Apellis (C). Ursula Schmidt-Erfurth: Genentech (F), Kodiak (F), Novartis (F), Apellis (F,C), RetinSight (F,P). Hrvoje Bogunović: Heidelberg Engineering (F), Apellis (F)., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

Introduction: In neovascular age-related macular degeneration (nAMD) the exact amount of fluid and its location on optical coherence tomography (OCT) have been defined as crucial biomarkers for disease activity and therapeutic decisions. Yet in the absence of quantitative evaluation tools, real-world care outcomes are disappointing. Artificial intelligence (AI) offers a practical option for clinicians to enhance point-of-care management by analysing OCT volumes in a short time. In this protocol we present the prospective implementation of an AI-algorithm providing automated real-time fluid quantifications in a clinical real-world setting., Methods: This is a prospective, multicentre, randomized (1:1) and double masked phase III clinical trial. Two-hundred-ninety patients with active nAMD will be randomized between a study arm using AI-supported fluid quantifications and another arm using conventional qualitative assessments, i.e. state-of-the-art disease management. The primary outcome is defined as the mean number of injections over 1 year. Change in BCVA is defined as a secondary outcome., Discussion: Automated measurement of fluid volumes in all retinal compartments such as intraretinal fluid (IRF), and subretinal fluid (SRF) will serve as an objective tool for clinical investigators on which to base retreatment decisions. Compared to qualitative fluid assessment, retreatment decisions will be plausible and less prone to error or large variability. The underlying hypothesis is that fluid should be treated, while residual persistent or stable amounts of fluid may not benefit from further therapy. Reducing injection numbers without diminishing the visual benefit will increase overall patient safety and relieve the burden for healthcare providers., Trial-Registration: EudraCT-Number: 2019-003133-42., (© 2022. The Author(s).)

Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials., (© 2023. The Author(s).)

Objectives: To assess the therapeutic response to brolucizumab and aflibercept by deep learning/OCT-based analysis of macular fluid volumes in neovascular age-related macular degeneration., Methods: In this post-hoc analysis of two phase III, randomised, multi-centre studies (HAWK/HARRIER), 1078 and 739 treatment-naive eyes receiving brolucizumab or aflibercept according to protocol-specified criteria in HAWK and HARRIER, respectively, were included. Macular fluid on 41,840 OCT scans was localised and quantified using a validated deep learning-based algorithm. Volumes of intraretinal fluid (IRF), subretinal fluid (SRF), pigment epithelial detachment (PED) for all central macular areas (1, 3 and 6 mm) in nanolitres (nL) and best corrected visual acuity (BCVA) change in ETDRS letters were associated using mixed models for repeated measures., Results: Baseline IRF volumes decreased by >92% following the first intravitreal injection and consistently remained low during follow-up. Baseline SRF volumes decreased by >74% following the first injection, while PED volume resolved by 68-79% of its baseline volume. Resolution of SRF and PED was dependent on the substance and regimen used. Larger residual post-loading IRF, SRF and PED volumes were all independently associated with progressive vision loss during maintenance, where the differences in mean BCVA change between high and low fluid volume subgroups for IRF, SRF and PED were 3.4 letters (p < 0.0001), 1.7 letters (p < 0.001) and 2.5 letters (p < 0.0001), respectively., Conclusions: Deep-learning methods allow an accurate assessment of substance and regimen efficacy. Irrespectively, all fluid compartments were found to be important markers of disease activity and were relevant for visual outcomes., (© 2022. The Author(s).)

Purpose: To identify correlations between the vascular characteristics of macular neovascularization (MNV) obtained by optical coherence tomography angiography (OCTA) and distinct retinal fluid volumes in neovascular age-related macular degeneration (nAMD)., Methods: In this prospective interventional study, 54 patients with treatment-naïve type 1 or 2 nAMD were included and treated with intravitreal aflibercept. At baseline and month 1, each patient underwent a SD-OCT volume scan and volumetric flow scan using a swept-source OCTA. A deep learning algorithm was used to automatically detect and quantify fluid in OCT scans. Angio Tool, a National Cancer Institute algorithm, was used to skeletonize MNV properties and quantify lesion size (LS), vessel area (VA), vessel density (VD), total number of endpoints (TNE), total number of junctions (TNJ), junction density (JD), total vessel length (TVL), average vessel length (AVL) and mean-e-lacunarity (MEL). Subsequently, linear regression models were used to investigate a correlation between OCTA parameters and fluid quantifications., Results: The median amount of fluid within the central 6-mm EDTRS ring was 173.7 nl at baseline, consisting of 156.6 nl of subretinal fluid (SRF) and 2.3 nl of intraretinal fluid (IRF). Fluid decreased significantly in all compartments to 1.76 nl (SRF) and 0.64 nl (IRF). The investigated MNV parameters did not change significantly after the first treatment. There was no significant correlation between MNV parameters and relative fluid decrease after anti-VEGF treatment. Baseline fluid correlated statistically significant but weakly with TNE (p = 0.002, R 2  = 0.17), SRF with TVL (p = 0.04, R 2  = 0.08), VD (p = 0.046, R 2  = 0.08), TNE (p = 0.001, R 2  = 0.20) and LS (p = 0.033, R 2  = 0.09). IRF correlated with VA (p = 0.042, R 2  = 0.08).The amount of IRF at month 1 correlated significantly but weakly with VD (p = 0.036, R 2  = 0.08), JD (p = 0.019, R 2  = 0.10) and MEL (p = 0.005, R 2  = 0.14)., Conclusion: Macular neovascularization parameters at baseline and month 1 played only a minor role in the exudation process in nAMD. None of the MNV parameters were correlated with the treatment response., (© 2022 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Purpose: To identify disease activity and effects of intravitreal pegcetacoplan treatment on the topographic progression of geographic atrophy (GA) secondary to age-related macular degeneration quantified in spectral-domain OCT (SD-OCT) by automated deep learning assessment., Design: Retrospective analysis of a phase II clinical trial study evaluating pegcetacoplan in GA patients (FILLY, NCT02503332)., Subjects: SD-OCT scans of 57 eyes with monthly treatment, 46 eyes with every-other-month (EOM) treatment, and 53 eyes with sham injection from baseline and 12-month follow-ups were included, in a total of 312 scans., Methods: Retinal pigment epithelium loss, photoreceptor (PR) integrity, and hyperreflective foci (HRF) were automatically segmented using validated deep learning algorithms. Local progression rate (LPR) was determined from a growth model measuring the local expansion of GA margins between baseline and 1 year. For each individual margin point, the eccentricity to the foveal center, the progression direction, mean PR thickness, and HRF concentration in the junctional zone were computed. Mean LPR in disease activity and treatment effect conditioned on these properties were estimated by spatial generalized additive mixed-effect models., Main Outcome Measures: LPR of GA, PR thickness, and HRF concentration in μm., Results: A total of 31,527 local GA margin locations were analyzed. LPR was higher for areas with low eccentricity to the fovea, thinner PR layer thickness, or higher HRF concentration in the GA junctional zone. When controlling for topographic and structural risk factors, we report on average a significantly lower LPR by -28.0% (95% confidence interval [CI], -42.8 to -9.4; P = 0.0051) and -23.9% (95% CI, -40.2 to -3.0; P = 0.027) for monthly and EOM-treated eyes, respectively, compared with sham., Conclusions: Assessing GA progression on a topographic level is essential to capture the pathognomonic heterogeneity in individual lesion growth and therapeutic response. Pegcetacoplan-treated eyes showed a significantly slower GA lesion progression rate compared with sham, and an even slower growth rate toward the fovea. This study may help to identify patient cohorts with faster progressing lesions, in which pegcetacoplan treatment would be particularly beneficial. Automated artificial intelligence-based tools will provide reliable guidance for the management of GA in clinical practice., (Copyright © 2022 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To perform an optical coherence tomography (OCT)-based analysis of geographic atrophy (GA) progression in patients treated with pegcetacoplan., Design: Post hoc analysis of a phase 2 multicenter, randomized, sham-controlled trial., Methods: Manual annotation of retinal pigment epithelium (RPE), ellipsoid zone (EZ), and external limiting membrane (ELM) loss was performed on OCT volumes from baseline and month 12 from the phase 2 FILLY trial of intravitreal pegcetacoplan for the treatment of GA secondary to age-related macular degeneration., Main Outcome Measures: Correlation of GA areas measured on fundus autofluorescence and OCT. Difference in square root transformed growth rates of RPE, EZ, and ELM loss between treatment groups (monthly injection [AM], injection every other month [AEOM], and sham [SM])., Results: OCT volumes from 113 eyes of 113 patients (38 AM, 36 AEOM, and 39 SM) were included, resulting in 11 074 B-scans. The median growth of RPE loss was significantly slower in the AM group (0.158 [0.057-0.296]) than the SM group (0.255 [0.188-0.359], P = .014). Importantly, the growth of EZ loss was also significantly slower in the AM group (0.127 [0.041-0.247]) than the SM group (0.232 [0.130-0.349], P = .017). There was no significant difference in the growth of ELM loss between the treatment groups (P = .114)., Conclusions: OCT imaging provided consistent results for GA growth compared with fundus autofluorescence. In addition to slower RPE atrophy progression in patients treated with pegcetacoplan, a significant reduction in EZ impairment was also identified by OCT, suggesting the use of OCT as a potentially more sensitive monitoring tool in GA therapy., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: To investigate the therapeutic effect of intravitreal pegcetacoplan on the inhibition of photoreceptor (PR) loss and thinning in geographic atrophy (GA) on conventional spectral-domain OCT (SD-OCT) imaging by deep learning-based automated PR quantification., Design: Post hoc analysis of a prospective, multicenter, randomized, sham (SM)-controlled, masked phase II trial investigating the safety and efficacy of pegcetacoplan for the treatment of GA because of age-related macular degeneration., Participants: Study eyes of 246 patients, randomized 1:1:1 to monthly (AM), bimonthly (AEOM), and SM treatment., Methods: We performed fully automated, deep learning-based segmentation of retinal pigment epithelium (RPE) loss and PR thickness on SD-OCT volumes acquired at baseline and months 2, 6, and 12. The difference in the change of PR loss area was compared among the treatment arms. Change in PR thickness adjacent to the GA borders and the entire 20° scanning area was compared between treatment arms., Main Outcome Measures: Square-root transformed PR loss area in μm or mm, PR thickness in μm, and PR loss/RPE loss ratio., Results: A total of 31 556 B-scans of 644 SD-OCT volumes of 161 study eyes (AM 52, AEOM 54, SM 56) were evaluated from baseline to month 12. Comparison of the mean change in PR loss area revealed statistically significantly less growth in the AM group at months 2, 6, and 12 than in the SM group (-41 μm ± 219 vs. 77 μm ± 126; P = 0.0004; -5 μm ± 221 vs. 156 μm ± 139; P < 0.0001; 106 μm ± 400 vs. 283 μm ± 226; P = 0.0014). Photoreceptor thinning was significantly reduced under AM treatment compared with SM within the GA junctional zone, as well as throughout the 20° area. A trend toward greater inhibition of PR loss than RPE loss was observed under therapy., Conclusions: Distinct and reliable quantification of PR loss using deep learning-based algorithms offers an essential tool to evaluate therapeutic efficacy in slowing disease progression. Photoreceptor loss and thinning are reduced by intravitreal complement C3 inhibition. Automated quantification of PR loss/maintenance based on OCT images is an ideal approach to reliably monitor disease activity and therapeutic efficacy in GA management in clinical routine and regulatory trials., (Copyright © 2022 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Objectives: To investigate the impact of qualitatively graded and deep learning quantified imaging biomarkers on growth of geographic atrophy (GA) secondary to age-related macular degeneration., Methods: This prospective study included 1062 visits of 181 eyes of 100 patients with GA. Spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) images were acquired at each visit. Hyperreflective foci (HRF) were quantitatively assessed in SD-OCT volumes using a validated deep learning algorithm. FAF images were graded for FAF patterns, subretinal drusenoid deposits (SDD), GA lesion configuration and atrophy enlargement. Linear mixed models were calculated to investigate associations between all parameters and GA progression., Results: FAF patterns were significantly associated with GA progression (p < 0.001). SDD was associated with faster GA growth (p = 0.005). Eyes with higher HRF concentrations showed a trend towards faster GA progression (p = 0.072) and revealed a significant impact on GA enlargement in interaction with FAF patterns (p = 0.01). The fellow eye status had no significant effect on lesion enlargement (p > 0.05). The diffuse-trickling FAF pattern exhibited significantly higher HRF concentrations than any other pattern (p < 0.001)., Conclusion: Among a wide range of investigated biomarkers, SDD and FAF patterns, particularly in interaction with HRF, significantly impact GA progression. Fully automated quantification of retinal imaging biomarkers such as HRF is both reliable and merited as HRF are indicators of retinal pigment epithelium dysmorphia, a central pathogenetic mechanism in GA. Identifying disease markers using the combination of FAF and SD-OCT is of high prognostic value and facilitates individualized patient management in a clinical setting., (© 2021. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

Purpose: To predict visual outcomes and treatment needs in a treat & extend (T&E) regimen in neovascular age-related macular degeneration (nAMD) using a machine learning model based on quantitative optical coherence tomography (OCT) imaging biomarkers., Materials and Methods: Study eyes of 270 treatment-naïve subjects, randomized to receiving ranibizumab therapy in the T&E arm of a randomized clinical trial were considered. OCT volume scans were processed at baseline and at the first follow-up visit 4 weeks later. Automated image segmentation was performed, where intraretinal (IRF), subretinal (SRF) fluid, pigment epithelial detachment (PED), hyperreflective foci, and the photoreceptor layer were delineated using a convolutional neural network (CNN). A set of respective quantitative imaging biomarkers were computed across an Early Treatment Diabetic Retinopathy Study (ETDRS) grid to describe the retinal pathomorphology spatially and its change after the first injection. Lastly, using the computed set of OCT features and available clinical and demographic information, predictive models of outcomes and retreatment intervals were built using machine learning and their performance evaluated with a 10-fold cross-validation., Results: Data of 228 evaluable patients were included, as some had missing scans or were lost to follow-up. Of those patients, 55% reached and maintained long (8, 10, 12 weeks) and another 45% stayed at short (4, 6 weeks) treatment intervals. This provides further evidence for a high disease activity in a major proportion of patients. The model predicted the extendable treatment interval group with an AUROC of 0.71, and the visual outcome with an AUROC of up to 0.87 when utilizing both, clinical and imaging features. The volume of SRF and the volume of IRF, remaining at the first follow-up visit, were found to be the most important predictive markers for treatment intervals and visual outcomes, respectively, supporting the important role of quantitative fluid parameters on OCT., Conclusion: The proposed Artificial intelligence (AI) methodology was able to predict visual outcomes and retreatment intervals of a T&E regimen from a single injection. The result of this study is an urgently needed step toward AI-supported management of patients with active and progressive nAMD., (Copyright © 2022 Bogunović, Mares, Reiter and Schmidt-Erfurth.)

The Vienna fluid monitor is an artificial intelligence (AI) algorithm for the precise localization and quantification of retinal fluid. The algorithm is designed to help clinicians to make objective and accurate decisions in the anti-vascular endothelial growth factor (anti-VEGF) therapy of patients with neovascular age-related macular degeneration. The goal of the implementation is to optimize patient safety, preserve visual function and simultaneously to reduce the treatment burden on the healthcare system and patients., (© 2022. The Author(s).)

The retinal world has been revolutionized by optical coherence tomography (OCT) and anti-vascular endothelial growth factor (VEGF) therapy. The numbers of intravitreal injections are on a constant rise and management in neovascular age-related macular degeneration (nAMD) is mainly driven by the qualitative assessment of macular fluid as detected on OCT scans. The presence of macular fluid, particularly subretinal fluid (SRF) and intraretinal fluid (IRF), has been used to trigger re-treatments in clinical trials and the real world. However, large discrepancies can be found between the evaluations of different readers or experts and especially small amounts of macular fluid might be missed during this process. Pixel-wise detection of macular fluid uses an entire OCT volume to calculate exact volumes of retinal fluid. While manual annotations of such pixel-wise fluid detection are unfeasible in a clinical setting, artificial intelligence (AI) is able to overcome this hurdle by providing real-time results of macular fluid in different retinal compartments. Quantitative fluid assessments have been used for various post hoc analyses of randomized controlled trials, providing novel insights into anti-VEGF treatment regimens. Nonetheless, the application of AI-algorithms in a prospective patient care setting is still limited. In this review, we discuss the use of quantitative fluid assessment in nAMD during anti-VEGF therapy and provide an outlook to novel forms of patient care with the support of AI quantifications., Competing Interests: Conflict of interest statement: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: GSR: Research Funding: RetInSight; US-E: Research Funding: Genentech, Apellis, Kodiak; Consultancy: Heidelberg Engineering Novartis, Roche, RetInSight., (© The Author(s), 2022.)

Purpose: The purpose of the study was to compare ultrasound (US) consumption and central macular thickness (CMT) and volume changes with manual and femtosecond laser (FSL)-assisted cataract nucleus workup., Methods: Sixty patients scheduled for immediate sequential bilateral surgery underwent a prospective randomized intraindividual comparison of nucleus sector fragmentation performed manually in one eye and with low-energy FSL assistance in the partner eye, followed by high-fluidics phacoaspiration with a maximum US power of 30%. Ultrasound (US) energy consumption and macular thickness and volume were compared as measured by intraoperative effective phacoemulsification time (EPT) and high-resolution spectral domain optical coherence tomography pre- and 1 week, 3 weeks and 6 weeks postoperatively. Results are presented as means ± SD or medians [min; max]., Results: Fifty-two patients completed the full follow-up. For the manual and FSL-assisted groups, nuclear hardness was almost identical with a mean LOCS III grade of 2.44 ± 1.08 and 2.50 ± 1.00 (p = 0.371). Median EPT was 1.40 [0.2; 8.3] and 1.25 [0.2; 9.4] seconds. Median preoperative CMT was 276.50 [263.25; 289.75] µm and 276.00 [262.00; 290.00] µm. Median postoperative CMT was 278.00 [260.50; 288.00] versus 275.50 [264.00; 290.50] µm at 1 week, 279.50 [266.75; 292.25] versus 280.00 [266.50; 294.50] µm at 3 weeks and 280.50 [268.00, 293.75] versus 279.50 [264.75; 295.25] µm at 6 weeks. Differences in CMT and total macular volume between the groups were not statistically significant at any point in time., Conclusion: Femtosecond laser (FSL) prefragmentation of the nucleus into six sectors did not reduce US energy consumption compared with manual splitting of the nucleus into four quadrants in this particular surgical setting. Sectorial FSL-prechopping with the low-energy FSL used had no additional impact on postoperative macular thickness and volume., (© 2021 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by high-resolution three-dimensional optical coherence tomography (OCT), which is used world-wide as a diagnostic gold standard largely replacing clinical examination. Artificial intelligence (AI) with its capability to objectively identify, localize and quantify fluid introduces fully automated tools into OCT imaging for personalized disease management. Deep learning performance has already proven superior to human experts, including physicians and certified readers, in terms of accuracy and speed. Reproducible measurement of retinal fluid relies on precise AI-based segmentation methods that assign a label to each OCT voxel denoting its fluid type such as intraretinal fluid (IRF) and subretinal fluid (SRF) or pigment epithelial detachment (PED) and its location within the central 1-, 3- and 6-mm macular area. Such reliable analysis is most relevant to reflect differences in pathophysiological mechanisms and impacts on retinal function, and the dynamics of fluid resolution during therapy with different regimens and substances. Yet, an in-depth understanding of the mode of action of supervised and unsupervised learning, the functionality of a convolutional neural net (CNN) and various network architectures is needed. Greater insight regarding adequate methods for performance, validation assessment, and device- and scanning-pattern-dependent variations is necessary to empower ophthalmologists to become qualified AI users. Fluid/function correlation can lead to a better definition of valid fluid variables relevant for optimal outcomes on an individual and a population level. AI-based fluid analysis opens the way for precision medicine in real-world practice of the leading retinal diseases of modern times., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: To investigate associations between residual subretinal fluid (rSRF) volumes, quantified using artificial intelligence and treatment outcomes in a subretinal fluid (SRF)-tolerant treat-and-extend (T&E) regimen in neovascular age-related macular degeneration., Methods: Patients enrolled in the prospective, multicenter FLUID study randomized in an SRF-tolerant T&E regimen were examined by spectral-domain optical coherence tomography and tested for best-corrected visual acuity (BCVA). Intraretinal fluid and SRF volumes were quantified using artificial intelligence tools. In total, 375 visits of 98 patients were divided into subgroups: extended intervals despite rSRF and extended intervals without fluid. Associations between BCVA change, SRF volume, subgroups, and treatment intervals were estimated using linear mixed models., Results: In extended intervals despite rSRF, increased SRF was associated with reduced BCVA at the next visit in the central 1 mm (-0.138 letters per nL; P = 0.014) and 6 mm (-0.024 letters per nL; P = 0.049). A negative association between increased interval and BCVA change was found for rSRF in 1 mm and 6 mm (-0.250 and -0.233 letter per week interval, respectively; both P < 0.001). Extended intervals despite rSRF had significantly higher SRF volumes in the central 6 mm at the following visit (P = 0.002)., Conclusion: Artificial intelligence-based analysis of extended visits despite rSRF demonstrated increasing SRF volumes associated with BCVA loss at the consecutive visit. This negative association contributes to the understanding of rSRF volumes on treatment outcomes in neovascular age-related macular degeneration.

Purpose: To investigate the impact of large choroidal vessels (LCV) on Choriocapillaris (CC) flow deficit (FD) analyses with swept-source optical coherence tomography angiography (SS-OCTA)., Design: Prospective, cross-sectional study., Methods: Macular 6x6mm SS-OCTA scans were obtained from intermediate age-related macular degeneration (iAMD) and healthy eyes. Images were captured and processed according to most common standards and analyzed for percentage of flow-deficits (FD%) within four 1x1mm squares at the corners of each image. Choroidal thickness (CT), iris color and refraction error were considered as potential influential factors for LCV visibility. A linear mixed model and logistic regression models were calculated for statistical evaluation., Results: Sixty-nine iAMD and 49 age-matched healthy eyes were enrolled. LCV were visible in at least one sector in 52% of iAMD and 47% of healthy eyes. Within the iAMD group FD% were significantly lower in areas containing LCV (p = 0.0029). Increasing CT resulted in an odds ratio decrease of LCV (OR: 0.94, p<0.0001). Below a CT value of ≤118μm LCV could be expected with a sensitivity of 86% and a specificity of 85%., Conclusions: LCV can significantly affect CC FD analyses of SS-OCTA images. Their visibility is negatively associated with CT. The impact of LCV should be taken into account when performing CC FD assessments, especially in patients where reduced CT is to be expected and inclusion of affected areas should be considered carefully., Competing Interests: The authors have declared that no competing interests exist.