Disease activity and therapeutic response to pegcetacoplan for geographic atrophy identified by deep learning-based analysis of OCT.

PURPOSE: To quantify morphological changes of the photoreceptors (PR) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of optical coherence tomography (OCT) images. DESIGN: Post-hoc longitudinal image analysis SUBJECTS: Patients with GA due to age-related macular degeneration from two 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 on SD-OCT images MAIN OUTCOME MEASURES: Change in the mean area of RPE loss and EZ loss over time in the pooled sham arms and the monthly (PM)/every other month (PEOM) treatment arms RESULTS: 897 eyes of 897 patients were included. There was a therapeutic reduction of RPE loss growth by 22%/20% in OAKS and 27%/21% in DERBY for PM/PEOM compared to sham, respectively, at 24 months. The reduction on the EZ level was significantly higher with 53%/46% in OAKS and 47%/46% in DERBY for PM/PEOM compared to sham at 24 months. The baseline EZ-RPE difference had an impact on disease activity and therapeutic response. The therapeutic benefit for RPE loss growth increased with larger EZ-RPE difference quartiles from 21.9%, 23.1%, 23.9% to 33.6% for PM vs. sham (all p<0.01) and from 13.6% (p=0.11), 23.8%, 23.8% to 20.0% for PEOM vs. sham (p<0.01) in quartiles 1,2,3 and 4, respectively, at 24 months. Regarding EZ layer maintenance, the therapeutic reduction of loss increased from 14.8% (p=0.09), 33.3%, 46.6% to 77.8% (p<0.0001) between PM and sham and from 15.9% (p=0.08), 33.8%, 52.0% to 64.9% (p<0.0001) between PEOM and sham for quartiles 1-4 at 24 months. CONCLUSION: OCT-based AI analysis objectively identifies and quantifies PR and RPE degeneration in GA. Reductions in further PR degeneration consistent with 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.

LONGITUDINAL CHANGES IN QUANTITATIVE AUTOFLUORESCENCE DURING PROGRESSION FROM INTERMEDIATE TO LATE AGE-RELATED MACULAR DEGENERATION.

PURPOSE: To prospectively investigate the development of quantitative autofluorescence (qAF) during progression from intermediate to late age-related macular degeneration (AMD). METHODS: Quantitative autofluorescence images from patients with intermediate AMD were acquired every three months with a Spectralis HRA + OCT (Heidelberg Engineering, Heidelberg, Germany) using a built-in autofluorescence reference. The association between changes in longitudinal qAF and progression toward late AMD was assessed using Cox regression models with time-dependent covariates. RESULTS: One hundred and twenty-one eyes of 71 patients were included, and 653 qAF images were acquired. Twenty-one eyes of 17 patients converted to late AMD (median follow-up: 21 months; 12 eyes: atrophic AMD; nine eyes: neovascular AMD). The converting patients' mean age was 74.6 ± 4.4 years. Eleven eyes in the converting group (52.4%) were pseudophakic. The presence of an intraocular lens did not affect the qAF regression slopes (P > 0.05). The median change for atrophic AMD was -2.34 qAF units/3 months and 0.78 qAF units/3 months for neovascular AMD. A stronger decline in qAF was significantly associated with an increased risk of developing atrophic AMD (hazard ratio = 1.022, P < 0.001). This association, however, was not present in the group progressing toward neovascular AMD (hazard ratio = 1.001, P = 0.875). CONCLUSION: The qAF signal declines with progression to atrophy, contrary to developing neovascularization. Quantitative autofluorescence may allow identification of patients at risk of progressing to late AMD and benefits individualized patient care in intermediate AMD.

IMPACT OF RESIDUAL SUBRETINAL FLUID VOLUMES ON TREATMENT OUTCOMES IN A SUBRETINAL FLUID-TOLERANT TREAT-AND-EXTEND REGIMEN.

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.

ANALYSIS OF FLUID VOLUME AND ITS IMPACT ON VISUAL ACUITY IN THE FLUID STUDY AS QUANTIFIED WITH DEEP LEARNING.

PURPOSE: To investigate quantitative differences in fluid volumes between subretinal fluid (SRF)-tolerant and SRF-intolerant treat-and-extend regimens for neovascular age-related macular degeneration and analyze the association with best-corrected visual acuity. METHODS: Macular fluid (SRF and intraretinal fluid) was quantified on optical coherence tomography volumetric scans using a trained and validated deep learning algorithm. Fluid volumes and complete resolution was automatically assessed throughout the study. The impact of fluid location and volumes on best-corrected visual acuity was computed using mixed-effects regression models. RESULTS: Baseline fluid quantifications for 348 eyes from 348 patients were balanced (all P > 0.05). No quantitative differences in SRF/intraretinal fluid between the treatment arms was found at any study-specific time point (all P > 0.05). Compared with qualitative assessment, the proportion of eyes without SRF/intraretinal fluid did not differ between the groups at any time point (all P > 0.05). Intraretinal fluid in the central 1 mm and SRF in the 1-mm to 6-mm macular area were negatively associated with best-corrected visual acuity (-2.8 letters/100 nL intraretinal fluid, P = 0.007 and -0.20 letters/100 nL SRF, P = 0.005, respectively). CONCLUSION: Automated fluid quantification using artificial intelligence allows objective and precise assessment of macular fluid volume and location. Precise determination of fluid parameters will help improve therapeutic efficacy of treatment in neovascular age-related macular degeneration.

INVESTIGATING A GROWTH PREDICTION MODEL IN ADVANCED AGE-RELATED MACULAR DEGENERATION WITH SOLITARY GEOGRAPHIC ATROPHY USING QUANTITATIVE AUTOFLUORESCENCE.

PURPOSE: To investigate geographic atrophy (GA) progression using quantitative autofluorescence (qAF) in eyes with solitary GA. METHODS: Forty-three eyes of 26 patients (age 79.7 ± 7.2 years; 28 women; 16 pseudophakic) underwent spectral-domain optical coherence tomography and qAF imaging at baseline and after 12 months. The junctional zone (AJZ) and a nonaffected 300-µm-wide control area (AC) were delineated on spectral-domain optical coherence tomography scans and transferred to the qAF image. Linear mixed models were calculated to investigate the association between GA progression and qAF, age, and baseline GA area. Mixed model analyses of variance were used to investigate differences in qAF between areas. RESULTS: Quantitative autofluorescence of the three inferior sections of both the AJZ (P = 0.028; P = 0.014 and P = 0.032) and the AC (P = 0.043; P = 0.02 and P = 0.028) were significantly associated with GA progression after 12 months. However, qAF measurements were not associated with GA progression in the overall model (P > 0.05). Mean qAF was significantly lower in the AJZ and growth area (AG12) than in the AC (both P ≤ 0.001). CONCLUSION: The authors report a statistically significant association between GA growth area and qAF measurements at specific retinal locations and a significant difference in qAF between the GA border and unaffected areas outside the lesion. Quantitative autofluorescence measurements may be limitedly useful for predicting GA progression.

SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY, FLUORESCEIN ANGIOGRAPHY, AND INDOCYANINE GREEN ANGIOGRAPHY COMPARISONS REVISITED: Using a Novel Deep-Learning-Assisted Approach for Image Registration.

PURPOSE: To compare area measurements between swept source optical coherence tomography angiography (SSOCTA), fluorescein angiography (FA), and indocyanine green angiography (ICGA) after applying a novel deep-learning-assisted algorithm for accurate image registration. METHODS: We applied an algorithm for the segmentation of blood vessels in FA, ICGA, and SSOCTA images of 24 eyes with treatment-naive neovascular age-related macular degeneration. We trained a model based on U-Net and Mask R-CNN for each imaging modality using vessel annotations and junctions to estimate scaling, translation, and rotation. For fine-tuning of the registration, vessels and the elastix framework were used. Area, perimeter, and circularity measurements were performed manually using ImageJ. RESULTS: Choroidal neovascularization lesion size, perimeter, and circularity delineations showed no significant difference between SSOCTA and ICGA (all P > 0.05). Choroidal neovascularization area showed excellent correlation between SSOCTA and ICGA (r = 0.992) and a Bland-Altman bias of -0.10 ± 0.24 mm. There was no significant difference in foveal avascular zone size between SSOCTA and FA (P = 0.96) and an extremely small bias of 0.0004 ± 0.04 mm and excellent correlation (r = 0.933). Foveal avascular zone perimeter was not significantly different, but foveal avascular zone circularity was significantly different (P = 0.047), indicating that some small cavities or gaps may be missed leading to higher circularity values representing a more round-shaped foveal avascular zone in FA. CONCLUSION: We found no statistically significant differences between SSOCTA and FA and ICGA area measurements in patients with treatment-naive neovascular age-related macular degeneration after applying a deep-learning-assisted approach for image registration. These findings encourage a paradigm shift to using SSOCTA as a first-line diagnostic tool in neovascular age-related macular degeneration.

Long-term impact of low-energy femtosecond laser and manual cataract surgery on macular layer thickness: A prospective randomized study.

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.

Influence of drusenoid pigment epithelial detachments on the progression of age-related macular degeneration and visual acuity.

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.

Surgically induced astigmatism in the scleral fixated 'Carlevale' IOL technique.

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.

AI-based support for optical coherence tomography in age-related macular degeneration.

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.

Deep Learning-Based Prediction of Individual Geographic Atrophy Progression from a Single Baseline OCT.

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.

An Analysis of Ocular Biometrics: A Comprehensive Retrospective Study in a Large Cohort of Pediatric Cataract Patients.

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.

Inter and intradevice assessment of microperimetry testing in aging eyes.

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.

Sequence of Morphological Changes Preceding Atrophy in Intermediate AMD Using Deep Learning.

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.

Quantitative comparison of automated OCT and conventional FAF-based geographic atrophy measurements in the phase 3 OAKS/DERBY trials.

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.

Structure-Function Correlation of Retinal Fibrosis in Eyes with Neovascular Age-Related Macular Degeneration.

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.

Deep Neural Networks for Automated Outer Plexiform Layer Subsidence Detection on Retinal OCT of Patients With Intermediate AMD.

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.

A Systematic Prospective Comparison of Fluid Volume Evaluation across OCT Devices Used in Clinical Practice.

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.

Long-term effect of fluid volumes during the maintenance phase in neovascular age-related macular degeneration: results from Fight Retinal Blindness!

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.

Approved AI-based fluid monitoring to identify morphological and functional treatment outcomes in neovascular age-related macular degeneration in real-world routine (FRB!).

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.