[Use of artificial intelligence in geographic atrophy in age-related macular degeneration]. / Einsatz von künstlicher Intelligenz bei der geographischen Atrophie bei der altersabhängigen Makuladegeneration.

The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macular degeneration in the USA constitutes an important milestone; however, due to the nature of GA as a non-acute, insidiously progressing pathology, the ophthalmologist faces specific challenges concerning risk stratification, making treatment decisions, monitoring of treatment and patient education. Innovative retinal imaging modalities, such as fundus autofluorescence (FAF) and optical coherence tomography (OCT) have enabled identification of typical morphological alterations in relation to GA, which are also suitable for the quantitative characterization of GA. Solutions based on artificial intelligence (AI) enable automated detection and quantification of GA-specific biomarkers on retinal imaging data, also retrospectively and over time. Moreover, AI solutions can be used for the diagnosis and segmentation of GA as well as the prediction of structure and function without and under GA treatment, thereby making a valuable contribution to treatment monitoring and the identification of high-risk patients and patient education. The integration of AI solutions into existing clinical processes and software systems enables the broad implementation of informed and personalized treatment of GA secondary to AMD.

Microperimetry Characteristics of Regions With a Truly Nonresponding Location: Implications for Atrophic Age-Related Macular Degeneration.

Purpose: To understand the microperimetry response characteristics of regions with a truly nonresponding location, which will be useful when considering criteria for end-stage atrophic age-related macular degeneration (AMD). Methods: A simulation model was developed using data from 128 participants with bilateral large drusen at baseline seen over 36 months at 6-month intervals. One hundred thousand pairs of real-world microperimetry testing results were simulated separately with and without one truly nonresponding location, where the sensitivity of one randomly selected location for the former group was derived from the distribution of responses from a truly nonresponding location at the optic nerve head from 60 healthy participants. Results: Only 60% of the simulated test pairs with a truly nonresponding location had ≥1 location that was <0 decibel (dB) on both tests. In contrast, 91% of the simulated test pairs had ≥1 location that was ≤10 dB on both tests, and 87% had ≥1 location that was ≤10 dB on both tests and <0 dB for one of the tests. Of the simulated test pairs without a truly nonresponding location, there were 0.04%, 1.4%, and 0.4% that met these three above criteria, respectively. Conclusions: Regions with a truly nonresponding test location do not almost always show a repeatable absolute scotoma (<0 dB), but instead, much more often a deep visual sensitivity defect (≤10 dB), with or without having an absolute scotoma on one of the tests. These findings are crucial if functional criteria are to be considered as part of a definition of end-stage atrophic AMD.

Impact of lens autofluorescence and opacification on retinal imaging.

BACKGROUND: Retinal imaging, including fundus autofluorescence (FAF), strongly depends on the clearness of the optical media. Lens status is crucial since the ageing lens has both light-blocking and autofluorescence (AF) properties that distort image analysis. Here, we report both lens opacification and AF metrics and the effect on automated image quality assessment. METHODS: 227 subjects (range: 19-89 years old) received quantitative AF of the lens (LQAF), Scheimpflug, anterior chamber optical coherence tomography as well as blue/green FAF (BAF/GAF), and infrared (IR) imaging. LQAF values, the Pentacam Nucleus Staging score and the relative lens reflectivity were extracted to estimate lens opacification. Mean opinion scores of FAF and IR image quality were compiled by medical readers. A regression model for predicting image quality was developed using a convolutional neural network (CNN). Correlation analysis was conducted to assess the association of lens scores, with retinal image quality derived from human or CNN annotations. RESULTS: Retinal image quality was generally high across all imaging modalities (IR (8.25±1.99) >GAF >BAF (6.6±3.13)). CNN image quality prediction was excellent (average mean absolute error (MAE) 0.9). Predictions were comparable to human grading. Overall, LQAF showed the highest correlation with image quality grading criteria for all imaging modalities (eg, Pearson correlation±CI -0.35 (-0.50 to 0.18) for BAF/LQAF). BAF image quality was most vulnerable to an increase in lenticular metrics, while IR (-0.19 (-0.38 to 0.01)) demonstrated the highest resilience. CONCLUSION: The use of CNN-based retinal image quality assessment achieved excellent results. The study highlights the vulnerability of BAF to lenticular remodelling. These results can aid in the development of cut-off values for clinical studies, ensuring reliable data collection for the monitoring of retinal diseases.

Personalized Lens Correction Improves Quantitative Fundus Autofluorescence Analysis.

Purpose: Quantitative fundus autofluorescence (QAF) currently deploys an age-based score to correct for lens opacification. However, in elderly people, lens opacification varies strongly between individuals of similar age, and innate lens autofluorescence is not included in the current correction formula. Our goal was to develop and compare an individualized formula. Methods: One hundred thirty participants were examined cross-sectionally, and a subset of 30 participants received additional multimodal imaging 2-week post-cataract-surgery. Imaging included the Scheimpflug principle, anterior chamber optical coherence tomography (AC-OCT), lens quantitative autofluorescence (LQAF), and retinal QAF imaging. Among the subset, least absolute shrinkage and selection operator regression and backward selection was implemented to determine which lens score best predicts the QAF value after lens extraction. Subsequently, a spline mixed model was applied to the whole cohort to quantify the influence of LQAF and Scheimpflug on QAF. Results: Age and LQAF measurements were found to be the most relevant variables, whereas AC-OCT measurements and Scheimpflug were eliminated by backward selection. Both an increase in Scheimpflug and LQAF values were associated with a decrease in QAF. The prediction error of the spline model (mean absolute error [MAE] ± standard deviation) of 32.2 ± 23.4 (QAF a.u.) was markedly lower compared to the current age-based formula MAE of 96.1 ± 93.5. Both smooth terms, LQAF (P < 0.01) and Scheimpflug (P < 0.001), were significant for the spline mixed model. Conclusions: LQAF imaging proved to be the most predictive for the impact of the natural lens on QAF imaging. The application of lens scores in the clinic could improve the accuracy of QAF imaging interpretation and might allow including aged patients in future QAF studies.

Association of Lesion Location and Functional Parameters with Vision-Related Quality of Life in Geographic Atrophy Secondary to Age-related Macular Degeneration.

OBJECTIVE: The primary goal of this study was to determine how structural and functional parameters influence the vision-related quality of life (VRQoL) in patients suffering from geographic atrophy (GA) secondary to age-related macular degeneration. DESIGN: This study was designed as a prospective, noninterventional, natural-history study (Directional Spread in Geographic-Atrophy study, NCT02051998). SUBJECTS: The research involved 82 patients with bilateral GA. METHODS: The study examined parameters including GA location as assessed by the ETDRS grid, best-corrected visual acuity, low-luminance visual acuity (LLVA), reading acuity, and speed. These parameters were then correlated with VRQoL, which was gauged using the National Eye Institute Visual Function Questionnaire 25. The analysis method employed was the least absolute shrinkage and selection operator with linear mixed-effects models. MAIN OUTCOME MEASURES: The central parameters measured in this study encompassed GA area, VRQoL scores associated with different GA subfields, and the significance of LLVA for foveal-sparing patients. RESULTS: On average, patients showed a total GA area of 2.9 ± 1.2 mm2 in the better eye (BE) and 3.1 ± 1.3 mm2 in the worse eye. The most significant associations with VRQoL scores for distance and near activities were observed in the inner lower and inner left subfields of the BE, respectively. For patients with foveal-sparing GA, the LLVA of the BE stood out as the most influential variable across all VRQoL scales. CONCLUSIONS: The study's findings point toward the pivotal role of GA location, especially the inner lower and inner left subfields of the BE, in relation to VRQoL in GA patients. The LLVA's importance becomes even more pronounced for foveal-sparing patients. These observations highlight the need for health care professionals to better understand the association between lesion location and patient-reported outcomes. This is critical for informing treatment decisions and refining the planning of interventional trials. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Age-Related Macular Degeneration: A Review.

Importance: Age-related macular degeneration (AMD) affects approximately 20 million people in the US and 196 million people worldwide. AMD is a leading cause of severe vision impairment in older people and is expected to affect approximately 288 million people worldwide by 2040. Observations: Older age, genetic factors, and environmental factors, such as cigarette smoking, are associated with development of AMD. AMD occurs when extracellular deposits accumulate in the outer retina, ultimately leading to photoreceptor degeneration and loss of central vision. The late stages of AMD are characterized by outer retinal atrophy, termed geographic atrophy, or neovascularization associated with subretinal and/or intraretinal exudation, termed exudative neovascular AMD. The annual incidence of AMD ranges from 0.3 per 1000 in people who are aged 55 to 59 years to 36.7 per 1000 in people aged 90 years or older. The estimated heritability of late-stage AMD is approximately 71% (95% CI, 18%-88%). Long-term prospective cohort studies show a significantly higher AMD incidence in people who smoke more than 20 cigarettes per day compared with people who never smoked. AMD is diagnosed primarily with clinical examination that includes a special lens that focuses light of the slit lamp through the pupil. Exudative neovascular AMD is best identified using angiography and by optical coherence tomography. Individuals with AMD who take nutritional supplements consisting of high-dose vitamin C, vitamin E, carotenoids, and zinc have a 20% probability to progress to late-stage AMD at 5 years vs a 28% probability for those taking a placebo. In exudative neovascular AMD, 94.6% of patients receiving monthly intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections experience less than a 15-letter visual acuity loss after 12 months compared with 62.2% receiving sham treatment. Conclusions and Relevance: The prevalence of AMD is anticipated to increase worldwide to 288 million individuals by 2040. Intravitreally administered anti-VEGF treatment is first-line therapy for exudative neovascular AMD.

Multimodal imaging and deep learning in geographic atrophy secondary to age-related macular degeneration.

Geographic atrophy (GA) secondary to age-related macular degeneration is among the most common causes of irreversible vision loss in industrialized countries. Recently, two therapies have been approved by the US FDA. However, given the nature of their treatment effect, which primarily involves a relative decrease in disease progression, discerning the individual treatment response at the individual level may not be readily apparent. Thus, clinical decision-making may have to rely on the quantification of the slope of GA progression before and during treatment. A panel of imaging modalities and artificial intelligence (AI)-based algorithms are available for such quantifications. This article aims to provide a comprehensive overview of the fundamentals of GA imaging, the procedures for diagnosis and classification using these images, and the cutting-edge role of AI algorithms in automatically deriving diagnostic and prognostic insights from imaging data.

Impact of lesion location and functional parameters on vision-related quality of life in geographic atrophy secondary to AMD.

Background/Aims: The primary objective was to determine how structural and functional parameters influence the vision-related quality of life (VRQoL) in patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD). Methods: This prospective, non-interventional, natural-history 'Directional Spread in Geographic-Atrophy' study was conducted at the University Eye Hospital in Bonn, enrolling 82 patients with bilateral GA. Parameters such as GA location (assessed by the Early Treatment Diabetic Retinopathy Study grid), best-corrected visual acuity (BCVA), low-luminance visual acuity (LLVA), reading acuity, and speed were examined. The association between these parameters and VRQoL, as gauged using the National Eye Institute Visual Function Questionnaire 25 (NEI VFQ-25), was analyzed through least absolute shrinkage and selection operator with linear mixed-effects models. Results: The average total GA area observed was 2.9 ± 1.2 mm2 (better eye) and 3.1 ± 1.3 mm2 (worse eye). The VRQoL scores for distance and near activities were most associated with the inner lower and inner left subfields of the better eye. For foveal-sparing patients, the LLVA of the better eye was the predominant determinate impacting all VRQoL scales. Conclusion: GA location, specifically the inner lower and inner left subfields of the better eye, has a notable effect on VRQoL in GA patients. LLVA stands out as especially vital in foveal-sparing patients, underscoring the importance for clinicians to incorporate considerations of GA location and functional parameters into their risk-benefit assessments for emerging treatments.

Association of complement C3 inhibitor pegcetacoplan with reduced photoreceptor degeneration beyond areas of geographic atrophy.

Preservation of photoreceptors beyond areas of retinal pigment epithelium atrophy is a critical treatment goal in eyes with geographic atrophy (GA) to prevent vision loss. Thus, we assessed the association of treatment with the complement C3 inhibitor pegcetacoplan with optical coherence tomography (OCT)-based photoreceptor laminae thicknesses in this post hoc analysis of the FILLY trial (NCT02503332). Retinal layers in OCT were segmented using a deep-learning-based pipeline and extracted along evenly spaced contour-lines surrounding areas of GA. The primary outcome measure was change from baseline in (standardized) outer nuclear layer (ONL) thickness at the 5.16°-contour-line at month 12. Participants treated with pegcetacoplan monthly had a thicker ONL along the 5.16° contour-line compared to the pooled sham arm (mean difference [95% CI] + 0.29 z-score units [0.16, 0.42], P < 0.001). The same was evident for eyes treated with pegcetacoplan every other month (+ 0.26 z-score units [0.13, 0.4], P < 0.001). Additionally, eyes treated with pegcetacoplan exhibited a thicker photoreceptor inner segment layer along the 5.16°-contour-line at month 12. These findings suggest that pegcetacoplan could slow GA progression and lead to reduced thinning of photoreceptor layers beyond the GA boundary. Future trials in earlier disease stages, i.e., intermediate AMD, aiming to slow photoreceptor degeneration warrant consideration.

Progression of Age-Related Macular Degeneration Among Individuals Homozygous for Risk Alleles on Chromosome 1 (CFH-CFHR5) or Chromosome 10 (ARMS2/HTRA1) or Both.

IMPORTANCE: Age-related macular degeneration (AMD) is a common cause of irreversible vision loss among individuals older than 50 years. Although considerable advances have been made in our understanding of AMD genetics, the differential effects of major associated loci on disease manifestation and progression may not be well characterized. OBJECTIVE: To elucidate the specific associations of the 2 most common genetic risk loci for AMD, the CFH-CFHR5 locus on chromosome 1q32 (Chr1) and the ARMS2/HTRA1 locus on chromosome 10q26 (Chr10)-independent of one another and in combination-with time to conversion to late-stage disease and to visual acuity loss. DESIGN, SETTING, AND PARTICIPANTS: This case series study included 502 individuals who were homozygous for risk variants at both Chr1 and Chr10 (termed Chr1&10-risk) or at either Chr1 (Chr1-risk) or Chr10 (Chr10-risk) and who had enrolled in Genetic and Molecular Studies of Eye Diseases at the Sharon Eccles Steele Center for Translational Medicine between September 2009 and March 2020. Multimodal imaging data were reviewed for AMD staging, including grading of incomplete and complete retinal pigment epithelium and outer retinal atrophy. MAIN OUTCOMES AND MEASURES: Hazard ratios and survival times for conversion to any late-stage AMD, atrophic or neovascular, and associated vision loss of 2 or more lines. RESULTS: In total, 317 participants in the Chr1-risk group (median [IQR] age at first visit, 75.6 [69.5-81.7] years; 193 women [60.9%]), 93 participants in the Chr10-risk group (median [IQR] age at first visit, 77.5 [72.2-84.2] years; 62 women [66.7%]), and 92 participants in the Chr1&10-risk group (median [IQR] age at first visit, 71.7 [68.0-76.3] years; 62 women [67.4%]) were included in the analyses. After adjusting for age and AMD grade at first visit, compared with 257 participants in the Chr1-risk group, 56 participants in the Chr1&10-risk group (factor of 3.3 [95% CI, 1.6-6.8]; P < .001) and 58 participants in the Chr10-risk group (factor of 2.6 [95% CI, 1.3-5.2]; P = .007) were more likely to convert to a late-stage phenotype during follow-up. This difference was mostly associated with conversion to macular neovascularization, which occurred earlier in participants with Chr1&10-risk and Chr10-risk. Eyes in the Chr1&10-risk group (median [IQR] survival, 5.7 [2.1-11.1] years) were 2.1 (95% CI, 1.1-3.9; P = .03) times as likely and eyes in the Chr10-risk group (median [IQR] survival, 6.3 [2.7-11.3] years) were 1.8 (95% CI, 1.0-3.1; P = .05) times as likely to experience a visual acuity loss of 2 or more lines compared with eyes of the Chr1-risk group (median [IQR] survival, 9.4 [4.1-* (asterisk indicates event rate did not reach 75%)] years). CONCLUSIONS AND RELEVANCE: These findings suggest differential associations of the 2 major AMD-related risk loci with structural and functional disease progression and suggest distinct underlying biological mechanisms associated with these 2 loci. These genotype-phenotype associations may warrant consideration when designing and interpreting AMD research studies and clinical trials.

Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence.

Refined understanding of the association of retinal microstructure with current and future (post-treatment) function in chronic central serous chorioretinopathy (cCSC) may help to identify patients that would benefit most from treatment. In this post-hoc analysis of data from the prospective, randomized PLACE trial (NCT01797861), we aimed to determine the accuracy of AI-based inference of retinal function from retinal morphology in cCSC. Longitudinal spectral-domain optical coherence tomography (SD-OCT) data from 57 eyes of 57 patients from baseline, week 6-8 and month 7-8 post-treatment were segmented using deep-learning software. Fundus-controlled perimetry data were aligned to the SD-OCT data to extract layer thickness and reflectivity values for each test point. Point-wise retinal sensitivity could be inferred with a (leave-one-out) cross-validated mean absolute error (MAE) [95% CI] of 2.93 dB [2.40-3.46] (scenario 1) using random forest regression. With addition of patient-specific baseline data (scenario 2), retinal sensitivity at remaining follow-up visits was estimated even more accurately with a MAE of 1.07 dB [1.06-1.08]. In scenario 3, month 7-8 post-treatment retinal sensitivity was predicted from baseline SD-OCT data with a MAE of 3.38 dB [2.82-3.94]. Our study shows that localized retinal sensitivity can be inferred from retinal structure in cCSC using machine-learning. Especially, prediction of month 7-8 post-treatment sensitivity with consideration of the treatment as explanatory variable constitutes an important step toward personalized treatment decisions in cCSC.

Association of Reading Performance in Geographic Atrophy Secondary to Age-Related Macular Degeneration With Visual Function and Structural Biomarkers.

IMPORTANCE: As a disabling and frequent disease, geographic atrophy secondary to age-related macular degeneration (AMD) constitutes an important study subject. Emerging clinical trials require suitable end points. The characterization and validation of reading performance as a functional outcome parameter is warranted. OBJECTIVE: To prospectively evaluate reading performance in geographic atrophy and to assess its association with established visual function assessments and structural biomarkers. DESIGN, SETTING, AND PARTICIPANTS: The noninterventional, prospective natural history Directional Spread in Geographic Atrophy study included patients with geographic atrophy secondary to AMD who were recruited at the University Hospital in Bonn, Germany. Participants were enrolled from June 2013 to June 2016. Analysis began December 2019 and ended January 2021. MAIN OUTCOMES AND MEASURES: Reading acuity and reading speed were assessed using Radner charts. Longitudinal fundus autofluorescence and infrared reflectance images were semiautomatically annotated for geographic atrophy, followed by extraction of shape-descriptive variables. Linear mixed-effects models were applied to investigate the association of those variables with reading performance. RESULTS: A total of 150 eyes of 85 participants were included in this study (median [IQR] age, 77.9 [72.4-82.1] years; 51 women [60%]; 34 men [40%]). Reading performance was impaired with a median (IQR) monocular reading acuity of 0.9 (0.4-1.3) logarithm of the reading acuity determination and a reading speed of 52.8 (0-123) words per minute. In the multivariable cross-sectional analysis, best-corrected visual acuity, area of geographic atrophy in the central Early Treatment Diabetic Retinopathy Study (ETDRS) subfield, classification of noncenter vs center-involving geographic atrophy, and area of geographic atrophy in the inner-right ETDRS subfield showed strongest associations with reading acuity (cross-validated R2for reading acuity = 0.69). Regarding reading speed, the most relevant variables were best-corrected visual acuity, low-luminance visual acuity, area of geographic atrophy in the central ETDRS subfield, in the inner-right ETDRS subfield, and in the inner-upper ETDRS subfield (R2 for reading speed = 0.67). In the longitudinal analysis, a similar prediction accuracy for reading performance was determined (R2 for reading acuity = 0.73; R2 for reading speed = 0.70). Prediction accuracy did not improve when follow-up time was added as an independent variable. Binocular reading performance did not differ from reading performance in the better-seeing eye. CONCLUSIONS AND RELEVANCE: The association of reading acuity and speed with visual functional and structural biomarkers supports the validity of reading performance as a meaningful end point in clinical trials. These findings suggest that measures in clinical and low-vision care for patients with geographic atrophy should focus primarily on the better-seeing eye.

Modeling of atrophy size trajectories: variable transformation, prediction and age-of-onset estimation.

BACKGROUND: To model the progression of geographic atrophy (GA) in patients with age-related macular degeneration (AMD) by building a suitable statistical regression model for GA size measurements obtained from fundus autofluorescence imaging. METHODS: Based on theoretical considerations, we develop a linear mixed-effects model for GA size progression that incorporates covariable-dependent enlargement rates as well as correlations between longitudinally collected GA size measurements. To capture nonlinear progression in a flexible way, we systematically assess Box-Cox transformations with different transformation parameters λ. Model evaluation is performed on data collected for two longitudinal, prospective multi-center cohort studies on GA size progression. RESULTS: A transformation parameter of λ=0.45 yielded the best model fit regarding the Akaike information criterion (AIC). When hypertension and hypercholesterolemia were included as risk factors in the model, they showed an association with progression of GA size. The mean estimated age-of-onset in this model was 67.21±6.49 years. CONCLUSIONS: We provide a comprehensive framework for modeling the course of uni- or bilateral GA size progression in longitudinal observational studies. Specifically, the model allows for age-of-onset estimation, identification of risk factors and prediction of future GA size. A square-root transformation of atrophy size is recommended before model fitting.

Probabilistic Forecasting of Anti-VEGF Treatment Frequency in Neovascular Age-Related Macular Degeneration.

Purpose: To probabilistically forecast needed anti-vascular endothelial growth factor (anti-VEGF) treatment frequency using volumetric spectral domain-optical coherence tomography (SD-OCT) biomarkers in neovascular age-related macular degeneration from real-world settings. Methods: SD-OCT volume scans were segmented with a custom deep-learning-based analysis pipeline. Retinal thickness and reflectivity values were extracted for the central and the four inner Early Treatment Diabetic Retinopathy Study (ETDRS) subfields for six retinal layers (inner retina, outer nuclear layer, inner segments [IS], outer segments [OS], retinal pigment epithelium-drusen complex [RPEDC] and the choroid). Machine-learning models were probed to predict the anti-VEGF treatment frequency within the next 12 months. Probabilistic forecasting was performed using natural gradient boosting (NGBoost), which outputs a full probability distribution. The mean absolute error (MAE) between the predicted versus actual anti-VEGF treatment frequency was the primary outcome measure. Results: In a total of 138 visits of 99 eyes with neovascular AMD (96 patients) from two clinical centers, the prediction of future anti-VEGF treatment frequency was observed with an accuracy (MAE [95% confidence interval]) of 2.60 injections/year [2.25-2.96] (R2 = 0.390) using random forest regression and 2.66 injections/year [2.31-3.01] (R2 = 0.094) using NGBoost, respectively. Prediction intervals were well calibrated and reflected the true uncertainty of NGBoost-based predictions. Standard deviation of RPEDC-thickness in the central ETDRS-subfield constituted an important predictor across models. Conclusions: The proposed, fully automated pipeline enables probabilistic forecasting of future anti-VEGF treatment frequency in real-world settings. Translational Relevance: Prediction of a probability distribution allows the physician to inspect the underlying uncertainty. Predictive uncertainty estimates are essential to highlight cases where human-inspection and/or reversion to a fallback alternative is warranted.

Comparing Fluorescence Lifetime Imaging Ophthalmoscopy in Atrophic Areas of Retinal Diseases.

Purpose: Fluorescence lifetime imaging ophthalmoscopy (FLIO) is a non-invasive imaging modality to investigate the human retina. This study compares FLIO lifetimes in different degenerative retinal diseases. Methods: Included were eyes with retinal pigment epithelium (RPE) and/or photoreceptor atrophy due to Stargardt disease (n = 66), pattern dystrophy (n = 18), macular telangiectasia type 2 (n = 49), retinitis pigmentosa (n = 28), choroideremia (n = 26), and geographic atrophy (n = 32) in age-related macular degeneration, as well as 37 eyes of 37 age-matched healthy controls. Subjects received Heidelberg Engineering FLIO, autofluorescence intensity, and optical coherence tomography imaging. Amplitude-weighted mean FLIO lifetimes (τm) were calculated and analyzed. Results: Retinal FLIO lifetimes show significant differences depending on the disease. Atrophic areas in geographic atrophy and choroideremia showed longest mean FLIO lifetimes. τm values within areas of RPE and outer nuclear layer atrophy were significantly longer than within areas with preserved outer nuclear layer (P < 0.001) or non-atrophic areas (P < 0.001). Conclusions: FLIO is able to contribute additional information regarding differences in chronic degenerative retinal diseases. Although it cannot replace conventional autofluorescence imaging, FLIO adds to the knowledge in these diseases and may help with the correct differentiation between them. This may lead to a more in-depth understanding of the pathomechanisms related to atrophy and types of progression. Translational Relevance: Differences between atrophic retinal diseases highlighted by FLIO may indicate separate pathomechanisms leading to atrophy and disease progression.

Age-related macular degeneration.

Age-related macular degeneration (AMD) is the leading cause of legal blindness in the industrialized world. AMD is characterized by accumulation of extracellular deposits, namely drusen, along with progressive degeneration of photoreceptors and adjacent tissues. AMD is a multifactorial disease encompassing a complex interplay between ageing, environmental risk factors and genetic susceptibility. Chronic inflammation, lipid deposition, oxidative stress and impaired extracellular matrix maintenance are strongly implicated in AMD pathogenesis. However, the exact interactions of pathophysiological events that culminate in drusen formation and the associated degeneration processes remain to be elucidated. Despite tremendous advances in clinical care and in unravelling pathophysiological mechanisms, the unmet medical need related to AMD remains substantial. Although there have been major breakthroughs in the treatment of exudative AMD, no efficacious treatment is yet available to prevent progressive irreversible photoreceptor degeneration, which leads to central vision loss. Compelling progress in high-resolution retinal imaging has enabled refined phenotyping of AMD in vivo. These insights, in combination with clinicopathological and genetic correlations, have underscored the heterogeneity of AMD. Hence, our current understanding promotes the view that AMD represents a disease spectrum comprising distinct phenotypes with different mechanisms of pathogenesis. Hence, tailoring therapeutics to specific phenotypes and stages may, in the future, be the key to preventing irreversible vision loss.

AI-based structure-function correlation in age-related macular degeneration.

Sensitive and robust outcome measures of retinal function are pivotal for clinical trials in age-related macular degeneration (AMD). A recent development is the implementation of artificial intelligence (AI) to infer results of psychophysical examinations based on findings derived from multimodal imaging. We conducted a review of the current literature referenced in PubMed and Web of Science among others with the keywords 'artificial intelligence' and 'machine learning' in combination with 'perimetry', 'best-corrected visual acuity (BCVA)', 'retinal function' and 'age-related macular degeneration'. So far AI-based structure-function correlations have been applied to infer conventional visual field, fundus-controlled perimetry, and electroretinography data, as well as BCVA, and patient-reported outcome measures (PROM). In neovascular AMD, inference of BCVA (hereafter termed inferred BCVA) can estimate BCVA results with a root mean squared error of ~7-11 letters, which is comparable to the accuracy of actual visual acuity assessment. Further, AI-based structure-function correlation can successfully infer fundus-controlled perimetry (FCP) results both for mesopic as well as dark-adapted (DA) cyan and red testing (hereafter termed inferred sensitivity). Accuracy of inferred sensitivity can be augmented by adding short FCP examinations and reach mean absolute errors (MAE) of ~3-5 dB for mesopic, DA cyan and DA red testing. Inferred BCVA, and inferred retinal sensitivity, based on multimodal imaging, may be considered as a quasi-functional surrogate endpoint for future interventional clinical trials in the future.

Prognostic value of intermediate age-related macular degeneration phenotypes for geographic atrophy progression.

BACKGROUND: To characterise early stages of geographic atrophy (GA) development in age-related macular degeneration (AMD) and to determine the prognostic value of structural precursor lesions in eyes with intermediate (i) AMD on the subsequent GA progression. METHODS: Structural precursor lesions for atrophic areas (lesion size at least 0.5 mm² in fundus autofluorescence images) were retrospectively identified based on multimodal imaging and evaluated for association with the subsequent GA enlargement rates (square-root transformed, sqrt). A linear mixed-effects model was used to account for the hierarchical nature of the data with a Tukey post hoc test to assess the impact of the local precursor on the subsequent GA progression rate. RESULTS: A total of 39 eyes with GA of 34 patients with a mean age of 74.4±6.7 (±SD) years were included in this study. Five precursor lesions (phenotypes 1-5) preceding GA development were identified: large, sub-retinal pigment epithelial drusen (n=19), reticular pseudodrusen (RPD, n=10), refractile deposits (n=4), pigment epithelial detachment (n=4) and vitelliform lesions (n=2). Precursor lesions exhibited a significant association with the subsequent (sqrt) GA progression rates (p=0.0018) with RPD (phenotype 2) being associated with the fastest GA enlargement (2.29±0.52 (±SE) mm/year. CONCLUSIONS: The results indicate the prognostic relevance of iAMD phenotyping for subsequent GA progression highlighting the role of structural AMD features across different AMD stages.