Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning

PURPOSE: To apply a deep learning algorithm for automated, objective, and comprehensive quantification of optical coherence tomography (OCT) scans to a large real-world dataset of eyes with neovascular age-related macular degeneration (AMD), and make the raw segmentation output data openly available for further research. DESIGN: Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database. PARTICIPANTS: 2473 first-treated eyes and another 493 second-treated eyes that commenced therapy for neovascular AMD between June 2012 and June 2017. METHODS: A deep learning algorithm was used to segment all baseline OCT scans. Volumes were calculated for segmented features such as neurosensory retina (NSR), drusen, intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM), retinal pigment epithelium (RPE), hyperreflective foci (HRF), fibrovascular pigment epithelium detachment (fvPED), and serous PED (sPED). Analyses included comparisons between first and second eyes, by visual acuity (VA) and by race/ethnicity, and correlations between volumes. MAIN OUTCOME MEASURES: Volumes of segmented features (mm3), central subfield thickness (CST) (μm). RESULTS: In first-treated eyes, the majority had both IRF and SRF (54.7%). First-treated eyes had greater volumes for all segmented tissues, with the exception of drusen, which was greater in second-treated eyes. In first-treated eyes, older age was associated with lower volumes for RPE, SRF, NSR and sPED; in second-treated eyes, older age was associated with lower volumes of NSR, RPE, sPED, fvPED and SRF. Eyes from black individuals had higher SRF, RPE and serous PED volumes, compared with other ethnic groups. Greater volumes of the vast majority of features were associated with worse VA. CONCLUSION: We report the results of large scale automated quantification of a novel range of baseline features in neovascular AMD. Major differences between first and second-treated eyes, with increasing age, and between ethnicities are highlighted. In the coming years, enhanced, automated OCT segmentation may assist personalization of real-world care, and the detection of novel structure-function correlations. These data will be made publicly available for replication and future investigation by the AMD research community

The Role of Medical Image Modalities and AI in the Early Detection, Diagnosis and Grading of Retinal Diseases: A Survey.

Traditional dilated ophthalmoscopy can reveal diseases, such as age-related macular degeneration (AMD), diabetic retinopathy (DR), diabetic macular edema (DME), retinal tear, epiretinal membrane, macular hole, retinal detachment, retinitis pigmentosa, retinal vein occlusion (RVO), and retinal artery occlusion (RAO). Among these diseases, AMD and DR are the major causes of progressive vision loss, while the latter is recognized as a world-wide epidemic. Advances in retinal imaging have improved the diagnosis and management of DR and AMD. In this review article, we focus on the variable imaging modalities for accurate diagnosis, early detection, and staging of both AMD and DR. In addition, the role of artificial intelligence (AI) in providing automated detection, diagnosis, and staging of these diseases will be surveyed. Furthermore, current works are summarized and discussed. Finally, projected future trends are outlined. The work done on this survey indicates the effective role of AI in the early detection, diagnosis, and staging of DR and/or AMD. In the future, more AI solutions will be presented that hold promise for clinical applications

En Face Enhanced-Depth Swept-Source Optical Coherence Tomography Features of Chronic Central Serous Chorioretinopathy

Objective To characterize en face features of the retinal pigment epithelium (RPE) and choroid in eyes with chronic central serous chorioretinopathy (CSCR) using a high-speed, enhanced-depth swept-source optical coherence tomography (SS-OCT) prototype. Design Consecutive patients with chronic CSCR were prospectively examined with SS-OCT. Participants Fifteen eyes of 13 patients. Methods Three-dimensional 6×6 mm macular cube raster scans were obtained with SS-OCT operating at 1050 nm wavelength and 100 000 A-lines/sec with 6 μm axial resolution. Segmentation of the RPE generated a reference surface; en face SS-OCT images of the RPE and choroid were extracted at varying depths every 3.5 μm (1 pixel). Abnormal features were characterized by systematic analysis of multimodal fundus imaging, including color photographs, fundus autofluorescence, fluorescein angiography, and indocyanine-green angiography (ICGA). Main Outcome Measures En face SS-OCT morphology of the RPE and individual choroidal layers. Results En face SS-OCT imaging at the RPE level revealed absence of signal corresponding to RPE detachment or RPE loss in 15 of 15 (100%) eyes. En face SS-OCT imaging at the choriocapillaris level showed focally enlarged vessels in 8 of 15 eyes (53%). At the level of Sattler's layer, en face SS-OCT documented focal choroidal dilation in 8 of 15 eyes (53%) and diffuse choroidal dilation in 7 of 15 eyes (47%). At the level of Haller's layer, these same features were observed in 3 of 15 eyes (20%) and 12 of 15 eyes (80%), respectively. In all affected eyes, these choroidal vascular abnormalities were seen just below areas of RPE abnormalities. In 2 eyes with secondary choroidal neovascularization (CNV), distinct en face SS-OCT features corresponded to the neovascular lesions. Conclusions High-speed, enhanced-depth SS-OCT at 1050 nm wavelength enables the visualization of pathologic features of the RPE and choroid in eyes with chronic CSCR not usually appreciated with standard spectral domain (SD) OCT. En face SS-OCT imaging seems to be a useful tool in the identification of CNV without the use of angiography. This in vivo documentation of the RPE and choroidal vasculature at variable depths may help elucidate the pathophysiology of disease and can contribute to the diagnosis and management of chronic CSCR.National Institutes of Health (U.S.) (R01-EY011289-27)National Institutes of Health (U.S.) (R01-EY013178-12)National Institutes of Health (U.S.) (R01-EY018184-05)National Institutes of Health (U.S.) (R44EY022864-01)National Institutes of Health (U.S.) (GR01-CA075289-16)National Institutes of Health (U.S.) (R01-NS057476-05)National Institutes of Health (U.S.) (R44-EY022864-01)United States. Air Force Office of Scientific Research (FA9550-10-1-0551)United States. Air Force Office of Scientific Research (FA9550-10-1-0063)Research to Prevent Blindness, Inc. (United States)Massachusetts Lions ClubGerman Science Foundation (DFG-GSC80-SAOT

Quantification of key retinal features in early and late age-related macular degeneration using deep learning

PURPOSE: To develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD). DESIGN: Development and validation of a deep-learning model for feature segmentation METHODS: Data for model development were obtained from 307 optical coherence tomography volumes. Eight experienced graders manually delineated all abnormalities in 2,712 B-scans. A deep neural network was trained with this data to perform voxel-level segmentation of the 13 most common abnormalities (features). For evaluation, 112 B-scans from 112 patients with a diagnosis of neovascular AMD were annotated by four independent observers. Main outcome measures were Dice score, intra-class correlation coefficient (ICC), and free-response receiver operating characteristic (FROC) curve. RESULTS: On 11 of the 13 features, the model obtained a mean Dice score of 0.63 ± 0.15, compared to 0.61 ± 0.17 for the observers. The mean ICC for the model was 0.66 ± 0.22, compared to 0.62 ± 0.21 for the observers. Two features were not evaluated quantitatively due to lack of data. FROC analysis demonstrated that the model scored similar or higher sensitivity per false positives compared to the observers. CONCLUSIONS: The quality of the automatic segmentation matches that of experienced graders for most features, exceeding human performance for some features. The quantified parameters provided by the model can be used in the current clinical routine and open possibilities for further research into treatment response outside clinical trials

Use of Fundus Autofluorescence Combined with Optical Coherence Tomography for Diagnose of Geographic Atrophy in Age-Related Macular Degeneration

The aim of this study was to demonstrate the sensitivity of Optical coherence tomography (OCT) in detection of geographic atrophy (GA) secondary to exudative age related macular degeneration (AMD). In this retrospective case series study 77 patients (53% female, with mean ± standard deviation [SD] of 82.6±9.3 years) with 97 eyes (45 OS [left eyes]/52 OD [right eyes]) were included. This was a retrospective review of the charts of patients who presented with exudative AMD at the Pitié Salpetrière Hospital, Paris, France, between December 2016 and August 2017 that received intravitreal injections of anti-vascular endothelial growth factor (anti-VEGF) therapies. At baseline, following biomicroscopy examination, multimodal imaging was performed including, fluorescein angiography (FA), fundus auto-fluorescence (FAF), spectral domain optical coherence tomography (SD-OCT) and indocyanine green angiography (ICGA). During the follow-up, SD-OCT with/without FAF and FA were performed for each patient at 6, 12 and 18 months. For investigation of the prevalence of GA in eyes undergoing intravitreal injections with anti-VEGF therapy, FAF and SD-OCT images were qualitatively reviewed by four independent observers (two graders per group). Kappa coefficient of Cohen was calculated to determine agreement between the graders. The kappa coefficient of Cohen, for inter-rater agreement in the evaluation of FAF images was 0.468, indicating a moderate agreement between the first and second raters. Thus, the sensitivity and specificity of FAF for the diagnosis of GA were 70% and 57%, respectively. If atrophy was assessed with SD-OCT image analysis, the kappa coefficient for inter-rater agreement was 0.846, implying an acceptable agreement between both readers. The sensitivity and specificity of SD-OCT were 93% and 58% respectively. In conclusion, SD-OCT image analysis was more sensitive than FAF for identifying GA in patients treated for exudative AMD. Epub: October 1, 2019

The Onion Sign in Neovascular Age-Related Macular Degeneration Represents Cholesterol Crystals

PURPOSE: To investigate the frequency, natural evolution, and histologic correlates of layered, hyperreflective, subretinal pigment epithelium (sub-RPE) lines, known as the onion sign, in neovascular age-related macular degeneration (AMD). DESIGN: Retrospective observational cohort study and experimental laboratory study. PARTICIPANTS: Two hundred thirty eyes of 150 consecutive patients with neovascular AMD and 40 human donor eyes with histopathologic diagnosis of neovascular AMD. METHODS: Spectral-domain optical coherence tomography (SD OCT), near-infrared reflectance (NIR), color fundus images, and medical charts were reviewed. Donor eyes underwent multimodal ex vivo imaging, including SD OCT, before processing for high-resolution histologic analysis. MAIN OUTCOME MEASURES: Presence of layered, hyperreflective sub-RPE lines, qualitative analysis of their change in appearance over time with SD OCT, histologic correlates of these lines, and associated findings within surrounding tissues. RESULTS: Sixteen of 230 eyes of patients (7.0%) and 2 of 40 donor eyes (5.0%) with neovascular AMD had layered, hyperreflective sub-RPE lines on SD OCT imaging. These appeared as refractile, yellow-gray exudates on color imaging and as hyperreflective lesions on NIR. In all 16 patient eyes, the onion sign persisted in follow-up for up to 5 years, with fluctuations in the abundance of lines and association with intraretinal hyperreflective foci. Patients with the onion sign disproportionately were taking cholesterol-lowering medications (P=0.025). Histologic analysis of 2 donor eyes revealed that the hyperreflective lines correlated with clefts created by extraction of cholesterol crystals during tissue processing. The fluid surrounding the crystals contained lipid, yet was distinct from oily drusen. Intraretinal hyperreflective foci correlated with intraretinal RPE and lipid-filled cells of probable monocytic origin. CONCLUSIONS: Persistent and dynamic, the onion sign represents sub-RPE cholesterol crystal precipitation in an aqueous environment. The frequency of the onion sign in neovascular AMD in a referral practice and a pathology archive is 5% to 7%. Associations include use of cholesterol-lowering medication and intraretinal hyperreflective foci attributable to RPE cells and lipid-filled cells of monocyte origin

Optical coherence tomography and optical coherence tomography angiography in uveitis : a review

Optical coherence tomography (OCT) has dramatically changed the understanding and management of uveitis and other ocular conditions. Currently, OCT angiography (OCTA) combines structural information with the visualization of blood flow within the imaged area. The aim of this review is to present the basic principles of OCT and OCTA interpretation and to investigate the role of these imaging techniques in the diagnosis and management of uveitis. Common complications of intraocular inflammation such as macular oedema and inflammatory choroidal neovascularization are often diagnosed and followed with OCT/OCTA scans. However, uveitis specialists can obtain much more information from tomographic scans. This review provides a comprehensive description of typical OCT/OCTA findings characterizing different ocular structures in uveitis, proceeding from the cornea to the choroid. A careful interpretation of OCT/OCTA images can help in the differential diagnosis, the prediction of clinical outcomes, and the follow-up of patients with uveitis

Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence

INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment worldwide. The endpoint of AMD, both in its dry or wet form, is macular atrophy (MA) which is characterized by the permanent loss of the RPE and overlying photoreceptors either in dry AMD or in wet AMD. A recognized unmet need in AMD is the early detection of MA development. AREAS COVERED: Artificial Intelligence (AI) has demonstrated great impact in detection of retinal diseases, especially with its robust ability to analyze big data afforded by ophthalmic imaging modalities, such as color fundus photography (CFP), fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). Among these, OCT has been shown to have great promise in identifying early MA using the new criteria in 2018. EXPERT OPINION: There are few studies in which AI-OCT methods have been used to identify MA; however, results are very promising when compared to other imaging modalities. In this paper, we review the development and advances of ophthalmic imaging modalities and their combination with AI technology to detect MA in AMD. In addition, we emphasize the application of AI-OCT as an objective, cost-effective tool for the early detection and monitoring of the progression of MA in AMD

Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence

INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment worldwide. The endpoint of AMD, both in its dry or wet form, is macular atrophy (MA) which is characterized by the permanent loss of the RPE and overlying photoreceptors either in dry AMD or in wet AMD. A recognized unmet need in AMD is the early detection of MA development. AREAS COVERED: Artificial Intelligence (AI) has demonstrated great impact in detection of retinal diseases, especially with its robust ability to analyze big data afforded by ophthalmic imaging modalities, such as color fundus photography (CFP), fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). Among these, OCT has been shown to have great promise in identifying early MA using the new criteria in 2018. EXPERT OPINION: There are few studies in which AI-OCT methods have been used to identify MA; however, results are very promising when compared to other imaging modalities. In this paper, we review the development and advances of ophthalmic imaging modalities and their combination with AI technology to detect MA in AMD. In addition, we emphasize the application of AI-OCT as an objective, cost-effective tool for the early detection and monitoring of the progression of MA in AMD

Progression of Retinal Pigment Epithelial Atrophy in Antiangiogenic Therapy of Neovascular Age-Related Macular Degeneration

PurposeTo monitor retinal pigment epithelial (RPE) atrophy progression during antiangiogenic therapy of neovascular age-related macular degeneration (AMD) over 2 years using polarization-sensitive optical coherence tomography (OCT).DesignProspective interventional case series.Methodssetting: Clinical practice. study population: Thirty patients (31 eyes) with treatment-naïve neovascular AMD. observation procedures: Standard intravitreal therapy (0.5 mg ranibizumab) was administered monthly during the first year and pro re nata (PRN; as-needed) during the second year. Spectral-domain (SD) OCT and polarization-sensitive OCT (selectively imaging the RPE) examinations were performed at baseline and at 1, 3, 6, 12, and 24 months using a standardized protocol. RPE-related changes were evaluated using a semi-automated polarization-sensitive OCT segmentation algorithm and correlated with SD OCT and fundus autofluorescence (FAF) findings. main outcome measures: RPE response, geographic atrophy (GA) progression.ResultsAtrophic RPE changes included RPE thinning, RPE porosity, focal RPE atrophy, and development of GA. Early RPE loss (ie, RPE porosity, focal atrophy) increased progressively during initial monthly treatment and remained stable during subsequent PRN-based therapy. GA developed in 61% of eyes at month 24. Mean GA area increased from 0.77 mm2 at 12 months to 1.10 mm2 (standard deviation = 1.09 mm2) at 24 months. Reactive accumulation of RPE-related material at the lesion borders increased until month 3 and subsequently decreased.ConclusionsProgressive RPE atrophy and GA developed in the majority of eyes. RPE migration signifies certain RPE plasticity. Polarization-sensitive OCT specifically images RPE-related changes in neovascular AMD, contrary to conventional imaging methods. Polarization-sensitive OCT allows for precisely monitoring the sequence of RPE-related morphologic changes