1. Articles from Ursula Schmidt-Erfurth

    1-24 of 126 1 2 3 4 5 6 »
    1. The effect of pegcetacoplan treatment on photoreceptor maintenance in geographic atrophy monitored by AI-based OCT analysis

      The effect of pegcetacoplan treatment on photoreceptor maintenance in geographic atrophy monitored by AI-based OCT analysis

      Purpose: To investigate the therapeutic effect of intravitreal pegcetacoplan on the inhibition of photoreceptor (PR) loss and thinning in geographic atrophy (GA) on conventional spectral domain-optical coherence tomography (SD-OCT) imaging by deep learning-based automated PR quantification. Design: Post-hoc analysis of a prospective, multicenter, randomized, sham-controlled, masked phase II trial investigating the safety and efficacy of pegcetacoplan for the treatment of GA due to age-related macular degeneration. Participants: Study eyes of 246 patients, randomized 1:1:1 to monthly (AM), bimonthly (AEOM) and sham (SM) treatment. Methods: We performed fully automated, deep learning-based segmentation of retinal pigment epithelium (RPE) loss and ...

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    2. Evaluation of neuroretinal integrity in optical coherence tomography-graded eyes with partial-thickness macular holes

      Evaluation of neuroretinal integrity in optical coherence tomography-graded eyes with partial-thickness macular holes

      Purpose: To evaluate neuroretinal integrity in different subtypes of optical coherence tomography (OCT)-graded partial-thickness macular holes. Methods: Fovea-centred SD-OCT images (Cirrus, Carl Zeiss Meditec AG; Spectralis, Heidelberg Engineering GmbH) and visual acuity (VA) acquired at every visit were analysed by two retina specialists retrospectively in 71 eyes of 65 patients. Partial-thickness macular holes were classified as lamellar macular hole (LMH), epiretinal membrane foveoschisis (ERMF) or macular pseudohole (MPH). Results: Lamellar macular hole, ERMF and MPH were diagnosed in 33 (47%), 31 (43%) and 7 (10%) eyes with a VA of 0.18 ± 0.25, 0.15 ± 0.2, and ...

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    3. Robust Fovea Detection in Retinal OCT Imaging using Deep Learning

      Robust Fovea Detection in Retinal OCT Imaging using Deep Learning

      The fovea centralis is an essential landmark in the retina where the photoreceptor layer is entirely composed of cones responsible for sharp, central vision. The localization of this anatomical landmark in optical coherence tomography (OCT) volumes is important for assessing visual function correlates and treatment guidance in macular disease. In this study, the "PRE U-net" is introduced as a novel approach for a fully automated fovea centralis detection, addressing the localization as a pixel-wise regression task. 2D B-scans are sampled from each image volume and are concatenated with spatial location information to train the deep network. A total of 5586 ...

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    4. Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning

      Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning

      Purpose To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomography (AS-OCT): The intraocular lens (IOL), the retrolental space (IOL to the posterior lens capsule) and Berger's space (BS; posterior capsule to the anterior hyaloid membrane). Methods An artificial intelligence (AI) approach based on a deep learning model to automatically segment the IOL, the retrolental space, and BS in AS-OCT, was trained using annotations from an experienced clinician. The training, validation and test set consisted of 92 cross-sectional OCT slices, acquired in 47 visits from 41 eyes. Annotations from ...

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    5. Linking Function and Structure with ReSenseNet: Predicting Retinal Sensitivity from Optical Coherence Tomography using Deep Learning

      Linking Function and Structure with ReSenseNet: Predicting Retinal Sensitivity from Optical Coherence Tomography using Deep Learning

      Purpose: Currently used measures of retinal function are limited by being subjective, non-localized and/or taxing for patients. To address these limitations, we sought to develop and evaluate a deep learning (DL) method to automatically predict a functional endpoint (retinal sensitivity) from structural optical coherence tomography (OCT) images. Design: Retrospective cross-sectional study. Subjects: In total, 714 volumes of 289 patients were used in this study. Methods: A novel deep learning algorithm was developed to automatically predict a comprehensive retinal sensitivity map from OCTs. 463 SD-OCT volumes from 174 patients and their corresponding microperimetry examinations (Nidek MP-1) were used for development ...

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    6. Optical coherence tomography in multiple sclerosis: A 3-year prospective multicenter study

      Optical coherence tomography in multiple sclerosis: A 3-year prospective multicenter study

      Objective: To evaluate changes over 3 years in the thickness of inner retinal layers including the peripapillary retinal nerve fiber layer (pRNFL), and combined macular ganglion cell and inner plexiform layers (mGCIPL), in individuals with relapsing-remitting multiple sclerosis (RRMS) versus healthy controls; to determine whether optical coherence tomography (OCT) is sufficiently sensitive and reproducible to detect small degrees of neuroaxonal loss over time that correlate with changes in brain volume and disability progression as measured by the Expanded Disability Status Scale (EDSS). Methods: Individuals with RRMS from 28 centers (n = 333) were matched with 64 healthy participants. OCT scans were ...

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    7. Optical coherence tomography in multiple sclerosis: A 3-year prospective multicenter study

      Optical coherence tomography in multiple sclerosis: A 3-year prospective multicenter study

      Objective: To evaluate changes over 3 years in the thickness of inner retinal layers including the peripapillary retinal nerve fiber layer (pRNFL), and combined macular ganglion cell and inner plexiform layers (mGCIPL), in individuals with relapsing-remitting multiple sclerosis (RRMS) versus healthy controls; to determine whether optical coherence tomography (OCT) is sufficiently sensitive and reproducible to detect small degrees of neuroaxonal loss over time that correlate with changes in brain volume and disability progression as measured by the Expanded Disability Status Scale (EDSS). Methods: Individuals with RRMS from 28 centers (n = 333) were matched with 64 healthy participants. OCT scans were ...

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    8. Assessment of Detailed Photoreceptor Structure and Retinal Sensitivity in Diabetic Macular Ischemia Using Adaptive Optics-OCT and Microperimetry

      Assessment of Detailed Photoreceptor Structure and Retinal Sensitivity in Diabetic Macular Ischemia Using Adaptive Optics-OCT and Microperimetry

      Purpose: The purpose of this study was to assess density and morphology of cone photoreceptors (PRs) and corresponding retinal sensitivity in ischemic compared to nonischemic retinal capillary areas of diabetic eyes using adaptive optics optical coherence tomography (AO-OCT) and microperimetry (MP). Methods: In this cross-sectional, observational study five eyes of four patients (2 eyes with proliferative diabetic retinopathy (DR) and 3 eyes moderate nonproliferative DR) were included. PR morphology and density was manually assessed in AO-OCT en face images both at the axial position of the inner-segment outer segment (IS/OS) and cone outer segment tips (COSTs). Retinal sensitivity was ...

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    9. Fundus autofluorescence and optical coherence tomography biomarkers associated with the progression of geographic atrophy secondary to age-related macular degeneration

      Fundus autofluorescence and optical coherence tomography biomarkers associated with the progression of geographic atrophy secondary to age-related macular degeneration

      Objectives To investigate the impact of qualitatively graded and deep learning quantified imaging biomarkers on growth of geographic atrophy (GA) secondary to age-related macular degeneration. Methods This prospective study included 1062 visits of 181 eyes of 100 patients with GA. Spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) images were acquired at each visit. Hyperreflective foci (HRF) were quantitatively assessed in SD-OCT volumes using a validated deep learning algorithm. FAF images were graded for FAF patterns, subretinal drusenoid deposits (SDD), GA lesion configuration and atrophy enlargement. Linear mixed models were calculated to investigate associations between all parameters and GA ...

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    10. Impact of large choroidal vessels on choriocapillaris flow deficit analyses in optical coherence tomography angiography

      Impact of large choroidal vessels on choriocapillaris flow deficit analyses in optical coherence tomography angiography

      Purpose To investigate the impact of large choroidal vessels (LCV) on Choriocapillaris (CC) flow deficit (FD) analyses with swept-source optical coherence tomography angiography (SS-OCTA) Design Prospective, cross-sectional study. Methods Macular 6x6mm SS-OCTA scans were obtained from intermediate age-related macular degeneration (iAMD) and healthy eyes. Images were captured and processed according to most common standards and analyzed for percentage of flow-deficits (FD%) within four 1x1mm squares at the corners of each image. Choroidal thickness (CT), iris color and refraction error were considered as potential influential factors for LCV visibility. A linear mixed model and logistic regression models were calculated for statistical ...

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    11. Deep Learning–Based Automated Optical Coherence Tomography Segmentation in Clinical Routine: Getting Closer

      Deep Learning–Based Automated Optical Coherence Tomography Segmentation in Clinical Routine: Getting Closer

      Recently, many ophthalmologists have heard the keywords artificial intelligence , machine learning , deep learning , and automatization at every conference and keynote lecture and seen them in every ophthalmology journal. 1 Many studies 1 have evaluated the use of such algorithms on large retrospective data sets—primarily on color fundus photographs at first, then on optical coherence tomography (OCT) images as well. Most of these have been study data sets with standardized and well-structured imaging protocols and reading center image collections with a predefined protocol, and therefore of good quality. However, how functional will algorithms be in a busy clinical routine? Can ...

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    12. Spatio-temporal alterations in retinal and choroidal layers in the progression of age-related macular degeneration (AMD) in optical coherence tomography

      Spatio-temporal alterations in retinal and choroidal layers in the progression of age-related macular degeneration (AMD) in optical coherence tomography

      Age-related macular degeneration (AMD) is the predominant cause of vision loss in the elderly with a major impact on ageing societies and healthcare systems. A major challenge in AMD management is the difficulty to determine the disease stage, the highly variable progression speed and the risk of conversion to advanced AMD, where irreversible functional loss occurs. In this study we developed an optical coherence tomography (OCT) imaging based spatio-temporal reference frame to characterize the morphologic progression of intermediate age-related macular degeneration (AMD) and to identify distinctive patterns of conversion to the advanced stages macular neovascularization (MNV) and macular atrophy (MA ...

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    13. Three-dimensional composition of the photoreceptor cone layers in healthy eyes using adaptive-optics optical coherence tomography (AO-OCT)

      Three-dimensional composition of the photoreceptor cone layers in healthy eyes using adaptive-optics optical coherence tomography (AO-OCT)

      Purpose To assess the signal composition of cone photoreceptors three-dimensionally in healthy retinas using adaptive optics optical coherence tomography (AO-OCT). Methods Study population. Twenty healthy eyes of ten subjects (age 23 to 67). Procedures. After routine ophthalmological assessments, eyes were examined using AO-OCT. Three-dimensional volumes were acquired at 2.5° and 6.5° foveal eccentricity in four main meridians (superior, nasal, inferior, temporal). Cone densities and signal compositions were investigated in four different planes: the cone inner segment outer segment junction (IS/OS), the cone outer segment combined with the IS/OS (ISOS+), the cone outer segment tips (COST) and ...

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    14. Three-dimensional assessment of para- and perifoveal photoreceptor densities and the impact of meridians and age in healthy eyes with adaptive-optics optical coherence tomography (AO-OCT)

      Three-dimensional assessment of para- and perifoveal photoreceptor densities and the impact of meridians and age in healthy eyes with adaptive-optics optical coherence tomography (AO-OCT)

      An adaptive optics optical coherence tomography (AO-OCT) system is used to assess sixty healthy eyes of thirty subjects (age 22 to 75) to evaluate how the outer retinal layers, foveal eccentricity and age effect the mean cone density. The cone mosaics of different retinal planes (the cone inner segment outer segment junction (IS/OS), the cone outer segment combined with the IS/OS (ISOS+), the cone outer segment tips (COST), and the full en-face plane (FEF)) at four main meridians (superior, nasal, inferior, temporal) and para- and perifoveal eccentricities (ecc 2.5° and 6.5°) were analyzed quantitatively. The mean ...

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    15. Deliberations of an International Panel of Experts on OCTA Nomenclature of nAMD

      Deliberations of an International Panel of Experts on OCTA Nomenclature of nAMD

      A panel of imaging experts was assembled to review neovascular age-related macular degeneration optical coherence tomography angiography descriptors published to date, and test agreement on use of these terms, which was found to be low. Optical coherence tomography angiography (OCTA) has been used to identify and characterize macular neovascularization (MNV) secondary to age-related macular degeneration (AMD). 1-4 Many studies have explored OCTA morphological features of MNV that might serve as biomarkers to assess disease activity and response to treatment. 1-6 The proliferation of studies however has resulted in an OCTA terminology that has been variable and inconsistent. To address inconsistency ...

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    16. Intraretinal microvascular changes after ERM and ILM peeling using SSOCTA

      Intraretinal microvascular changes after ERM and ILM peeling using SSOCTA

      Background To prospectively investigate retinal vascular changes in patients undergoing epiretinal membrane (ERM) and internal limiting membrane (ILM) peeling using swept source optical coherence tomography angiography (SSOCTA). Methods Consecutive patients were grouped based on ERM severity and followed using SSOCTA up to month 3 after surgical intervention. Superficial and deep foveal avascular zone (s/dFAZ) as well as foveal and parafoveal vessel density (VD) were correlated with ERM severity and visual acuity. Differences between groups were evaluated. Results Significant correlations were found between ERM severity and baseline sFAZ, dFAZ and best corrected visual acuity (BCVA), central retinal subfield thickness (CST ...

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    17. Analysis of retinal nerve fiber layer birefringence in patients with glaucoma and diabetic retinopathy by polarization sensitive OCT

      Analysis of retinal nerve fiber layer birefringence in patients with glaucoma and diabetic retinopathy by polarization sensitive OCT

      The retinal nerve fiber layer (RNFL) is a fibrous tissue that shows form birefringence. This optical tissue property is related to the microstructure of the nerve fiber axons that carry electrical signals from the retina to the brain. Ocular diseases that are known to cause neurologic changes, like glaucoma or diabetic retinopathy (DR), might alter the birefringence of the RNFL, which could be used for diagnostic purposes. In this pilot study, we used a state-of-the-art polarization sensitive optical coherence tomography (PS-OCT) system with an integrated retinal tracker to analyze the RNFL birefringence in patients with glaucoma, DR, and in age-matched ...

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    18. Atlas of Human Retinal Pigment Epithelium Organelles Significant for Clinical Imaging

      Atlas of Human Retinal Pigment Epithelium Organelles Significant for Clinical Imaging

      Purpose : To quantify organelles impacting imaging in the cell body and intact apical processes of human retinal pigment epithelium (RPE), including melanosomes, lipofuscin–melanolipofuscin (LM), mitochondria, and nuclei. Methods : A normal perifovea of a 21-year-old white male was preserved after rapid organ recovery. An aligned image stack was generated using serial block-face scanning electron microscopy and was annotated by expert readers (TrakEM, ImageJ). Acquired measures included cell body and nuclear volume ( n = 17); organelle count in apical processes ( n = 17) and cell bodies ( n = 8); distance of cell body organelles along a normalized apical–basal axis ( n = 8); and dimensions ...

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    19. Predicting Progression of Age-Related Macular Degeneration Using Optical Coherence Tomography and Fundus Photography

      Predicting Progression of Age-Related Macular Degeneration Using Optical Coherence Tomography and Fundus Photography

      Purpose To compare the performance of automatically quantified optical coherence tomography (OCT) imaging biomarkers and conventional risk factors manually graded on color fundus photographs (CFP) for predicting progression to late age-related macular degeneration (AMD). Design Longitudinal observational study. Participants 280 eyes from 140 participants with bilateral large drusen. Methods All participants underwent OCT and CFP imaging at baseline and were then reviewed at six-monthly intervals to determine progression to late AMD. CFPs were manually graded and OCT scans underwent automated image analyses to quantify risk factors and imaging biomarkers respectively based on drusen and AMD pigmentary abnormalities. Four predictive models ...

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    20. End-to-end deep learning model for predicting treatment requirements in neovascular AMD from longitudinal retinal OCT imaging

      End-to-end deep learning model for predicting treatment requirements in neovascular AMD from longitudinal retinal OCT imaging

      Neovascular age-related macular degeneration (nAMD) is nowadays successfully treated with anti-VEGF substances, but interindividual treatment requirements are vastly heterogeneous and currently poorly plannable resulting in suboptimal treatment frequency. Optical coherence tomography (OCT) with its 3D high-resolution imaging serves as a companion diagnostic to anti-VEGF therapy. This creates a need for building predictive models using automated image analysis of OCT scans acquired during the treatment initiation phase. We propose such a model based on deep learning (DL) architecture, comprised of a densely connected neural network (DenseNet) and a recurrent neural network (RNN), trainable end-to-end. The method starts by sampling several 2D-images ...

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    21. Computerized device and method for processing image data

      Computerized device and method for processing image data

      A computerized device for processing image data is proposed. The computerized device comprises a receiving unit which is configured to receive optical coherence tomography data of a of a tissue, in particular of a retina, a providing unit which is configured to provide a convolutional neural network for processing the optical coherence tomography data, and a processing unit which is configured to process the received optical coherence tomography data using the convolutional neural network for identifying at least one certain object in the tissue.

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    22. Subretinal Drusenoid Deposits and Photoreceptor Loss Detecting Global and Local Progression of Geographic Atrophy by SD-OCT Imaging

      Subretinal Drusenoid Deposits and Photoreceptor Loss Detecting Global and Local Progression of Geographic Atrophy by SD-OCT Imaging

      Purpose : To investigate the impact of subretinal drusenoid deposits (SDD) and photoreceptor integrity on global and local geographic atrophy (GA) progression. Methods : Eighty-three eyes of 49 patients, aged 50 years and older with GA secondary to age-related macular degeneration (AMD), were prospectively included in this study. Participants underwent spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) imaging at baseline and after 12 months. The junctional zone and presence of SDD were delineated on SD-OCT and FAF images. Linear mixed models were calculated to investigate the association between GA progression and the junctional zone area, baseline GA area, age, global ...

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    23. Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography

      Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography

      Importance The morphologic changes and their pathognomonic distribution in progressing age-related macular degeneration (AMD) are not well understood. Objectives To characterize the pathognomonic distribution and time course of morphologic patterns in AMD and to quantify changes distinctive for progression to macular neovascularization (MNV) and macular atrophy (MA). Design, Setting, and Participants This cohort study included optical coherence tomography (OCT) volumes from study participants with early or intermediate AMD in the fellow eye in the HARBOR (A Study of Ranibizumab Administered Monthly or on an As-needed Basis in Patients With Subfoveal Neovascular Age-Related Macular Degeneration) trial. Patients underwent imaging monthly for ...

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    24. Automated Quantification of Photoreceptor alteration in macular disease using Optical Coherence Tomography and Deep Learning

      Automated Quantification of Photoreceptor alteration in macular disease using Optical Coherence Tomography and Deep Learning

      Diabetic macular edema (DME) and retina vein occlusion (RVO) are macular diseases in which central photoreceptors are affected due to pathological accumulation of fluid. Optical coherence tomography allows to visually assess and evaluate photoreceptor integrity, whose alteration has been observed as an important biomarker of both diseases. However, the manual quantification of this layered structure is challenging, tedious and time-consuming. In this paper we introduce a deep learning approach for automatically segmenting and characterising photoreceptor alteration. The photoreceptor layer is segmented using an ensemble of four different convolutional neural networks. En-face representations of the layer thickness are produced to characterize ...

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