scholarly journals Machine Learning of the Progression of Intermediate Age-Related Macular Degeneration Based on OCT Imaging

2017 ◽  
Vol 58 (6) ◽  
pp. BIO141 ◽  
Author(s):  
Hrvoje Bogunovic ◽  
Alessio Montuoro ◽  
Magdalena Baratsits ◽  
Maria G. Karantonis ◽  
Sebastian M. Waldstein ◽  
...  
Keyword(s):  
Machine Learning ◽  
Macular Degeneration ◽  
Age Related Macular Degeneration ◽  
Age Related ◽  
Oct Imaging

Assessment of CFH and HTRA1 polymorphisms in age-related macular degeneration using classic and machine-learning approaches

2020 ◽  
Vol 41 (6) ◽  
pp. 539-547
Author(s):  
Antonieta Martínez-Velasco ◽  
Andric C. Perez-Ortiz ◽  
Bani Antonio-Aguirre ◽  
Lourdes Martínez-Villaseñor ◽  
Esmeralda Lira-Romero ◽  
...  
Keyword(s):  
Machine Learning ◽  
Macular Degeneration ◽  
Age Related Macular Degeneration ◽  
Learning Approaches ◽  
Age Related

scholarly journals The Relevance of Cataract as a Risk Factor for Age-Related Macular Degeneration: A Machine Learning Approach

2019 ◽  
Vol 9 (24) ◽  
pp. 5550
Author(s):  
Antonieta Martínez-Velasco ◽  
Lourdes Martínez-Villaseñor ◽  
Luis Miralles-Pechuán ◽  
Andric C. Perez-Ortiz ◽  
Juan C. Zenteno ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factor ◽  
Macular Degeneration ◽  
Significant Risk ◽  
Age Related Macular Degeneration ◽  
Supervised Machine Learning ◽  
Current Debate ◽  
Learning Approach ◽  
Age Related ◽  
Machine Learning Approach

Age-related macular degeneration (AMD) is the leading cause of visual dysfunction and irreversible blindness in developed countries and a rising cause in underdeveloped countries. There is a current debate on whether or not cataracts are significant risk factors for AMD development. In particular, research regarding this association is so far inconclusive. For this reason, we aimed to employ here a machine-learning approach to analyze the relevance and importance of cataracts as a risk factor for AMD in a large cohort of Hispanics from Mexico. We conducted a nested case control study of 119 cataract cases and 137 healthy unmatched controls focusing on clinical data from electronic medical records. Additionally, we studied two single nucleotide polymorphisms in the CFH gene previously associated with the disease in various populations as positive control for our method. We next determined the most relevant variables and found the bivariate association between cataracts and AMD. Later, we used supervised machine-learning methods to replicate these findings without bias. To improve the interpretability, we detected the five most relevant features and displayed them using a bar graph and a rule-based tree. Our findings suggest that bilateral cataracts are not a significant risk factor for AMD development among Hispanics from Mexico.

Quantitative SD-OCT Imaging Biomarkers as Indicators of Age-Related Macular Degeneration Progression

2014 ◽  
Vol 55 (11) ◽  
pp. 7093 ◽  
Author(s):  
Luis de Sisternes ◽  
Noah Simon ◽  
Robert Tibshirani ◽  
Theodore Leng ◽  
Daniel L. Rubin
Keyword(s):  
Macular Degeneration ◽  
Age Related Macular Degeneration ◽  
Imaging Biomarkers ◽  
Age Related ◽  
Oct Imaging ◽  
Sd Oct

scholarly journals Clinically visible progression indicators in age-related macular degeneration are transdifferentiated retinal pigment epithelium

2021 ◽  
Author(s):  
Dongfeng Cao ◽  
Belinda Leong ◽  
Jeffrey D. Messinger ◽  
Deepayan Kar ◽  
Thomas Ach ◽  
...  
Keyword(s):  
Retinal Pigment Epithelium ◽  
Macular Degeneration ◽  
Pigment Epithelium ◽  
Retinal Pigment ◽  
Age Related Macular Degeneration ◽  
Risk Indicators ◽  
Muller Glia ◽  
Müller Glia ◽  
Age Related ◽  
Oct Imaging

AbstractAge-related macular degeneration (AMD) is a common sight-threatening disease of older adults and treatment options are needed. Abnormalities of retinal pigment epithelium (RPE), supporting cells to photoreceptors and capillaries, are a hallmark. Clinical optical coherence tomography (OCT) imaging reveals hyperreflective foci (HRF) that confer risk for end-stage disease and are attributed to ectopic out-of-layer RPE. Using longitudinal OCT imaging of AMD patients, we demonstrate that the trajectory of one HRF form, RPE plume, parallels the retinal Henle fiber layer. Histology shows fully pigmented cells approaching and contacting retinal capillaries with RPE organelles dispersing along Müller glia columns. We used immunohistochemistry and a system of morphologic phenotypes to assess RPE functional repertoire in AMD. RPE corresponding to HRF loses immunoreactivity for retinoid processing proteins RPE65 and CRALBP, and gains immunoreactivity for immune cell markers CD68 and CD163. Müller glia retain CRALBP immunoreactivity. Gain- and loss-of-function for RPE starts with individual in-layer cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may contribute to slowed rod vision while Müller glia sustain cone vision. Ectopic RPE corresponding to HRF are emblematic of widespread transdifferentiation, motivating treatments targeting AMD pathology earlier than the initiation of atrophy. Data can propel new biomarkers and therapeutic strategies for AMD.One Sentence SummaryIn age-related macular degeneration retinal pigment epithelial cells transdifferentiate and migrate into the retina where they are clinically visible progression risk indicators.

scholarly journals Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration

2018 ◽  
Vol 2 (1) ◽  
pp. 24-30 ◽  
Author(s):  
Ursula Schmidt-Erfurth ◽  
Hrvoje Bogunovic ◽  
Amir Sadeghipour ◽  
Thomas Schlegl ◽  
Georg Langs ◽  
...  
Keyword(s):  
Machine Learning ◽  
Macular Degeneration ◽  
Prognostic Value ◽  
Age Related Macular Degeneration ◽  
Imaging Biomarkers ◽  
Age Related

scholarly journals Topological analysis of single-cell data reveals shared glial landscape of macular degeneration and neurodegenerative diseases

2021 ◽  
Author(s):  
Manik Kuchroo ◽  
Marcello DiStasio ◽  
Eda Calapkulu ◽  
Maryam Ige ◽  
Le Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Multiple Sclerosis ◽  
Alzheimer’S Disease ◽  
Macular Degeneration ◽  
Single Cell ◽  
Topological Analysis ◽  
Age Related Macular Degeneration ◽  
Learning Approach ◽  
Age Related ◽  
Machine Learning Approach

1One Sentence SummaryA novel topological machine learning approach applied to single-nucleus RNA sequencing from human retinas with age-related macular degeneration identifies interacting disease phase-specific glial activation states shared with Alzheimer’s disease and multiple sclerosis.2AbstractNeurodegeneration occurs in a wide range of diseases, including age-related macular degeneration (AMD), Alzheimer’s disease (AD), and multiple sclerosis (MS), each with distinct inciting events. To determine whether glial transcriptional states are shared across phases of degeneration, we sequenced 50,498 nuclei from the retinas of seven AMD patients and six healthy controls, generating the first single-cell transcriptomic atlas of AMD. We identified groupings of cells implicated in disease pathogenesis by applying a novel topologically-inspired machine learning approach called ‘diffusion condensation.’ By calculating diffusion homology features and performing persistence analysis, diffusion condensation identified activated glial states enriched in the early phases of AMD, AD, and MS as well as an AMD-specific proangiogenic astrocyte state promoting pathogenic neovascularization in advanced AMD. Finally, by mapping the expression of disease-associated genes to glial states, we identified key signaling interactions creating hypotheses for therapeutic intervention. Our topological analysis identified an integrated disease-phase specific glial landscape that is shared across neurodegenerative conditions affecting the central nervous system.

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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wolf-Dieter Vogl ◽  
Hrvoje Bogunović ◽  
Sebastian M. Waldstein ◽  
Sophie Riedl ◽  
Ursula Schmidt-Erfurth
Keyword(s):  
Optical Coherence Tomography ◽  
Macular Degeneration ◽  
Reference Frame ◽  
Age Related Macular Degeneration ◽  
Disease Stage ◽  
Optical Coherence ◽  
Common Reference ◽  
Age Related ◽  
Oct Imaging ◽  
Spatio Temporal

AbstractAge-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). We included 10,040 OCT volumes of 518 eyes with intermediate AMD acquired according to a standardized protocol in monthly intervals over two years. Two independent masked retina specialists determined the time of conversion to MNV or MA. All scans were aligned to a common reference frame by intra-patient and inter-patient registration. Automated segmentations of retinal layers and the choroid were computed and en-face maps were transformed into the common reference frame. Population maps were constructed in the subgroups converting to MNV (n=135), MA (n=50) and in non-progressors (n=333). Topographically resolved maps of changes were computed and tested for statistical significant differences. The development over time was analysed by a joint model accounting for longitudinal and right-censoring aspect. Significantly enhanced thinning of the outer nuclear layer (ONL) and retinal pigment epithelium (RPE)–photoreceptorinner segment/outer segment (PR-IS/OS) layers within the central 3 mm and a faster thinning speed preceding conversion was documented for MA progressors. Converters to MNV presented an accelerated thinning of the choroid and appearance changes in the choroid prior to MNV onset. The large-scale automated image analysis allowed us to distinctly assess the progression of morphologic changes in intermediate AMD based on conventional OCT imaging. Distinct topographic and temporal patterns allow to prospectively determine eyes with risk of progression and thereby greatly improving early detection, prevention and development of novel therapeutic strategies.

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