Progressive Eye Disease Research Articles

Progression of eye disease over 15 years in a patient with mucopolysaccharidosis type VI on enzyme replacement therapy

We present a case report of a 24-year-old Caucasian man with mucopolysaccharidosis (MPS) type VI (Maroteaux-Lamy) who has documented progression of visual loss and corneal clouding over 18 years of...

Machine learning approach for detection of keratoconus

Keratoconus is a progressive eye disease and it should be detected in early stage, to avert probable refractive surgery that could develop ecstasies. In this the authors proposes a new computer aided diagnosis model based on Support Vector Machine (SVM) learning to detect the early stage of keratoconus using the available topographic, pachymetric and aberrometry parameters of patients with keratoconus, subclinical keratoconus and normal corneas. The proposed SVM produces 91.8% accuracy with 94.2% sensitivity, 97.5% specificity for classification of early keratoconus from normal; 100% accuracy with 100%, 100% of sensitivity and specificity respectively for classification of early keratoconus from subclinical keratoconus.

The Gambia National Eye Health Survey 2019: survey protocol

Two national surveys of vision impairment and blindness were undertaken in The Gambia in 1986 and 1996. These provided data for the inception of The Gambia’s National Eye Health Programme (NEHP) within the Ministry of Health and Social Welfare. There have been important developments in the eye health services provided by the NEHP in the last 20 years. At the same time, the population has also undergone major demographic changes that may have led to substantial changes in the burden of eye disease. We conducted a National Eye Health Survey of vision impairment, blindness and its comorbidities in adults in The Gambia in 2019. We examined a nationally representative population-based sample of adults 35 years and above to permit direct comparison with the data available from the previous surveys. Alongside a comprehensive vision and eye examination, the survey provides nationally representative data on important comorbidities in this population: diabetes, hypertension, obesity, hearing impairment, disability and mental health. Secondly, it estimates access to assistive technologies and eye health services. Thirdly, it is powered to allow a five-year follow up cohort study to measure the incidence and progression of eye disease.

Antioxidant Defenses in the Human Eye: A Focus on Metallothioneins.

The human eye, the highly specialized organ of vision, is greatly influenced by oxidants of endogenous and exogenous origin. Oxidative stress affects all structures of the human eye with special emphasis on the ocular surface, the lens, the retina and its retinal pigment epithelium, which are considered natural barriers of antioxidant protection, contributing to the onset and/or progression of eye diseases. These ocular structures contain a complex antioxidant defense system slightly different along the eye depending on cell tissue. In addition to widely studied enzymatic antioxidants, including superoxide dismutase, glutathione peroxidase, catalase, peroxiredoxins and selenoproteins, inter alia, metallothioneins (MTs) are considered antioxidant proteins of growing interest with further cell-mediated functions. This family of cysteine rich and low molecular mass proteins captures and neutralizes free radicals in a redox-dependent mechanism involving zinc binding and release. The state of the art of MTs, including the isoforms classification, the main functions described to date, the Zn-MT redox cycle as antioxidant defense system, and the antioxidant activity of Zn-MTs in the ocular surface, lens, retina and its retinal pigment epithelium, dependent on the number of occupied zinc-binding sites, will be comprehensively reviewed.

The Impact of the COVID-19 Pandemic Lockdown Measures on Diabetic Retinopathy Services in the East Kent Area of the United Kingdom - A Special Focus on the Pregnant Diabetic

The impact of extended lockdown measures, aimed at controlling the COVID-19 viral spread, are starting to be evaluated in many world regions. We have evaluated the impact of lockdown measures on diabetic retinopathy services in our region, especially as it affects pregnant diabetics who are at risk of diabetic eye disease progression. As services start to return, the potential impact of absent diabetic eye screening and intervention services over a 3-month period is envisaged to be seen. Coverage about this topic of interest is scanty, hence its timeliness.

Correlations Between Choriocapillaris and Choroidal Measurements and the Growth of Geographic Atrophy Using Swept Source OCT Imaging

Correlations among enlargement rates (ERs) of geographic atrophy (GA) and choriocapillaris (CC) flow deficits (FDs), mean choroidal thickness (MCT), and choroidal vascularity index (CVI) were investigated using swept source-optical coherence tomography (SS-OCT) in age-related macular degeneration (AMD). A retrospective review of prospective, observational case series. Eyes with GA from AMD were imaged with SS-OCT using 6× 6-mm scan pattern. GA lesions were identified and measured using customized en face structural images, and annual square root ERs of GA were calculated. At baseline, choriocapillaris FDs from different regions outside the GA were measured, and MCT and CVI from the entire scan area were measured. All measurements were performed using previously published and validated algorithms. A total of 38 eyes from 27 patients were included. The CC FDs within each region around GA lesions were highly correlated with ERs of GA (all P < .005). CVI inside the GA region was correlated with the ERs (P= .03), whereas other choroidal measurements had no significant correlation with the ERs of GA (P > .06). Statistically significant correlations were found between the ERs of GA and CC percentage of FD (FD%) from the entire scan region outside the GA and not just the region immediately adjacent to the GA. These results suggest that abnormal CC perfusion throughout the macula contributes to disease progression in eyes with GA. CVI inside the GA region could also be a potential indicator for the growth of GA.

4-(Phenylsulfanyl) Butan-2-One Attenuates the Inflammatory Response Induced by Amyloid-β Oligomers in Retinal Pigment Epithelium Cells.

Age-related macular degeneration (AMD) is a progressive eye disease that causes irreversible impairment of central vision, and effective treatment is not yet available. Extracellular accumulation of amyloid-beta (Aβ) in drusen that lie under the retinal pigment epithelium (RPE) has been reported as one of the early signs of AMD and was found in more than 60% of Alzheimer’s disease (AD) patients. Extracellular deposition of Aβ can induce the expression of inflammatory cytokines such as IL-1β, TNF-α, COX-2, and iNOS in RPE cells. Thus, finding a compound that can effectively reduce the inflammatory response may help the treatment of AMD. In this research, we investigated the anti-inflammatory effect of the coral-derived compound 4-(phenylsulfanyl) butan-2-one (4-PSB-2) on Aβ1-42 oligomer (oAβ1-42) added to the human adult retinal pigment epithelial cell line (ARPE-19). Our results demonstrated that 4-PSB-2 can decrease the elevated expressions of TNF-α, COX-2, and iNOS via NF-κB signaling in ARPE-19 cells treated with oAβ1-42 without causing any cytotoxicity or notable side effects. This study suggests that 4-PSB-2 is a promising drug candidate for attenuation of AMD.

A significant progress of computer aided diagnosis system using automated glaucoma screening

The automatic retinal image examination will be developing and significant screening device for initial recognition of eye diseases. This research proposes a computer aided diagnosis framework for initial recognition of glaucoma through Cup to Disc Ratio (CDR) measurement utilizing 2D fundus images. The system uses computer based analytical methods to procedure the patient data. The Glaucoma is chronic &amp; progressive eye disease which damages optic nerve (ON) caused by improved intraocular pressure (IOP) of eye. The Glaucoma mostly affects on optic disc (OD) by enhancing cup size. It might lead to blindness whether not recognized initially. The glaucoma detection through “Heidelberg Retinal Tomography (HRT) optical Coherence Tomography (OCT)” have been more costly. This system proposes an efficient technique to recognize glaucoma utilizing 2D fundus image. The physical analysis of OD is a normal process utilized for identifying glaucoma. In this manuscript, we suggest automatic OD parameterization method is based on segmented OD and optic cup (OC) region attained from fundus retinal images. To automatically extract OD and optic cup, we used K-means clustering technique, SLIC (Simple linear iterative clustering) method, Gabor filter and thresholding. To reshape the attained disc and cup boundary ellipse fitting (EF) is applied to obtained image. We also propose a novel method which automatically calculates CDR from non-stereographic fundus camera images. The CDR is initial clinical indicator for glaucoma assessment. Also, we have calculated OD and cup area. These features are validated by classifying image either normal or glaucomatous for given patient.

Development and validation of a novel prognostic model for predicting AMD progression using longitudinal fundus images

ObjectiveTo develop a prognostic tool to predict the progression of age-related eye disease progression using longitudinal colour fundus imaging.Methods and analysisPrevious prognostic models using deep learning with imaging data require...

Computer-aided retinal vessel segmentation in retinal images: convolutional neural networks

In medicine, diagnosis is as important as treatment. Retinal blood vessels are the most easily visible vessels in the whole body, and therefore, play a key role in the diagnosis of numerous diseases and eye disorders. Systematic and eye diseases cause morphologic variations, such as the growing, narrowing or branching of retinal blood vessels. Imaging-based screening of retinal blood vessels plays an important role in the identification and follow-up of eye diseases. Therefore, automatic retinal vessel segmentation can be used to diagnose and monitor those diseases. Computer-aided algorithms are required for the analysis of progression of eye diseases. This study proposes a hybrid method that provides a combination of pre-processing and data augmentation methods with a deep learning model. Pre-processing was used to solve the irregular clarification problems and to form a contrast between the background and retinal blood vessels. After pre-processing step, a convolutional neural network (CNN) was designed and then trained for the extraction of retinal blood vessels. In the training phase, data augmentation was performed to improve training performance. The CNN was trained and tested in the DRIVE database, which is commonly used in retinal blood vessel segmentation and publicly available for studies in this area. Results showed that the proposed system extracted vessels with a sensitivity of 77.78%, specificity of 97,84%, precision of 84.17% and accuracy of 95.27%. This study also compared the results to those of previous studies. The comparison showed that the proposed method is an efficient and successful method for extracting retinal blood vessels. Moreover, the pre-processing phases improved the system performance. We believe that the proposed method and results will make contribution to the literature.

Further evaluation of differential expression of keratoconus candidate genes in human corneas.

BackgroundKeratoconus (KTCN) is a progressive eye disease, characterized by changes in the shape and thickness of the cornea that results in loss of visual acuity. While numerous KTCN candidate genes have been identified, the genetic etiology of the disease remains undetermined. To further investigate and verify the contribution of particular genetic factors to KTCN, we assessed 45 candidate genes previously indicated as involved in KTCN etiology based on transcriptomic and genomic data.MethodsThe RealTime ready Custom Panel, covering 45 KTCN candidate genes and two reference transcripts, has been designed. Then, the expression profiles have been assessed using the RT-qPCR assay in six KTCN and six non-KTCN human corneas, obtained from individuals undergoing a penetrating keratoplasty procedure.ResultsIn total, 35 genes exhibiting differential expression between KTCN and non-KTCN corneas have been identified. Among these genes were ones linked to the extracellular matrix formation, including collagen synthesis or the TGF-β, Hippo, and Wnt signaling pathways. The most downregulated transcripts in KTCN corneas were CTGF, TGFB3, ZNF469, COL5A2, SMAD7, and SPARC, while TGFBI and SLC4A11 were the most upregulated ones. Hierarchical clustering of expression profiles demonstrated almost clear separation between KTCN and non-KTCN corneas. The gene expression levels determined using RT-qPCR showed a strong correlation with previous RNA sequencing (RNA-Seq) results.ConclusionsA strong correlation between RT-qPCR and earlier RNA-Seq data confirms the possible involvement of genes from collagen synthesis and the TGF-β, Hippo, and Wnt signaling pathways in KTCN etiology. Our data also revealed altered expression of several genes, such as LOX, SPARC, and ZNF469, in which single nucleotide variants have been frequently identified in KTCN. These findings further highlight the heterogeneous nature of KTCN.

Diabetic Retinopathy (DR) Severity Level Classification Using Multimodel Convolutional Neural Networks.

Diabetic retinopathy (DR) is a progressive eye disease that affects a large portion of working-age adults. DR, which may progress to an irreversible state that causes blindness, can be diagnosed with a comprehensive dilated eye exam. With the eye dilated, the Doctor takes pictures of the inside of the eye via a medical procedure called Fluorescein Angiography, in which a dye is injected into the bloodstream. The dye highlights the blood vessels in the back of the eye so they can be photographed. In addition, the Doctor may request an Optical Coherence Tomography (OCT) exam, by which cross-sectional photos of the retina are produced to measure the thickness of the retina. Early prognostication is vital in treating the disease and preventing it from progressing into advanced irreversible stages. Skilled medical personnel and necessary medical facilities are required to detect DR in its five major stages. In this paper, we propose a diagnostic tool to detect Diabetic retinopathy from fundus images by using an ensemble of multi-inception CNN networks. Our inception block consists of three Convolutional layers with kernel sizes of 3x3, 5x5, and 1x1 that are concatenated deeply and forwarded to the max-pooling layer. We experimentally compare our proposed method with two pre-trained models: VGG16 and GoogleNets. The experiment results show that the proposed method can achieve an accuracy of 93.2% by an ensemble of 10 random networks, compared to 81% obtained with transfer learning based on VGG19.

Analyzing Age-Related Macular Degeneration Progression in Patients with Geographic Atrophy Using Joint Autoencoders for Unsupervised Change Detection.

Age-Related Macular Degeneration (ARMD) is a progressive eye disease that slowly causes patients to go blind. For several years now, it has been an important research field to try to understand how the disease progresses and find effective medical treatments. Researchers have been mostly interested in studying the evolution of the lesions using different techniques ranging from manual annotation to mathematical models of the disease. However, artificial intelligence for ARMD image analysis has become one of the main research focuses to study the progression of the disease, as accurate manual annotation of its evolution has proved difficult using traditional methods even for experienced practicians. In this paper, we propose a deep learning architecture that can detect changes in the eye fundus images and assess the progression of the disease. Our method is based on joint autoencoders and is fully unsupervised. Our algorithm has been applied to pairs of images from different eye fundus images time series of 24 ARMD patients. Our method has been shown to be quite effective when compared with other methods from the literature, including non-neural network based algorithms that still are the current standard to follow the disease progression and change detection methods from other fields.

Role of Ocular Angiogenic Factors in the Development of Neovascular Age-Related Macular Degeneration

Abstract Age-related macular degeneration (AMD) is a progressive degenerative eye disease. Neovascular age-related macular degeneration (nAMD) is the advanced form of AMD characterised by abnormal growth of newly formed blood vessels in chorioidea which typically involves fluid accumulation in the retina or retinal haemorrhage, retinal epithelial detachments, hard exudate or subretinal scars. The process of angiogenesis is controlled by ocular angiogenic factors, which have enabled the development of different treatment options aimed at these factors. This review aims to compile the available information about the most commonly identified ocular angiogenic factors, uncovering their role in the pathogenesis of nAMD and assessing their application possibilities as biomarkers of disease identification and treatment.

Design of ocular drug delivery platforms and in vitro - in vivo evaluation of riboflavin to the cornea by non-interventional (epi-on) technique for keratoconus treatment

AimKeratoconus is a common and progressive eye disease characterized by thinning and tapering of the cornea. This degenerative eye disease is currently treated in the clinic with an interventional technique (“epi-off”) that can cause serious side effects as a result of the surgical procedure. The aim of this project is to design innovative formulations for the development of a riboflavin-containing medicinal product to develop a non-invasive (“epi-on”) keratoconus treatment as an alternative to current treatment modalities. MethodsNanostructured lipid carriers (NLCs) were successfully loaded with either riboflavin base of riboflavin-5-phosphate sodium and designed with either Stearylamine (positive charge) or Trancutol P (permeation enhancer). In vitro characterization studies, cytotoxicity and permeability studies were performed. Selected formulations and commercial preparations were applied and compared in ex-vivo corneal drug accumulation and transition studies. Furthermore, in vivo studies were performed to assess drug accumulation in the rat cornea and the corneal stability after NLC treatment was investigated via a biomechanical study on isolated rabbit corneas. ResultsBoth in vitro and ex-vivo as well as in vivo data showed that from the prepared NLC formulations, the most effective formulation was riboflavin-5-phosphate sodium containing NLC with Transcutol P as permeation enhancer. It possessed the highest drug loading content, low accumulation in the cornea but high permeability through the cornea as well as the highest functional performance in corneal crosslinking. ConclusionTopical application of riboflavin-5-phosphate sodium loaded NLC systems designed with permeation enhancer Transcutol P may act as a potential alternative for non-invasive keratoconus treatments.

A Nomenclature to Describe the Sequence of Visual Field Defects in Progressive Thyroid Eye Disease–Compressive Optic Neuropathy (An American Ophthalmological Society Thesis)

To create a novel nomenclature to characterize the longitudinal sequence of visual field (VF) defects in patients with progression of thyroid eye disease-compressive optic neuropathy (TED-CON). A retrospective review of records from 1 institution identified patients with progressive Humphrey VF defects secondary to TED-CON. The VF defects were analyzed by 2 independent reviewers and classified into 1 of 10 categories, divided into 3 stages that reflect the observed progression pattern, plus a miscellaneous category (stage X). Stage 1 VF defects are the earliest detectable and involve the inferior visual field with 3 levels of severity. Stage 2 VF defects include 2 distinguishable levels of severity and occur as the inferior defects advance above the horizontal midline to involve the superior VF. Stage 3 involves progression of stage 2 VF defects to complete loss of inferior and superior hemifields. Of 234 VFs in 37 eyes of 23 subjects, inferior defects were most common, including stage 1a (small inferior paracentral defect) in 22 of 234 VFs (9.4%), stage 1b (large inferior paracentral defect) in 112 of 234 VFs (47.9%), and stage 1c (inferior altitudinal defect) in 11 of 234 VFs (4.7%). Stage 2a (inferior altitudinal with superior advancement above the horizontal meridian) occurred in 41 of 234 VFs (17.5%), stage 2b (inferior altitudinal with superior arcuate) occurred in 6 of 234 VFs (2.6%), and stage 3 (total loss) occurred in 5 of 234 VFs (2.1%). The longitudinal sequence of VF defects from the 37 eyes of 23 patients was analyzed. Thirty-one of 37 eyes (83.8%) demonstrated a predictable progression pattern from least to more severe: stage 1a, stage 1b, stage 1c, stage 2a, stage 2b, and stage 3. A reverse order of VF defect progression was noted in 15 eyes with improving TED-CON. A minority of progression patterns (16.2%) originated from stage X (central/paracentral, enlarged blind spot, and scatter). Humphrey VF defects resulting from TED-CON are most often inferior, often have a predictable pattern of progression, and can be categorized into a novel descriptive nomenclature system. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

An hybrid feature space from texture information and transfer learning for glaucoma classification

Glaucoma is a progressive eye disease due to the increase in intraocular pressure. Accurate early detection may prevent vision loss. Most algorithms in the literature are not feasible for use in screening programs since they are not able to handle a wide diversity of images. We conducted an extensive study to determine the best set of features for image representation. Our feature extraction methodology included the following descriptors: LBP, GLCM, HOG, Tamura, GLRLM, morphology, and seven CNN architectures, that results in 30.682 features. Then, we used the gain ratio to order the features by importance and select the best set for glaucoma classification. Our tests were performed using 1675 images of DRISHTI, RIM-ONE, HRF, JSIEC, and ACRIMA databases. We concluded that a combination of the GLCM and pre-trained CNN’s has the potential to be used in a computer aid system for glaucoma detection. Our approach achieved an accuracy of 93.61%.

Inhibition of Experimental Age-Related Macular Degeneration by ZQMT in Mice

Age-related macular degeneration (AMD) is a progressive and irreversible eye disease. The anti-vascular endothelial growth factor (VEGF) therapy has revolutionized the treatment of neovascular AMD. However, the expense for such treatment is quite high. We used a traditional Chinese medicine ZQMT as an alternative therapeutic regimen for AMD. We employed two in vivo animal models mimicking dry and wet AMD respectively to assess the therapeutic efficacy of ZQMT on treating AMD-related retinopathy. AMD-related retinopathy in Crb1rd8 mice was evaluated from week 1 to 8 by fundus photography. Laser-induced choroidal neovascularization (CNV) was evaluated by fluorescein angiography and histopathology. ZQMT increased CX3CR1 expression in murine CD4+ T cells either cultured in vitro or directly isolated from animals treated with ZQMT. We also performed both in vitro and in vivo studies to confirm that ZQMT has no apparent toxic effects. ZQMT alleviated AMD-related retinopathy in both Crb1rd8 and CNV models. Depletion of CCL2 and CX3CR1 in Crb1rd8 mice abolished the efficacy of ZQMT, suggesting that CCL2 and/or CX3CR1 may underlie the mechanisms of ZQMT in treating AMD-related retinopathy in mice. In summary, our study supports the protective roles of a traditional Chinese medicine ZQMT in AMD.

Human vitreous in proliferative diabetic retinopathy: Characterization and translational implications.

Diabetic retinopathy (DR) is one of the leading causes of visual impairment in the working-age population. DR is a progressive eye disease caused by long-term accumulation of hyperglycaemia-mediated pathological alterations in the retina of diabetic patients. DR begins with asymptomatic retinal abnormalities and may progress to advanced-stage proliferative diabetic retinopathy (PDR), characterized by neovascularization or preretinal/vitreous haemorrhages. The vitreous, a transparent gel that fills the posterior cavity of the eye, plays a vital role in maintaining ocular function. Structural and molecular alterations of the vitreous, observed during DR progression, are consequences of metabolic and functional modifications of the retinal tissue. Thus, vitreal alterations reflect the pathological events occurring at the vitreoretinal interface. These events are caused by hypoxic, oxidative, inflammatory, neurodegenerative, and leukostatic conditions that occur during diabetes. Conversely, PDR vitreous can exert pathological effects on the diabetic retina, resulting in activation of a vicious cycle that contributes to disease progression. In this review, we recapitulate the major pathological features of DR/PDR, and focus on the structural and molecular changes that characterize the vitreal structure and composition during DR and progression to PDR. In PDR, vitreous represents a reservoir of pathological signalling molecules. Therefore, in this review we discuss how studying the biological activity of the vitreous in different in vitro, ex vivo, and in vivo experimental models can provide insights into the pathogenesis of PDR. In addition, the vitreous from PDR patients can represent a novel tool to obtain preclinical experimental evidences for the development and characterization of new therapeutic drug candidates for PDR therapy.

The incidence of keratoconus and its association with ocular disorders in Lahore population

Abstract This study was conducted to check predominance of keratoconus in male and female of the various age groups in Pakistan and to check the severity of disease in keratoconus patients. Keratoconus is a progressive eye disease in which the normally round cornea thins and begins to bulge into a cone-like shape. A cross-sectional, analytical study was performed between September 2016 to May 2017 on Keratoconus patients visiting Layton Rahmatullah Benevolent Trust Hospital and Sir Ganga Ram Hospital during their ophthalmic consultation. The techniques used for the diagnosis of Keratoconus were Visual Acuity by Snellen chart, Ophthalmoscopy, Orbscan corneal topography, and Slit lamp bio microscopy. Total 110 patients of Keratoconus were studied in which 62 were females and 48 were males. Patients developed both unilateral as well as bilateral conditions. Visual acuity from normal to high vision loss was also observed in Keratoconus patients. Different disorders with different percentage such as Munson’s sign were present in 68 patients, Rizutti’s sign was present in 30 patients, Vogt’s striae were present in 26 patients and Fleischer ring was present in 23 patients. 19 patients had Atopic syndrome and 6 patients had Leber’s Congenital Amaurosis were also associated with keratoconus. Keywords: Cross-sectional; Keratoconus; Ophthalmoscopy; Orbscan corneal topography; Snellen chart; Slit lamp biomicroscopy http://dx.doi.org/10.19045/bspab.2019.80001