Adrienne Csutak

Repeatability of ocular biomechanical data measurements with a scheimpflug-based noncontact device on normal corneas

PURPOSE To analyze the repeatability of a new device measuring ocular biomechanical properties, central corneal thickness (CCT), and intraocular pressure (IOP) and to investigate these parameters and their correlations in healthy eyes. METHODS Three consecutive measurements were performed on each eye using the CorVis ST device (Oculus Optikgeräte, Inc., Wetzler, Germany). Ten specific parameters, CCT, and IOP were measured. Biometric data were recorded with IOLMaster (Carl Zeiss Meditec, Jena, Germany). RESULTS This study comprised 75 eyes of 75 healthy volunteers (mean age: 61.24 ± 15.72 years). Mean IOP was 15.02 ± 2.90 mm Hg and mean CCT was 556.33 ± 33.13 μm. Intraclass correlation coefficient (ICC) was 0.865 for IOP and 0.970 for CCT, and coefficient of variation was 0.069 for IOP and 0.008 for CCT. ICC was 0.758 for maximum amplitude at highest concavity and 0.784 for first applanation time, and less than 0.6 for all other parameters. The device-specific data showed no significant relationship with age and axial length. Flattest and steepest keratometric values and IOP showed a significant correlation with the 10 device-specific parameters. CONCLUSIONS The CorVis ST showed high repeatability for only IOP and pachymetric values. Single measurements are not reliable for the 10 device-specific parameters. The device allows for conducting clinical examinations and screening for surgeries altering ocular biomechanical properties with some form of averaging of multiple measurements.

Quantitative analysis of proteins in the tear fluid of patients with diabetic retinopathy

Diabetic retinopathy is the leading cause of new cases of legal blindness among adults in the developed countries. Approximately 40% of all people with diabetes have diabetic retinopathy and 5% of these have sight-threatening form. As the advanced stage, where there is a high risk for vision loss, can develop without any serious symptoms, sometimes it is hard to detect it. A non invasive method to detect biomarkers characteristic for diabetic retinopathy from the tear fluid was developed. Tear samples from diabetic patients with no retinopathy, non proliferative and proliferative stages of diabetic retinopathy were analyzed and the protein content of each sample was compared to the protein content of tear pool from healthy volunteers. The samples were labeled with iTRAQ fourplex labels and were analyzed with nanoHPLC coupled ESI-MS/MS mass spectrometry. The lipocalin 1, lactotransferrin, lacritin, lysozyme C, lipophilin A and immunoglobulin lambda chain were identified as possible biomarker candidates with significantly higher relative levels in the tear of patients with diabetic retinopathy.

Automatic detection of the optic disc using majority voting in a collection of optic disc detectors

This paper proposes an efficient method for locating the optic disc in retinal images automatically using majority voting scheme and data fusion. We show that instead of inventing a new algorithm which ends up being a minor variation on an old idea, the fusion of different optic disc (OD) detectors can enhance the overall performance of the detection system. The optic disc centre candidates of different optic disc detectors are marked in the image and a circular template is fit on each pixel in the image to count the outputs of these algorithms that fall within the radius. The location with maximum number of optic disc centre candidates is the hotspot and is used to localize the optic disc centre. An assessment of the performance of the combined optic disc detector versus detectors working separately is also presented. Our method achieved highest performance (overall 100% correct detection).

Tear fluid proteomics multimarkers for diabetic retinopathy screening

BackgroundThe aim of the project was to develop a novel method for diabetic retinopathy screening based on the examination of tear fluid biomarker changes. In order to evaluate the usability of protein biomarkers for pre-screening purposes several different approaches were used, including machine learning algorithms.MethodsAll persons involved in the study had diabetes. Diabetic retinopathy (DR) was diagnosed by capturing 7-field fundus images, evaluated by two independent ophthalmologists. 165 eyes were examined (from 119 patients), 55 were diagnosed healthy and 110 images showed signs of DR. Tear samples were taken from all eyes and state-of-the-art nano-HPLC coupled ESI-MS/MS mass spectrometry protein identification was performed on all samples. Applicability of protein biomarkers was evaluated by six different optimally parameterized machine learning algorithms: Support Vector Machine, Recursive Partitioning, Random Forest, Naive Bayes, Logistic Regression, K-Nearest Neighbor.ResultsOut of the six investigated machine learning algorithms the result of Recursive Partitioning proved to be the most accurate. The performance of the system realizing the above algorithm reached 74% sensitivity and 48% specificity.ConclusionsProtein biomarkers selected and classified with machine learning algorithms alone are at present not recommended for screening purposes because of low specificity and sensitivity values. This tool can be potentially used to improve the results of image processing methods as a complementary tool in automatic or semiautomatic systems.

Agreement between image grading of conventional (45°) and ultra wide-angle (200°) digital images in the macula in the Reykjavik eye study

PurposeTo establish the agreement between image grading of conventional (45°) and ultra wide-angle (200°) digital images in the macula.MethodsIn 2008, the 12-year follow-up was conducted on 573 participants of the Reykjavik Eye Study. This study included the use of the Optos P200C AF ultra wide-angle laser scanning ophthalmoscope alongside Zeiss FF 450 conventional digital fundus camera on 121 eyes with or without age-related macular degeneration using the International Classification System. Of these eyes, detailed grading was carried out on five cases each with hard drusen, geographic atrophy and chorioretinal neovascularisation, and six cases of soft drusen. Exact agreement and κ-statistics were calculated.ResultsComparison of the conventional and ultra wide-angle images in the macula showed an overall 96.43% agreement (κ=0.93) with no disagreement at end-stage disease; although in one eye chorioretinal neovascularisation was graded as drusenoid pigment epithelial detachment. Of patients with drusen only, the exact agreement was 96.1%. The detailed grading showed no clinically significant disagreement between the conventional 45° and 200° images.ConclusionsOn the basis of our results, there is a good agreement between grading conventional and ultra wide-angle images in the macula.

Expression of betaig-h3 is lower than normal in keratoconus corneas but increases with scarring.

PURPOSE Keratoconus is a progressive ectatic disease of the cornea. Despite extensive clinical and laboratory investigations, its pathogenesis remains unclear. In this study, we examined the localization of betaig-h3, a recently described extracellular matrix protein in keratoconus corneas both in the absence and presence of subepithelial scarring. METHODS Two normal corneas and central corneal buttons of 10 patients with keratoconus were excised during perforating keratoplasty and examined, including one case with acute corneal hydrops. In one case, keratoconus was associated with Down syndrome. Immunodetection was done with an antipeptide antibody reacting with the N-terminal part of betaig-h3. RESULTS We found decreased betaig-h3 levels in the basal epithelial layer and keratocytes of keratoconus corneas. In the scarred corneas, however, betaig-h3 levels were increased in the basal epithelial layers and in activated keratocytes at the places of scarring. In the cornea of the patient with Down syndrome, we found an additional betaig-h3-positive zone in the anterior stroma. CONCLUSIONS The decreased levels of betaig-h3 corneas seem to be specific for keratoconus. Considering the putative role of betaig-h3 as a cellular-attachment protein, paucity of betaig-h3 in the corneal stroma may lead to decreased mechanical stability and contribute to the development of keratoconus.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. SIGNIFICANCE Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases.

A Population-Based Ultra-Widefield Digital Image Grading Study for Age-Related Macular Degeneration–Like Lesions at the Peripheral Retina

PURPOSE Our understanding of the relevance of peripheral retinal abnormalities to disease in general and in age-related macular degeneration (AMD) in particular is limited by the lack of detailed peripheral imaging studies. The purpose of this study was to develop image grading protocols suited to ultra-widefield imaging (UWFI) in an aged population. DESIGN A cross-sectional study of a random population sample in which UWFI was introduced at the 12-year review of the Reykjavik Eye Study in Iceland. PARTICIPANTS Five hundred seventy-six subjects 62 years of age or older. METHODS Ultra-widefield (up to 200°) color and autofluorescence images were obtained using the Optos P200CAF laser scanning ophthalmoscope (Optos plc, Dunfermline, Scotland). The images were graded at Moorfields Eye Hospital Reading Centre primarily based on the International Classification for AMD. Macular and peripheral changes were graded using a standardized grid developed for this imaging method. MAIN OUTCOME MEASURES Presence or absence of hard, crystalline, and soft drusen; retinal pigment epithelial changes; choroidal neovascularization (CNV); atrophy; and hypoautofluorescence and hyperautofluorescence were graded in the peripheral retina. RESULTS Of the eyes examined, 81.1% had AMD-like changes in the macula alone (13.6%), periphery alone (10.1%), and both periphery and macula (57.4%). There was no AMD-like CNV or pigment epithelial detachment in the periphery except in those cases in which these clearly originated from the macula. Seven patients had AMD-like atrophy in the periphery without end-stage disease in the macula. One patient with end-stage disease in the macula had normal periphery results on the color images. While analyzing the eyes, we detected pathologic appearances that were very reliably identified by graders. CONCLUSIONS Phenotyping the retinal periphery using the categories defined by the International Classification confirmed the presence of wide-ranging AMD-like pathologic changes even in those without central sight-threatening macular disease. Based on our observations, we propose here new, reliably identifiable grading categories that may be more suited for population-based UWFI.

Combined Methods for Diabetic Retinopathy Screening, Using Retina Photographs and Tear Fluid Proteomics Biomarkers

Background. It is estimated that 347 million people suffer from diabetes mellitus (DM), and almost 5 million are blind due to diabetic retinopathy (DR). The progression of DR can be slowed down with early diagnosis and treatment. Therefore our aim was to develop a novel automated method for DR screening. Methods. 52 patients with diabetes mellitus were enrolled into the project. Of all patients, 39 had signs of DR. Digital retina images and tear fluid samples were taken from each eye. The results from the tear fluid proteomics analysis and from digital microaneurysm (MA) detection on fundus images were used as the input of a machine learning system. Results. MA detection method alone resulted in 0.84 sensitivity and 0.81 specificity. Using the proteomics data for analysis 0.87 sensitivity and 0.68 specificity values were achieved. The combined data analysis integrated the features of the proteomics data along with the number of detected MAs in the associated image and achieved sensitivity/specificity values of 0.93/0.78. Conclusions. As the two different types of data represent independent and complementary information on the outcome, the combined model resulted in a reliable screening method that is comparable to the requirements of DR screening programs applied in clinical routine.

Changes in the chemical barrier composition of tears in Alzheimer's disease reveal potential tear diagnostic biomarkers

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases, with increasing prevalence affecting millions of people worldwide. Currently, only autopsy is able to confirm the diagnosis with a 100% certainty, therefore, biomarkers from body fluids obtained by non-invasive means provide an attractive alternative for the diagnosis of Alzheimer`s disease. Global changes of the protein profile were examined by quantitative proteomics; firstly, electrophoresis and LC-MS/MS were used, thereafter, SRM-based targeted proteomics method was developed and applied to examine quantitative changes of tear proteins. Alterations in the tear flow rate, total tear protein concentration and composition of the chemical barrier specific to AD were demonstrated, and the combination of lipocalin-1, dermcidin, lysozyme-C and lacritin was shown to be a potential biomarker, with an 81% sensitivity and 77% specificity.