Summarising the retinal vascular calibres in healthy, diabetic and diabetic retinopathy eyes

Retinal vessel calibre has been found to be an important biomarker of several retinal diseases, including diabetic retinopathy (DR). Quantifying the retinal vessel calibres is an important step for estimating the central retinal artery and vein equivalents. In this study, an alternative method to the already estab- lished branching coefficient(BC) is proposed for summarising the vessel calibres in retinal junctions. This new method combines the mean diameter ratio with an alternative to Murray’s cube law exponent, derived by the fractal dimen- sion,experimentally, and the branch exponent of cerebral vessels, as has been suggested in previous studies with blood flow modelling. For the above calcu- lations, retinal images from healthy, diabetic and DR subjects were used. In addition, the above method was compared with the BC and was also applied to the evaluation of arteriovenous ratio as a biomarker of progression from diabetes to DR in four consecutive years, i.e. three/two/one years before the onset of DR and the first year of DR. Moreover, the retinal arteries and veins around the optic nerve head were also evaluated. The new approach quantifies the vessels more accurately. The decrease in terms of the mean absolute percentage error was between 0.24% and 0.49%, extending at the same time the quantification beyond healthy subjects

Retinal vascular geometry: novel biomarkers of progression from diabetes to diabetic retinopathy

Diabetic retinopathy (DR) remains a major cause of blindness in the developed countries. Geometric and Haemodynamic features are still not widely investigated, especially as biomarkers of progression to DR. Most studies rely on disease vs control design, which introduces errors and limitations, given the diversity of the retinal vascular geometry (small and large vessels). Our studies have mainly focused on investigating the vascular changes within the same patients during a four year period that includes the last three years of pre-DR and 1st year of DR (onset)

Hemodynamics in the retinal vasculature during the progression of diabetic retinopathy

Purpose: Several studies have established, using various measurement modalities, that progression from diabetes to diabetic retinopathy is associated with changes in haemodynamics or measurable vascular geometry. In this study we take vessel measurements from standard fundus images, and estimate haemodynamic parameters (which are not directly observable) using a simple haemodynamic model. We show that there are statistically significant changes in some estimated haemodynamic parameters associated with the development of DR. Methods: A longitudinal study of twenty-four subjects was conducted. For each subject four fundus images were used, taken annually during the three years before the appearance of DR and in the first year of DR. A venous and arterial vascular bifurcation, each of which consisted of a parent vessel and two child branches was extracted, and at the branching nodes a zero dimensional model estimated the fluid dynamic conditions in terms of volumetric blood flow, blood flow velocity, nodal pressure, wall shear stress and Reynolds number. These features were statistically analyzed using linear mixed models. Results: A number of parameters, primarily venous, showed significant change with the development of DR, including early change two years before the onset of DR. A large proportion of overall variance is accounted for by individual patient differences, making progressive study essential. Conclusion: This is the first paper to demonstrate that haemodynamic feature estimates extracted from standard fundus images are sensitive to progression from diabetes to DR. In our future work, we aim to test whether the variations in haemodynamic conditions are predictive of progression prior to the appearance of retinal lesions

Evaluation of geometric features as biomarkers of diabetic retinopathy for characterizing the retinal vascular changes during the progression of diabetes

Diabetic retinopathy (DR) has been widely studied and characterized. However, until now, it is unclear how different features, extracted from the retinal vasculature, can be associated with the progression of diabetes and therefore become biomarkers of DR. In this study, a comprehensive analysis is presented, in which four groups were created, using eighty fundus images from twenty patients, who have progressed to DR and they had no history of any other diseases (e.g. hypertension or glaucoma). The significance of the following features was evaluated: widths, angles, branching coefficient (BC), angle-to-BC ratio, standard deviations, means and medians of widths and angles, fractal dimension (FD), lacunarity and FD-to-lacunarity ratio, using a mixed model analysis of variance (ANOVA) design. All the features were measured from the same junctions of each patient, using an automated tool. The discriminative power of these features was evaluated, using decision trees and random forests classifiers. Cross validation and out-of-bag error were used to evaluate the classifiers’ performance, calculating the area under the ROC curve (AUC) and the classification error. Widths, FD and FD- to-Lacunarity ratio were found to differ significantly. Random forests had a superior performance of 0.768 and 0.737 in the AUC for the two cases of classification, namely three-years-pre- DR/post-DR and two-years-pre-DR/post-DR respectively

Early screening and diagnosis of diabetic retinopathy

Diabetic retinopathy (DR) is a chronic, progressive and possibly vision-threatening eye disease. Early detection and diagnosis of DR, prior to the development of any lesions, is paramount for more efficiently dealing with it and managing its consequences. This thesis investigates and proposes a number of candidate geometric and haemodynamic biomarkers, derived from fundus images of the retinal vasculature, which can be reliably utilised for identifying the progression from diabetes to DR. Numerous studies exist in literature that investigate only some of these biomarkers in independent normal, diabetic and DR cohorts. However, none exist, to the best of my knowledge, that investigates more than 100 biomarkers altogether, both geometric and haemodynamic ones, for identifying the progression to DR, by also using a novel experimental design, where the same exact matched junctions and subjects are evaluated in a four year period that includes the last three years pre-DR (still diabetic eye) and the onset of DR (progressors’ group). Multiple additional conventional experimental designs, such as non-matched junctions, non-progressors’ group, and a combination of them are also adopted in order to present the superiority of this type of analysis for retinal features. Therefore, this thesis aims to present a complete framework and some novel knowledge, based on statistical analysis, feature selection processes and classification models, so as to provide robust, rigorous and meaningful statistical inferences, alongside efficient feature subsets that can identify the stages of the progression. In addition, a new and improved method for more accurately summarising the calibres of the retinal vessel trunks is also presented. The first original contribution of this thesis is that a series of haemodynamic features (blood flow rate, blood flow velocity, etc.), which are estimated from the retinal vascular geometry based on some boundary conditions, are applied to studying the progression from diabetes to DR. These features are found to undoubtedly contribute to the inferences and the understanding of the progression, yielding significant results, mainly for the venular network. The second major contribution is the proposed framework and the experimental design for more accurately and efficiently studying and quantifying the vascular alterations that occur during the progression to DR and that can be safely attributed only to this progression. The combination of the framework and the experimental design lead to more sound and concrete inferences, providing a set of features, such as the central retinal artery and vein equivalent, fractal dimension, blood flow rate, etc., that are indeed biomarkers of progression to DR. The third major contribution of this work is the new and improved method for more accurately summarising the calibre of an arterial or venular trunk, with a direct application to estimating the central retinal artery equivalent (CRAE), the central retinal vein equivalent (CRVE) and their quotient, the arteriovenous ratio (AVR). Finally, the improved method is shown to truly make a notable difference in the estimations, when compared to the established alternative method in literature, with an improvement between 0.24% and 0.49% in terms of the mean absolute percentage error and 0.013 in the area under the curve. I have demonstrated that some thoroughly planned experimental studies based on a comprehensive framework, which combines image processing algorithms, statistical and classification models, feature selection processes, and robust haemodynamic and geometric features, extracted from the retinal vasculature (as a whole and from specific areas of interest), provide altogether succinct evidence that the early detection of the progression from diabetes to DR can be indeed achieved. The performance that the eight different classification combinations achieved in terms of the area under the curve varied from 0.745 to 0.968

Retinal Imaging in Alzheimer’s Disease

Identifying biomarkers of Alzheimer's disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies. Developments in non-invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study neuronal and vascular structures in the retina in people with AD. Both qualitative and quantitative measurements from these retinal imaging technologies (eg, thinning of peripapillary retinal nerve fibre layer, inner retinal layer, and choroidal layer, reduced capillary density, abnormal vasodilatory response) have been shown to be associated with cognitive function impairment and risk of AD. The development of computer algorithms for respective retinal imaging methods has further enhanced the potential of retinal imaging as a viable tool for rapid, early detection and screening of AD. In this review, we present an update of current retinal imaging techniques and their potential applications in AD research. We also discuss the newer retinal imaging techniques and future directions in this expanding field

Age-Related Macular Degeneration and Diabetic Retinopathy

This reprint includes contributions from leaders in the field of personalized medicine in ophthalmology. The contributions are diverse and cover pre-clinical and clinical topics. We hope you enjoy reading the articles

Biomedical Applications of Mid-Infrared Spectroscopic Imaging and Multivariate Data Analysis: Contribution to the Understanding of Diabetes Pathogenesis

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of adult vision loss. Although a great deal of progress has been made in ophthalmological examinations and clinical approaches to detect the signs of retinopathy in patients with diabetes, there still remain outstanding questions regarding the molecular and biochemical changes involved. To discover the biochemical mechanisms underlying the development and progression of changes in the retina as a result of diabetes, a more comprehensive understanding of the bio-molecular processes, in individual retinal cells subjected to hyperglycemia, is required. Animal models provide a suitable resource for temporal detection of the underlying pathophysiological and biochemical changes associated with DR, which is not fully attainable in human studies. In the present study, I aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the retinal tissue from Ins2Akita/+ (Akita/+; a model of Type I diabetes) male mice with different duration of diabetes. Employing label-free, spatially resolved Fourier transform infrared (FT-IR) imaging engaged with chemometric tools enabled me to identify temporal-dependent reproducible biomarkers of the diabetic retinal tissue from mice with 6 or 12 weeks, and 6 or 10 months of diabetes. I report, for the first time, the origin of molecular changes in the biochemistry of individual retinal layers with different duration of diabetes. A robust classification between distinctive retinal layers - namely photoreceptor layer (PRL), outer plexiform layer (OPL), inner nuclear layer (INL), and inner plexiform layer (IPL) - and associated temporal-dependent spectral biomarkers, were delineated. Spatially-resolved super resolution chemical images revealed oxidative stress-induced structural and morphological alterations within the nucleus of the photoreceptors. Comparison among the PRL, OPL, INL, and IPL suggested that the photoreceptor layer is the most susceptible layer to the oxidative stress with short-duration of diabetes. Moreover, for the first time, we present the temporal-dependent molecular alterations for the PRL, OPL, INL, and IPL from Akita/+ mice, with progression of diabetes. These findings are potentially important and may be of particular benefit in understanding the molecular and biological activity of retinal cells during oxidative stress in diabetes. Our integrating paradigm provides a new conceptual framework and a significant rationale for a better understanding of the molecular and cellular mechanisms underlying the development and progression of DR. This approach may yield alternative and potentially complimentary methods for the assessment of diabetes changes. It is expected that the conclusions drawn from this work will bridge the gap in our knowledge regarding the biochemical mechanisms of the DR and address some critical needs in the biomedical community

Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review

Background. This study aimed to review the literature on the application of ImageJ in optical coherence tomography angiography (OCT-A) images. Methods. A general search was performed in PubMed, Google Scholar, and Scopus databases. The authors evaluated each of the selected articles in order to assess the implementation of ImageJ in OCT-A images. Results. ImageJ can aid in reducing artifacts, enhancing image quality to increase the accuracy of the process and analysis, processing and analyzing images, generating comparable parameters such as the parameters that assess perfusion of the layers (vessel density (VD), skeletonized density (SD), and vessel length density (VLD)) and the parameters that evaluate the structure of the layers (fractal dimension (FD), vessel density index (VDI), and lacunarity (LAC)), and the foveal avascular zone (FAZ) that are used widely in the retinal and choroidal studies), and establishing diagnostic criteria. It can help to save time when the dataset is huge with numerous plugins and options for image processing and analysis with reliable results. Diverse studies implemented distinct binarization and thresholding techniques, resulting in disparate outcomes and incomparable parameters. Uniformity in methodology is required to acquire comparable data from studies employing diverse processing and analysis techniques that yield varied outcomes. Conclusion. Researchers and professionals might benefit from using ImageJ because of how quickly and correctly it processes and analyzes images. It is highly adaptable and potent software, allowing users to evaluate images in a variety of ways. There exists a diverse range of methodologies for analyzing OCTA images through the utilization of ImageJ. However, it is imperative to establish a standardized strategy to ensure the reliability and consistency of the method for research purposes

Retinal vessel traits and their association with diabetic retinopathy and cognitive decline in a population with type 2 diabetes

Background People with diabetes are at an increased risk of developing vascular disease, which is the leading cause of morbidity and mortality in this population. The retina is one of the few places in the body that offers noninvasive visualisation of the vascular system and thus provides a rich platform to evaluate local and systemic vascular disease. Recent advancements in retinal image analysis tools allow us to evaluate the retinal microvasculature in a more efficient and unbiased way compared to manual methods. Local retinal changes may provide insight into vascular disease prior to overt pathological changes. Aim The aim of this thesis was to explore and evaluate retinal vessel traits in relation to various manifestations of vascular disease, specifically diabetic retinopathy and cognitive decline, using prospectively collected data. In addition to undertaking this research, this PhD project also aimed to contribute to the collection of primary data from in ongoing longitudinal cohort in order to provide data not only for this project, but for many other future and ongoing projects. Methods Edinburgh Type 2 Diabetes Study is a cohort of 1,066 adults aged 60-75 years with type 2 diabetes living in the Lothian region of Scotland. Data were collected through research clinics as well as record linkage. Diabetic retinopathy status was obtained from the national screening programme and to evaluate cognitive decline, dementia diagnosis was obtained from a combination of medical records, death records and self-report. Cognitive decline was also evaluated using cognitive status derived from a battery of cognitive tests administered at baseline and then again after 10 years. Retinal images were analysed using VAMPIRE software for central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), arteriolar and venular tortuosity, fractal dimension and density. Results A total of 83 participants (11.6%) developed retinopathy over 10 years. After controlling for a wide number of cardiometabolic, diabetic and vascular risk factors, there was evidence of an association between increased venular tortuosity and incident retinopathy (odds ratio (OR) 1.51, 95% confidence interval (CI) 1.15 to 1.98, p = 0.003), as well as decreased standardised fractal dimension and incident retinopathy (OR 0.75, 0.58 to 0.96, p = 0.025). Of the total 1066, 106 (9.9%) were determined to have a dementia diagnosis after 10 years of follow-up. Cognitive decline, as measured by cognitive testing after 10 years, controlling for baseline cognitive status, was measured in the 581 returning participants. There were no independent associations between the retinal vessel traits and cognitive decline, using either dementia or the general intelligence factor, after controlling for various covariates. There was, however, evidence of age-related decreases in fractal dimension and density over the course of the study. Conclusions This thesis has provided evidence from the ET2DS that venular tortuosity and fractal dimension are independently associated with diabetic retinopathy. The independent associations were modest and need to be contextualised within the heterogeneity that exists within the supporting literature as well as replicated in other studies, but they provide exciting support for the use of the retinal vessel traits in future risk prediction modelling for diabetic retinopathy. There was no evidence of an association between the reported retinal vessel traits and cognitive decline. Novel findings regarding age-related decreases in fractal dimension and density are important as more information is coming to light regarding the vessel traits and their associations with vascular disease