Eye as a window to the brain: investigating the clinical utility of retinal imaging derived biomarkers in the phenotyping of neurodegenerative disease.

Background Neurodegenerative diseases, like multiple sclerosis, dementia and motor neurone disease, represent one of the major public health threats of our time. There is a clear persistent need for novel, affordable, and patient‐acceptable biomarkers of these diseases, to assist with diagnosis, prognosis and impact of interventions. And these biomarkers need to be sensitive, specific and precise. The retina is an attractive site for exploring this potential, as it is easily accessible to non‐invasive imaging. Remarkable technology revolutions in retinal imaging are enabling us to see the retina in microscopic level detail, and measure neuronal and vascular integrity. Aims and objectives I therefore propose that retinal imaging could provide reliable and accurate markers of these neurological diseases. In this project, I aimed to explore the clinical utility of retinal imaging derived measures of retinal neuronal and vessel size and morphology, and determine their candidacy for being reliable biomarkers in these diseases. I also aimed to detail the methods of retinal imaging acquisition, and processing, and the principles underlying all these stages, in relation to understanding of retinal structure and function. This provides an essential foundation to the application of retinal imaging analysis, highlighting both the strengths and potential weaknesses of retinal biomarkers and how they are interpreted. Methods After performing detailed systematic reviews and meta‐analyses of the existing work on retinal biomarkers of neurodegenerative disease, I carried out a prospective, controlled, cross‐sectional study of retinal image analysis, in patients with MS, dementia, and ALS. This involved developing new software for vessel analysis, to add value and maximise the data available from patient imaging episodes. Results From the systematic reviews, I identified key unanswered questions relating to the detailed analysis and utility of neuroretinal markers, and diseases with no studies yet performed of retinal biomarkers, such as non‐AD dementias. I recruited and imaged 961 participants over a two‐year period, and found clear patterns of significance in the phenotyping of MS, dementia and ALS. Detailed analysis has provided new insights into how the retina may yield important disease information for the individual patient, and also generate new hypotheses with relation to the disease pathophysiology itself. Conclusions Overall, the results show that retinal imaging derived biomarkers have an important and specific role in the phenotyping of neurodegenerative diseases, and support the hypothesis that the eye is an important window to neurological brain disease

Malarial retinopathy and neurovascular injury in paediatric cerebral malaria

Background Diseases of the brain are difficult to study because this organ is relatively inaccessible. Only one part of the central nervous system is available to direct, non-invasive observation – the retina. The concept of the retina as a window to the brain has created much interest in the retina as a source of potential markers of brain disease. Paediatric cerebral malaria is a severe neurological complication of infection with the parasite Plasmodium falciparum, which is responsible for death and disability in a significant number of children in sub-Saharan Africa. As with many neurological diseases, the precise mechanisms by which this infection causes damage to the brain remain unclear, and this hampers efforts to develop effective treatments. It may be that studying the retina in paediatric cerebral malaria could both illuminate pathogenesis specific to this disease, and also provide an illustration of how to approach retinal biomarkers in a new, and potentially more effective way. Methods I approached the aim of developing retinal features as markers of brain disease in paediatric cerebral malaria via several objectives. I made use of an existing clinical study to collect new retinal data from ophthalmoscopic examinations and fundus fluorescein angiograms from patients over three successive malaria seasons in Malawi, and added these to historical data obtained previously at the same site. I devised a new method for grading retinal images. I reviewed the biological plausibility of associations between retina and brain in cerebral malaria, and then considered analytical methods to interpret my retinal data effectively. Finally I estimated associations between retinal features, outcomes, and a radiological measure of brain swelling using combinations of regression models. Results My review of retinal and cerebral histopathology, vascular anatomy and physiology indicated that certain retinal and brain regions may be similarly prone to damage from sequestration as a result of interactions between aberrant rheology and microvascular geometry, such as branching patterns and arteriole to venule ratios. My review of evaluations of analogy and surrogacy suggested that biological similarities between retina and brain could be used to justify statistical evaluation of the amount of information the subject and object of the inference share about a common outcome, as used to assess surrogate end points for clinical trials. This kind of approach is able to address questions about whether a particular retinal feature is effectively equivalent to an analogous disease manifestation in the brain. I report analyses on three overlapping groups of subjects, all of whom had retinopathy positive cerebral malaria: children with admission ophthalmoscopy (n=817), children with admission fluorescein angiography (n=260), and children with admission angiography and MRI of the brain (n=134). Several retinal features are associated with death and longer time to recover consciousness in paediatric cerebral malaria. Broadly speaking, these features appear to reflect two processes: neurovascular sequestration (e.g. orange vessel discolouration and death), and neurovascular leakage (e.g. >5 sites of punctate leak and death). Respective adjusted odds ratios and 95% confidence intervals for these particular associations are: 2.88 (1.64-5.05); and 6.90 (1.52-31.3). Other related processes may also be important, such as ischaemia, which can be extensive. Associations between retina and brain are less clear, in part because of selection bias in the samples. Conclusions Neurovascular leak is important in fatal paediatric cerebral malaria, suggesting that fatal brain swelling may occur primarily as a result of vasogenic oedema. Other processes are also likely to be involved, particularly neurovascular sequestration, which is visible on retinal imaging as orange vessels or intravascular filling defects. Sequestration may plausibly cause leak through direct damage to tight junctions and by increasing transmural pressure secondary to venous congestion. Several types of retinal leakage are seen and some of these may represent re-perfusion rather than acute injury. Future work to investigate temporal changes in retinal signs may find clearer associations with radiological and clinical outcomes. The steps taken to evaluate retinal markers in cerebral malaria illustrate a more rigorous approach to retinal biomarkers in general, which can be applied to other neurological disease

Automatic Artery/Vein Classification Using a Vessel-Constraint Network for Multicenter Fundus Images

Retinal blood vessel morphological abnormalities are generally associated with cardiovascular, cerebrovascular, and systemic diseases, automatic artery/vein (A/V) classification is particularly important for medical image analysis and clinical decision making. However, the current method still has some limitations in A/V classification, especially the blood vessel edge and end error problems caused by the single scale and the blurred boundary of the A/V. To alleviate these problems, in this work, we propose a vessel-constraint network (VC-Net) that utilizes the information of vessel distribution and edge to enhance A/V classification, which is a high-precision A/V classification model based on data fusion. Particularly, the VC-Net introduces a vessel-constraint (VC) module that combines local and global vessel information to generate a weight map to constrain the A/V features, which suppresses the background-prone features and enhances the edge and end features of blood vessels. In addition, the VC-Net employs a multiscale feature (MSF) module to extract blood vessel information with different scales to improve the feature extraction capability and robustness of the model. And the VC-Net can get vessel segmentation results simultaneously. The proposed method is tested on publicly available fundus image datasets with different scales, namely, DRIVE, LES, and HRF, and validated on two newly created multicenter datasets: Tongren and Kailuan. We achieve a balance accuracy of 0.9554 and F1 scores of 0.7616 and 0.7971 for the arteries and veins, respectively, on the DRIVE dataset. The experimental results prove that the proposed model achieves competitive performance in A/V classification and vessel segmentation tasks compared with state-of-the-art methods. Finally, we test the Kailuan dataset with other trained fusion datasets, the results also show good robustness. To promote research in this area, the Tongren dataset and source code will be made publicly available. The dataset and code will be made available at https://github.com/huawang123/VC-Net

Level set segmentation of retinal structures

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Changes in retinal structure are related to different eye diseases. Various retinal imaging techniques, such as fundus imaging and optical coherence tomography (OCT) imaging modalities, have been developed for non-intrusive ophthalmology diagnoses according to the vasculature changes. However, it is time consuming or even impossible for ophthalmologists to manually label all the retinal structures from fundus images and OCT images. Therefore, computer aided diagnosis system for retinal imaging plays an important role in the assessment of ophthalmologic diseases and cardiovascular disorders. The aim of this PhD thesis is to develop segmentation methods to extract clinically useful information from these retinal images, which are acquired from different imaging modalities. In other words, we built the segmentation methods to extract important structures from both 2D fundus images and 3D OCT images. In the first part of my PhD project, two novel level set based methods were proposed for detecting the blood vessels and optic discs from fundus images. The first one integrates Chan-Vese's energy minimizing active contour method with the edge constraint term and Gaussian Mixture Model based term for blood vessels segmentation, while the second method combines the edge constraint term, the distance regularisation term and the shape-prior term for locating the optic disc. Both methods include the pre-processing stage, used for removing noise and enhancing the contrast between the object and the background. Three automated layer segmentation methods were built for segmenting intra-retinal layers from 3D OCT macular and optic nerve head images in the second part of my PhD project. The first two methods combine different methods according to the data characteristics. First, eight boundaries of the intra-retinal layers were detected from the 3D OCT macular images and the thickness maps of the seven layers were produced. Second, four boundaries of the intra-retinal layers were located from 3D optic nerve head images and the thickness maps of the Retinal Nerve Fiber Layer (RNFL) were plotted. Finally, the choroidal layer segmentation method based on the Level Set framework was designed, which embedded with the distance regularisation term, edge constraint term and Markov Random Field modelled region term. The thickness map of the choroidal layer was calculated and shown.Department of Computer Science, Brunel University London

Human retinal oximetry using hyperspectral imaging

The aim of the work reported in this thesis was to investigate the possibility of measuring human retinal oxygen saturation using hyperspectral imaging. A direct non-invasive quantitative mapping of retinal oxygen saturation is enabled by hyperspectral imaging whereby the absorption spectra of oxygenated and deoxygenated haemoglobin are recorded and analysed. Implementation of spectral retinal imaging thus requires ophthalmic instrumentation capable of efficiently recording the requisite spectral data cube. For this purpose, a spectral retinal imager was developed for the first time by integrating a liquid crystal tuneable filter into the illumination system of a conventional fundus camera to enable the recording of narrow-band spectral images in time sequence from 400nm to 700nm. Postprocessing algorithms were developed to enable accurate exploitation of spectral retinal images and overcome the confounding problems associated with this technique due to the erratic eye motion and illumination variation. Several algorithms were developed to provide semi-quantitative and quantitative oxygen saturation measurements. Accurate quantitative measurements necessitated an optical model of light propagation into the retina that takes into account the absorption and scattering of light by red blood cells. To validate the oxygen saturation measurements and algorithms, a model eye was constructed and measurements were compared with gold-standard measurements obtained by a Co-Oximeter. The accuracy of the oxygen saturation measurements was (3.31%± 2.19) for oxygenated blood samples. Clinical trials from healthy and diseased subjects were analysed and oxygen saturation measurements were compared to establish a merit of certain retinal diseases. Oxygen saturation measurements were in agreement with clinician expectations in both veins (48%±9) and arteries (96%±5). We also present in this thesis the development of novel clinical instrument based on IRIS to perform retinal oximetry.Al-baath University, Syri

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

Investigation Of Hypoxia And Mitochondrial Dysfunction In The Central Nervous System Resulting From Focal And Systemic Inflammation

Inflammation is an important feature of several seemingly disparate neurological disorders, including multiple sclerosis, Parkinson’s disease and sepsis-related brain dysfunction. Inadequate oxygenation and mitochondrial dysfunction have been implicated in these and other CNS pathologies in which inflammation is found. Indeed, inflammation can have direct or indirect effects on mitochondrial function, for example, via reactive oxygen/nitrogen species, or through compromised perfusion respectively. However, the study of oxygenation and mitochondrial function in the CNS has been limited as tissues are typically excised for study in vitro, invariably exposing cells and their mitochondria to non-physiological environments. To overcome these limitations, the work described in this thesis involved the study of mitochondrial dysfunction and tissue oxygenation in the CNS during local and systemic inflammation in whole-animal preparations under physiological and pathophysiological conditions. The experiments include development of in vivo optical imaging techniques to assess the redox potential of mitochondria, without the application of dyes, and with an intact blood supply. Using this technique in conjunction with established methods we investigated mitochondrial function and tissue oxygen concentrations in cortical and retinal models of local and systemic inflammation. Our findings reveal that mitochondrial flavoprotein autofluorescence imaged in the cortex of anaesthetised mice can be used to assess an aspect of mitochondrial function (redox potential) in the CNS in vivo. Additionally, we show that certain types of inflammation are associated with tissue hypoxia in the brain and retina, and that this can have profound functional consequences for cerebral mitochondria during systemic inflammation. Hypothermia was also explored as a potential therapeutic strategy to attenuate inflammation-induced functional deficits. Collectively, these findings further our understanding of the mechanisms underlying neurological deficits associated with inflammation, and reveal mitochondrial redox state imbalances in certain inflammatory conditions with potential implications for the treatment of CNS disorders in which inflammation plays a role

The development of an in-vivo method for assessing the antithrombotic properties of pharmaceutical compounds

The formation of a thrombus stems from the malfunction of a normal physiological function referred to as haemostasis and the activity of blood platelets; such thrombi give rise to debilitating and often fatal strokes. Consequently much effort is associated with the search for pharmacological compounds capable of their prevention or dispersion. · Most of the primary screens associated with such work rely on in-vitro tests and in separating the blood from it's vasculature, the influence and results associated with several naturally occuring moderators may be lost. There therefore exists the incentive to develop more representative in-vivo screening methods. Following an introduction to the underlying physiology and pharmacology and a review of established screening methods, this thesis proceeds to describe the development of a novel technique suitable for such in-vivo studies. It's inception is shown to be a consequence of an amalgamation of ultrasonic methods associated with the clinical detection of occlusions and laser Doppler velocimetry. Both topics are individually surveyed and then brought together through a concept whereby the efficacy of compounds might be evaluated in animal models by measuring the velocity of blood in the fluid jet formed distal to an induced thrombus.The main underlying assumption is that the jet velocity will reflect the degree of encroachment of the thrombus into the vasculature. In accord with the evolved measurement rationale there then follows a description of a specific laser Doppler velocimeter and some associated experiments, designed to qualitatively appraise the validity of the underlying assumptions. The ensuing results in turn give rise to the design of a laser Doppler microscope, an analyser for extracting the required velocity information from the Doppler shift spectrum and an additional series of experiments. Central to this latter stage of validation is the use of a thrombus analogue in a narrow bored glass flow tube. Finally, some preliminary in-vivo experiments and results are presented

Optical Diagnostics in Human Diseases

Optical technologies provide unique opportunities for the diagnosis of various pathological disorders. The range of biophotonics applications in clinical practice is considerably wide given that the optical properties of biological tissues are subject to significant changes during disease progression. Due to the small size of studied objects (from μm to mm) and despite some minimum restrictions (low-intensity light is used), these technologies have great diagnostic potential both as an additional tool and in cases of separate use, for example, to assess conditions affecting microcirculatory bed and tissue viability. This Special Issue presents topical articles by researchers engaged in the development of new methods and devices for optical non-invasive diagnostics in various fields of medicine. Several studies in this Special Issue demonstrate new information relevant to surgical procedures, especially in oncology and gynecology. Two articles are dedicated to the topical problem of breast cancer early detection, including during surgery. One of the articles is devoted to urology, namely to the problem of chronic or recurrent episodic urethral pain. Several works describe the studies in otolaryngology and dentistry. One of the studies is devoted to diagnosing liver diseases. A number of articles contribute to the studying of the alterations caused by diabetes mellitus and cardiovascular diseases. The results of all the presented articles reflect novel innovative research and emerging ideas in optical non-invasive diagnostics aimed at their wider translation into clinical practice