Three-dimensional optical coherence tomography imaging of the optic nerve head

Background: the primary site of injury in glaucoma is likely to be at the lamina cribrosa (LC), deep within the optic nerve head (ONH). Optical coherence tomography (OCT) in glaucoma has, to date, focused on the detection of nerve fibre loss. Spectral domain OCT (SDOCT) has improved speed and axial resolution, allowing acquisition of three-dimensional ONH volumes and may capture targets deep within the ONH. This thesis explores the capabilities and potential of deep SDOCT imaging in the monkey ONH. Plan of research: an investigation was conducted into the detection of key landmarks that would be necessary for future quantification strategies. In particular, detection of the neural canal opening (NCO) was assessed and how the NCO relates to what is clinically identified as the disc margin. The next phase involved clarifying the anatomical and histological basis of ONH structures observed within SDCOT volumes, by comparison with histological sections and disc photographs. Finally, quantification strategies for novel parameters based on deep targets were developed and used to detect chronic longitudinal changes in experimental glaucoma and acute changes following IOP manipulation. Results: SDOCT reliably detects the NCO, which can be used as an anchoring structure for reference planes. Usually the NCO equates to the disc margin but disc margin architecture can be complex and highly variable. SDOCT captures the prelaminar tissue and anterior LC surface. Prelaminar thinning and posterior LC displacement were both detected longitudinally in experimental glaucoma. Prelaminar thinning was observed with acute IOP elevation; posterior LC movement was rare. Significance: deep ONH structures, including the LC, are realistic targets for clinical imaging. These imaging targets may be useful in the detection of glaucoma progression and in the verification of ex-vivo models of ONH biomechanical behaviour

The use of 1050nm OCT to identify changes in optic nerve head pathophysiology in glaucoma

Glaucoma is a progressive optic neuropathy that causes irreversible vision loss and is the second leading cause of blindness worldwide. Glaucoma is characterised by loss of retinal ganglion cells (RGC) and the proposed site of primary damage is the lamina cribrosa (LC), where RGC axonal transport is disrupted causing subsequent RGC damage and eventual cell death. Current detection for primary open angle glaucoma (POAG) is based upon clinical measures such as intraocular pressure (IOP), visual field loss and changes to the optic nerve head (ONH). However, for there to be an indication that there is a problem using these measures, often RGC damage has already occurred. Therefore it is crucial to determine ocular parameters that alter in the earliest stage of disease, prior to vision loss occurring. In this thesis optical coherence tomography (OCT) was used to assess the optic nerve heads and maculae of control eyes and eyes with preperimetric, early and advanced glaucoma in order to characterise changes that could potentially be used as biomarkers for the earliest stages of the disease. A custom built 1050 nm research OCT was used to acquire datasets from the macula and optic nerve heads of eyes glaucomatous and control eyes in vivo. Analysis of the inner retinal layers at the macula was performed to indirectly assess RGC integrity. At the ONH the prelamina and LC volume and regional depth and thicknesses were investigated. Additionally, nerve fibre layer and Bruch’s membrane parameters were assessed. Finally, LC beam coherence and orientation were probed in order to determine whether regional or glaucomatous changes ould be detected at the LC connective tissue microstructure. Prelamina depth and thickness was shown to be an indicator of early and preperimetric glaucoma (p0.01). Border nerve fibre layer revealed significant thinning in early glaucoma compared to control, and the superior peripapillary nerve fibre layer was thinner in preperimetric glaucoma than control. The ratio of inner plexiform layer (IPL) : ganglion cell layer (GCL) showed significant differences between control eyes and preperimetric glaucoma, and as such has potential to be a useful biomarker for indicating the earliest stages of disease. Both the GCL and IPL were thinner in early glaucoma than control (p<0.01), a hypothesis that cell body shrinkage and death occurs in preperimetric glaucoma and dendritic loss occurs in early glaucoma, when vision loss is first apparent, is suggested. Additionally, LC beams showed greater coherence in the superior and inferior poles than the temporal region, indicating that the shows regional variation but that further research is required to characterise changes. In conclusion, 1050 nm OCT was used to probe microstructural parameters of the optic nerve head in vivo to characterise changes that could be used as a potential biomarker for early glaucoma. ONH and retinal parameters have been identified that, with further research, may be used to differentiate between control eyes and those with preperimetric and early glaucoma. These have the potential to help identify those ONHs at risk of glaucoma damage

Retinal Fundus Image Analysis for Diagnosis of Glaucoma: A Comprehensive Survey

© 2016 IEEE. The rapid development of digital imaging and computer vision has increased the potential of using the image processing technologies in ophthalmology. Image processing systems are used in standard clinical practices with the development of medical diagnostic systems. The retinal images provide vital information about the health of the sensory part of the visual system. Retinal diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, Stargardt's disease, and retinopathy of prematurity, can lead to blindness manifest as artifacts in the retinal image. An automated system can be used for offering standardized large-scale screening at a lower cost, which may reduce human errors, provide services to remote areas, as well as free from observer bias and fatigue. Treatment for retinal diseases is available; the challenge lies in finding a cost-effective approach with high sensitivity and specificity that can be applied to large populations in a timely manner to identify those who are at risk at the early stages of the disease. The progress of the glaucoma disease is very often quiet in the early stages. The number of people affected has been increasing and patients are seldom aware of the disease, which can cause delay in the treatment. A review of how computer-aided approaches may be applied in the diagnosis and staging of glaucoma is discussed here. The current status of the computer technology is reviewed, covering localization and segmentation of the optic nerve head, pixel level glaucomatic changes, diagonosis using 3-D data sets, and artificial neural networks for detecting the progression of the glaucoma disease

A Parametric Model for the Analysis and Quantification of Foveal Shapes

Recently, the advance of OCT enables a detailed examination of the human retina in-vivo for clinical routine and experimental eye research. One of the structures inside the retina of immense scientific interest is the fovea, a small retinal pit located in the central region with extraordinary visual resolution. Today, only a few investigations captured foveal morphology based on a large subject group by a detailed analysis employing mathematical models. In this work, we develop a parametric model function to describe the shape of the human fovea. Starting with a detailed discussion on the history and present of fovea research, we define the requirements for a suitable model and derive a function which can represent a broad range of foveal shapes. The model is one-dimensional in its basic form and can only account for the shape of one particular section through a fovea. Therefore, we apply a radial fitting scheme in different directions which can capture a fovea in its full three-dimensional appearance. Highly relevant foveal characteristics, derived from the model, provide valuable descriptions to quantify the fovea and allow for a detailed analysis of different foveal shapes. To put the theoretical model into practice, we develop a numerical scheme to compute model parameters from retinal \ac{oct} scans and to reconstruct the shape of an entire fovea. For the sake of scientific reproducibility, this section includes implementation details, examples and a discussion of performance considerations. Finally, we present several studies which employed the fovea model successfully. A first feasibility study verifies that the parametric model is suitable for foveal shapes occurring in a large set of healthy human eyes. In a follow-up investigation, we analyse foveal characteristics occurring in healthy humans in detail. This analysis will concern with different aspects including, e.g. an investigation of the fovea's asymmetry, a gender comparison, a left versus right eye correlation and the computation of subjects with extreme foveal shapes. Furthermore, we will show how the model was used to support investigations unrelated to the direct quantification of the fovea itself. In these investigations we employed the model to compute anatomically correct regions of interest in an analysis of the OCB and the calculation of an average fovea for an optical simulation of light rays. We will conclude with currently unpublished data that shows the fovea modelling of hunting birds which have unusual, funnel-like foveal shapes

An in vivo investigation of optic nerve head microstructure in primary open angle glaucoma

Glaucoma remains the leading cause of irreversible blindness in the world. Since retinal ganglion cell (RGC) axonal degeneration precedes permanent vision loss, identification of ONH parameters affected in the earliest stages of primary open angle glaucoma (POAG) is critical to ensure early diagnosis. This cross-sectional study used enhanced-depth imaging optical coherence tomography (EDI-OCT; 1040/70nm) to acquire 10° and 20° scans centred on the ONH (glaucomatous; n=128 or healthy controls; n=60). Regional measures of prelamina and LC depth and thickness, nerve fibre layer thickness at ONH border (bNFL) and peripapillary (pNFL), neuroretinal minimum rim width; (MRW) and area; (MRA) were analysed. This is the first study to quantify volumetric parameters including optic cup, prelamina and LC volume, and also Bruch’s membrane opening (BMO) surface area. Furthermore, LC connective tissue alignment was probed regionally and depth-wise within the LC. Statistical modelling was performed to identify ONH parameters that best contributed to characterisation of ONHs in the earliest stages of POAG. Regional measures of prelamina depth and thickness, and LC thickness were able to differentiate between control eyes and preperimetric (PG), and early glaucoma (EG) (P<0.05). Additionally, EG LC volume was significantly less than in controls (P<0.05). Significant associations of these parameters with loss of VF sensitivity (VF Mean deviation [MD]) were identified. Border and pNFL thickness, MRW (but not MRA) significantly differed between controls and PG and EG (P<0.05); and decreased with VF MD. Lamina cribrosa connective tissue alignment altered in a region and depth specific manner between PG LC and controls, or EG LCs (P<0.05), providing an original in vivo indicator of disease. In conclusion, in vivo ONH and NFL parameters are able to discriminate between healthy ONHs and early POAG ONHs; providing a group index with potential as a novel biomarker for early diagnosis, critical to personalised clinical decision making

Investigating neuroinflammatory disease through retinal imaging and biomarkers

Neuroinflammatory diseases, in particular multiple sclerosis (MS) and neuromyelitis optica spectrum disorder, often affect the anterior visual pathways. This can occur through direct inflammatory insult in the form of optic neuritis or through retrograde degeneration, but progressive neurodegenerative processes related to axonal loss and atrophy also play a role. Energy failure has been postulated as an important factor mediating factor in these neurodegenerative processes, but its exact role is poorly understood. The advent of optical coherence tomography (OCT) enables high resolution imaging of the retina with relative ease. In neurology research, OCT has mostly been used to quantify retinal layer thicknesses. This thesis focuses on the largely unexplored potential of OCT as a functional biomarker. The primary aim is to develop indirect non-invasive in-vivo biomarkers informing on metabolic function, taking into account the high energy demand of the retina, particularly during dark-adaptation. First, two novel functional OCT measures are presented; the dynamic dark-adaptation related thickening of the outer retinal layers and the relative reflectivity of the ellipsoid zone (EZ), which comprises the majority of retinal mitochondria. Both measures appeared to be reduced in acute optic neuritis, and also in chronic neuroinflammatory disease in the case of EZ reflectivity. Furthermore, pilot OCT-angiography (OCTA) data indicated that vascular density was reduced in acute optic neuritis. As reduced EZ reflectivity and lower vascular density were present to a similar degree in both eyes of acute optic neuritis patients suggest that a background level of mitochondrial dysfunction and hypoperfusion may occur in neuroinflammatory disease, independent from acute inflammatory activity. The work presented in this thesis illustrates that OCT has the potential to provide valuable information on retinal function in neuroinflammatory disease. In the future, artificial intelligence and big data analysis may enable the development of a holistic analysis method for raw OCT data, providing a summary report on both qualitative, such as presence of microcystic macular oedema (MMO), and quantitative scan features, such as layer thickness, vascular density and reflectivity. Comprehensive analysis of both functional and structural OCT data may facilitate diagnosis, inform on prognosis and provide important insight into the role of metabolic failure in the pathophysiology of neuroinflammatory disease

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

Optic Nerve Deformation by Eye Movements

Ocular rotation can cause mechanical deformation of the optic nerve head and surrounding tissues. During extreme angles of gaze, the optic nerve can become stretched and impose strain on other ocular tissues. Over a lifetime, the ill effects of repetitive mechanical injury from large adduction can compound, resulting in progressive optic neuropathy in some glaucoma patients.We investigated the etiology of this form of glaucoma through a series of papers focusing on anatomical analysis of the human optic nerve from donated tissue and clinical studies utilizing optical coherence tomography (OCT) and confocal scanning laser ophthalmoscopy (cSLO). The optic nerve is surrounded and protected by a bi-layered dural sheath that bears the bulk of exerted mechanical force. Elastin fibers embedded within the sheath and peripapillary tissues around the nerve head form a three-dimensional meshwork that reinforces the tissue against mechanical strain. While the tissue at the globe optic nerve junction is heavily fortified with organized layers of collagen and elastin fibers, irregularities in the elastin fiber arrangement resulting in large dense elastin deposits were observed to correlate with older age. These elastin deposits could be a pathologic byproduct of optic nerve injury from mechanical strain, or serve as a protective mechanism to further reinforce the ocular tissues.In OCT studies, adduction of angles beyond 26� caused marked deformation of the peripapillary tissues around the optic nerve head, and choroidal volume change. cSLO imaging showed similar deformations of the retina surface during large angle adduction. Ocular tissue of younger subjects appears more compliant, while those of glaucoma patients were stiffer and thus experienced less deformation.We explored possible therapies for optic nerve traction during eye movement. Using collagen crosslinking to fortify ocular tissue, we observed that exposure to riboflavin and UV light can stiffen scleral tissue. In addition, we investigated whether prostaglandin agonists could be used to reduce ocular fat and found that topical administration of these agonists had insignificant effects on the retrobulbar fat

Multi-modal imaging in Ophthalmology: image processing methods for improving intra-ocular tumor treatment via MRI and Fundus image photography

The most common ocular tumors in the eye are retinoblastoma and uveal melanoma, affecting children and adults respectively, and spreading throughout the body if left untreated. To date, detection and treatment of such tumors rely mainly on two imaging modalities: Fundus Image Photography (Fundus) and Ultrasound (US), however, other image modalities such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are key to confirm a possible tumor spread outside the eye cavity. Current procedures to select the best treatment and follow-up are based on manual multimodal measures taken by clinicians. These tasks often require the manual annotation and delineation of eye structures and tumors, a rather tedious and time consuming endeavour, to be performed in multiple medical sequences simultaneously. ################################ This work presents a new set of image processing methods for improving multimodal evaluation of intra-ocular tumors in 3D MRI and 2D Fundus. We first introduce a novel technique for the automatic delineation of ocular structures and tumors in the 3D MRI. To this end, we present an Active Shape Model (ASM) built out of a dataset of healthy patients to demonstrate that the segmentation of ocular structures (e.g. the lens, the vitreous humor, the cornea and the sclera) can be performed in an accurate and robust manner. To validate these findings, we introduce a set of experiments to test the model performance on eyes with presence of endophytic retinoblastoma, and discover that the segmentation of healthy eye structures is possible, regardless of the presence of the tumor inside the eyes. Moreover, we propose a specific set of Eye Patient-specific eye features that can be extracted -- Le rétinoblastome et le mélanome uvéal sont les types de cancer oculaire les plus communs, touchant les enfants et adultes respectivement, et peuvent se répandre à travers l’organisme s’ils ne sont pas traités. Actuellement, le traitement pour la détection du rétinoblastome se base essentiellement à partir de deux modalites d’imagerie fond d’œil (Fundus) et l’ultrason (US). Cependant, d’autres modalités d’imagerie comme l’Imagerie par Résonance magnétique (IRM) et la Tomodensitométrie (TDM) sont clé pour confirmer la possible expansion du cancer en dehors de la cavité oculaire. Les techniques utilisées pour déterminer la tumeur oculaire, ainsi que le choix du traitement, se basent sur des mesures multimodales réalisées de manière manuelle par des médecins. Cette méthodologie manuelle est appliquée quotidiennement et continuellement pendant toute la durée de la maladie. Ce processus nécessite souvent la délinéation manuelle des structures ocularies et de la tumeur, un mécanisme laborieux et long, effectuée dans des multiples séquences médicales simultanées (par exemple : T1-weighted et T2-weighted IRM ...) qui augmentent la difficulté pour évaluer la maladie. Le présent travail présente une nouvelle série de techniques permettant d’améliorer l´évaluation multimodale de tumeurs oculaires en IRM et Fundus. Dans un premier temps, nous intro- duisons une méthode qui assure la délinéation automatique de la structure oculaire et de la tumeur dans un IRM 3D. Pour cela, nous présentons un Active Shape Model (ASM) construite à partir d’un ensemble de données de patients en bonne santé pour prouver que la segmenta- tion automatique de la structure oculaire (par exemple : le cristallin, l´humeur aqueuse, la cornée et la sclère) peut être réalisée de manière précise et robuste. Afin de valider ces résultats, nous introduisons un ensemble d’essais pour tester la performance du modèle par rapport à des yeux de patients affectés pathologiquement par un rétinoblastome, et démontrons que la segmentation de la structure oculaire d’un œil sain est possible, indépendamment de la présence d’une tumeur à l’intérieur des yeux. De plus, nous proposons une caractérisation spécifique du patient-specific eye features qui peuvent être utile pour la segmentation de l’œil dans l’IRM 3D, fournissant des formes riches et une information importante concernant le tissu pathologique noyé dans la structure oculaire de l’œil sain. Cette information est ultérieurement utilisée pour entrainer un ensemble de classificateurs (Convolutional Neural Network (CNN), Random Forest, . . . ) qui réalise la segmentation automatique de tumeurs oculaires à l’intérieur de l’œil. En outre, nous explorons une nouvelle méthode pour évaluer des multitudes de séquences d’images de manière simultanée, fournissant aux médecins un outil pour observer l’extension de la tumeur dans le fond d’œil et l’IRM. Pour cela, nous combinons la segmentation auto- matique de l’œil de l’IRM selon la description ci-dessus et nous proposons une delineation manuelle de tumeurs oculaires dans le fond d’œil. Ensuite, nous recalons ces deux modalités d’imagerie avec une nouvelle base de points de repère et nous réalisons la fusion des deux modalités. Nous utilisons cette nouvelle méthode pour (i) améliorer la qualité de la délinéation dans l’IRM et pour (ii) utiliser la projection arrière de la tumeur pour transporter de riches me- sures volumétriques de l’IRM vers le fond d’œil, en créant une nouvelle forme 3D représentant le fond d’œil 2D dans une méthode que nous appelons Topographic Fundus Mapping. Pour tous les tests et contributions, nous validons les résultats avec une base de données d’IRM et une base de données d’images pathologiques du fond d’œil de rétinoblastome