An approach to the quantitative assessment of retinal layer distortions and subretinal fluid in SD-OCT images

A modern tool for age-related macular degeneration (AMD) investigation is Optical Coherence Tomography (OCT), which can produce high resolution cross-sectional images of retinal layers. AMD is one of the most frequent reasons for blindness in economically developed countries. AMD means degeneration of the macula, which is responsible for central vision. Since AMD affects only this specific part of the retina, untreated patients lose their fine shape- and face recognition, reading ability, and central vision. Here, we deal with the automatic localization of subretinal fluid areas and also analyze retinal layers, since layer information can help to localize fluid regions. We present an algorithm that automatically delineates the two extremal retinal layers, successfully localizes subretinal fluid regions, and computes their extent. We present our results using a set of SD-OCT images. The quantitative information can also be visualized in an anatomical context for visual assessment

Fundus Autofluorescence and Clinical Applications

Fundus autofluorescence (FAF) has allowed in vivo mapping of retinal metabolic derangements and structural changes not possible with conventional color imaging. Incident light is absorbed by molecules in the fundus, which are excited and in turn emit photons of specific wavelengths that are captured and processed by a sensor to create a metabolic map of the fundus. Studies on the growing number of FAF platforms has shown each may be suited to certain clinical scenarios. Scanning laser ophthalmoscopes, fundus cameras, and modifications of these each have benefits and drawbacks that must be considered before and after imaging to properly interpret the images. Emerging clinical evidence has demonstrated the usefulness of FAF in diagnosis and management of an increasing number of chorioretinal conditions, such as agerelated macular degeneration, central serous chorioretinopathy, retinal drug toxicities, and inherited retinal degenerations such as retinitis pigmentosa and Stargardt disease. This article reviews commercial imaging platforms, imaging techniques, and clinical applications of FAF

An overview of the clinical applications of optical coherence tomography angiography

Optical coherence tomography angiography (OCTA) has emerged as a novel, non-invasive imaging modality that allows the detailed study of flow within the vascular structures of the eye. Compared to conventional dye angiography, OCTA can produce more detailed, higher resolution images of the vasculature without the added risk of dye injection. In our review, we discuss the advantages and disadvantages of this new technology in comparison to conventional dye angiography. We provide an overview of the current OCTA technology available, compare the various commercial OCTA machines technical specifications and discuss some future software improvements. An approach to the interpretation of OCTA images by correlating images to other multimodal imaging with attention to identifying potential artefacts will be outlined and may be useful to ophthalmologists, particularly those who are currently still unfamiliar with this new technology. This review is based on a search of peer-reviewed published papers relevant to OCTA according to our current knowledge, up to January 2017, available on the PubMed database. Currently, many of the published studies have focused on OCTA imaging of the retina, in particular, the use of OCTA in the diagnosis and management of common retinal diseases such as age-related macular degeneration and retinal vascular diseases. In addition, we describe clinical applications for OCTA imaging in inflammatory diseases, optic nerve diseases and anterior segment diseases. This review is based on both the current literature and the clinical experience of our individual authors, with an emphasis on the clinical applications of this imaging technology.Eye advance online publication, 8 September 2017; doi:10.1038/eye.2017.181

The Concurrent Use of Medical Imaging Modalities and Innovative Treatments to Combat Retinitis Pigmentosa

Retinitis pigmentosa (RP), one of the leading causes of vision loss and blindness globally, is a progressive retinal disease involving the degradation of photoreceptors (7) and/or retinal pigment epithelial cells (14). Affecting approximately 1 in 4000 people, RP is caused by a series of genetic mutations; each specific mutation presents a specific pathological pattern in the patient, with the same mutation even presenting in different phenotypes in different patients (14). RP generally starts with peripheral vision loss, attacking the rods first, causing nyctalopia or night blindness (22). In later stages of the disease, the cones start to atrophy, further narrowing the field of vision and obscuring central vision (22). Luckily, with recent advances in medical imaging techniques and novel therapeutic treatments, both early detection and the overall prognosis of RP in patients have improved dramatically in the past few decades. This review will trace RP's physiological causes, how it affects retinal and ocular physiology, the techniques through which we can diagnose and image it, and the various treatments developed to try to combat it. The medical imaging techniques to be discussed include but are not limited to adaptive optics (AO), OCT including SD-OCT and OCTA, fundus autofluorescence (FAF) and its associated fluorescence lifetime imaging ophthalmoscopy (FLIO), colour Doppler flow imaging (CDFI), microperimetry, and MRI. The treatments to be discussed include stem cell therapy, gene therapy, cell transplantation, pharmacological therapy, and artificial retinal implants. Throughout this review, it will be made evident of not just the severity and diversity through which RP can present, but also the advanced made in medical imaging and innovative treatments designed to combat this pathology.Comment: 39 pages, 23 figure

In vivo Assessment of Structural Components of Retinal Degeneration in Animal Models

Human inherited retinal degenerative disorders exhibit a large genetic and phenotypic heterogeneity. Retinitis Pigmentosa (RP), one of the most severe forms, denotes a group of hereditary disorders of the rod system that cause progressive retinal degeneration and may eventually lead to blindness. Achromatopsia is characterized by a total loss of function of all cone photoreceptors in the retina, leading to a severe visual impairment. So far, no cure or scientifically proven symptomatic treatment has been found for neither RP nor Achromatopsia. Because the full course of the disease is difficult to follow in patients, the availability of genetically engineered animal models is instrumental to uncover the pathophysiological mechanisms underlying the disease. The aim of this project was to apply and further develop retinal imaging technology in order to refine in vivo structural information as a basis to better understand the mechanisms of the pathophysiology associated with inherited retinal diseases. Particularly within the scope of this thesis, major advances have been made in an early-onset form of RP called Leber’s Congenital Amaurosis (LCA) and two photoreceptor channelopathies that affect the rod and the cone system, respectively. This is complemented by the development of novel structural biomarkers for the follow-up of therapeutic strategies in both rod- and cone-centered disease classes. The first part of the thesis introduces recent insights in the mechanisms of interaction of Crumbs proteins and the potential exchangeability of the different forms by means of respective mouse models: Crb1-/-, Crb2-/- and the Crb1Crb2 double knock-out mouse. It has been found that the lack of Crb1 resulted in a partial degeneration of the retina, whereas the lack of Crb2 induced a severe retinal degeneration similar to that of Retinitis Pigmentosa. The simultaneous ablation of both proteins mimics the characteristic retinal degeneration pattern showed by Leber Congenital Amarosis type (LCA) patients. This work has led to substantial progress in the field and several publications in a number of high-ranking journals (publication list 2,5,9,17,18). The second part addresses the work on the restoration of function and morphology in a mouse model of Retinitis Pigmentosa or Achromatopsia, lacking the Cngb1 and Cnga3 proteins, respectively. Both approaches were performed by means of an adeno-associated viral (AAV) therapy. For the short –and long term assessment of therapeutic effects, novel morphological biomarkers based on optical coherence (OCT) data were develop. This work was documented in Koch et. al. 2012 and in Mühlfriedel et al. 2013. The third part is devoted to the expansion of the diagnostic repertoire by improved, more informative biomarkers for therapy assessment beyond the state-of-the-art. The work is based on OCT, a novel technique for the in vivo visualization of retinal layers. Here, a quantitative method for a more detailed description of the retinal structure by means of reflectivity profiles was designed. This method was verified in three common laboratory species with differences in retinal architechture. Finally, the problem of unequal scales for the measurement of two-dimensional structures was resolved. Intraocular objects of known dimensions in the murine eye were used for the equal calibration of axes in OCT images. This work was reported in Garcia Garrido et al. 2014 and Garcia Garrido et al. 2015

Graph Theory and Dynamic Programming Framework for Automated Segmentation of Ophthalmic Imaging Biomarkers

<p>Accurate quantification of anatomical and pathological structures in the eye is crucial for the study and diagnosis of potentially blinding diseases. Earlier and faster detection of ophthalmic imaging biomarkers also leads to optimal treatment and improved vision recovery. While modern optical imaging technologies such as optical coherence tomography (OCT) and adaptive optics (AO) have facilitated in vivo visualization of the eye at the cellular scale, the massive influx of data generated by these systems is often too large to be fully analyzed by ophthalmic experts without extensive time or resources. Furthermore, manual evaluation of images is inherently subjective and prone to human error.</p><p>This dissertation describes the development and validation of a framework called graph theory and dynamic programming (GTDP) to automatically detect and quantify ophthalmic imaging biomarkers. The GTDP framework was validated as an accurate technique for segmenting retinal layers on OCT images. The framework was then extended through the development of the quasi-polar transform to segment closed-contour structures including photoreceptors on AO scanning laser ophthalmoscopy images and retinal pigment epithelial cells on confocal microscopy images. </p><p>The GTDP framework was next applied in a clinical setting with pathologic images that are often lower in quality. Algorithms were developed to delineate morphological structures on OCT indicative of diseases such as age-related macular degeneration (AMD) and diabetic macular edema (DME). The AMD algorithm was shown to be robust to poor image quality and was capable of segmenting both drusen and geographic atrophy. To account for the complex manifestations of DME, a novel kernel regression-based classification framework was developed to identify retinal layers and fluid-filled regions as a guide for GTDP segmentation.</p><p>The development of fast and accurate segmentation algorithms based on the GTDP framework has significantly reduced the time and resources necessary to conduct large-scale, multi-center clinical trials. This is one step closer towards the long-term goal of improving vision outcomes for ocular disease patients through personalized therapy.</p>Dissertatio

Diagnosis, Treatment and Prevention of Age-Related Macular Degeneration

In this reprint, we hope to review the basics and highlight the latest developments in AMD. This demonstrates the benefits of the international scientific community working on this disease, to limit its negative impacts, the most vital of which is the loss of visual function, leading to a loss of autonomy and a decrease in patients’ quality of life