Data mining for AMD screening: A classification based approach

This paper investigates the use of three alternative approaches to classifying retinal images. The novelty of these approaches is that they are not founded on individual lesion segmentation for feature generation, instead use encodings focused on the entire image. Three different mechanisms for encoding retinal image data were considered: (i) time series, (ii) tabular and (iii) tree based representations. For the evaluation two publically available, retinal fundus image data sets were used. The evaluation was conducted in the context of Age-related Macular Degeneration (AMD) screening and according to statistical significance tests. Excellent results were produced: Sensitivity, specificity and accuracy rates of 99% and over were recorded, while the tree based approach has the best performance with a sensitivity of 99.5%. Further evaluation indicated that the results were statistically significant. The excellent results indicated that these classification systems are ideally suited to large scale AMD screening processes

Retinal vessel segmentation using textons

Segmenting vessels from retinal images, like segmentation in many other medical image domains, is a challenging task, as there is no unified way that can be adopted to extract the vessels accurately. However, it is the most critical stage in automatic assessment of various forms of diseases (e.g. Glaucoma, Age-related macular degeneration, diabetic retinopathy and cardiovascular diseases etc.). Our research aims to investigate retinal image segmentation approaches based on textons as they provide a compact description of texture that can be learnt from a training set. This thesis presents a brief review of those diseases and also includes their current situations, future trends and techniques used for their automatic diagnosis in routine clinical applications. The importance of retinal vessel segmentation is particularly emphasized in such applications. An extensive review of previous work on retinal vessel segmentation and salient texture analysis methods is presented. Five automatic retinal vessel segmentation methods are proposed in this thesis. The first method focuses on addressing the problem of removing pathological anomalies (Drusen, exudates) for retinal vessel segmentation, which have been identified by other researchers as a problem and a common source of error. The results show that the modified method shows some improvement compared to a previously published method. The second novel supervised segmentation method employs textons. We propose a new filter bank (MR11) that includes bar detectors for vascular feature extraction and other kernels to detect edges and photometric variations in the image. The k-means clustering algorithm is adopted for texton generation based on the vessel and non-vessel elements which are identified by ground truth. The third improved supervised method is developed based on the second one, in which textons are generated by k-means clustering and texton maps representing vessels are derived by back projecting pixel clusters onto hand labelled ground truth. A further step is implemented to ensure that the best combinations of textons are represented in the map and subsequently used to identify vessels in the test set. The experimental results on two benchmark datasets show that our proposed method performs well compared to other published work and the results of human experts. A further test of our system on an independent set of optical fundus images verified its consistent performance. The statistical analysis on experimental results also reveals that it is possible to train unified textons for retinal vessel segmentation. In the fourth method a novel scheme using Gabor filter bank for vessel feature extraction is proposed. The ii method is inspired by the human visual system. Machine learning is used to optimize the Gabor filter parameters. The experimental results demonstrate that our method significantly enhances the true positive rate while maintaining a level of specificity that is comparable with other approaches. Finally, we proposed a new unsupervised texton based retinal vessel segmentation method using derivative of SIFT and multi-scale Gabor filers. The lack of sufficient quantities of hand labelled ground truth and the high level of variability in ground truth labels amongst experts provides the motivation for this approach. The evaluation results reveal that our unsupervised segmentation method is comparable with the best other supervised methods and other best state of the art methods

Developmental insights and biomedical potential of human embryonic stem cells : modelling trophoblast differentiation and establishing novel cell therapies for age-related macular degeneration

Understanding the molecular pathways responsible for lineage segregation in the preimplantation human embryo is critical in order to fully elucidate the mechanisms involved in pluripotency and differentiation of embryonic stem cells. A significant increase in our comprehension of such processes will lead to an improvement in the quality and efficiency of these cells for applications requiring stem cell maintenance and differentiation, such as regenerative medicine. Through responsible and ethical research, such new knowledge can then be translated effectively and efficiently into future advancements in health and medical practices. This thesis focuses on two different applications of human embryonic stem cells (hESC): first, as an in-vitro model to investigate the genetic requirements for human trophoblast formation and second, as a cell replacement therapy for age-related macular degeneration (AMD) through the establishment of efficient, scalable, and clinically compliant protocols for their differentiation into retinal pigment epithelium cells (RPE). In paper I, we used human embryonic stem cells to model trophoblast establishment and differentiation in order to better understand the mechanisms governing trophectoderm segregation in the embryo. Combining this in-vitro model with the use of pharmacological inhibitors and CRISPR/Cas9 genome editing, we demonstrated that blockade of the YAP1/WWTR1-TEAD complex impairs not only trophoblast differentiation, but also survival of undifferentiated stem cells. Furthermore, through systematic targeting of the different components of the complex, we described a dominant role for YAP1 in these processes and a striking genetic and functional redundancy of the function of TEAD proteins. Altogether, the findings indicate a role for the Hippo signaling pathway, both in human trophectoderm segregation and in maintaining human pluripotency. In papers II and III, we developed xeno-free and defined methodologies for the differentiation of human embryonic stem cells into RPE with the potential for use in replacement therapies for common retinal degenerative diseases, such as age-related macular degeneration. These invitro derived cells exhibited specific morphological and molecular features and functional properties that are typical of native RPE. In addition, upon subretinal transplantation into a large-eyed animal model, hESC-derived RPE cells were able to integrate and survive for extensive periods of time and rescued the neuroretina from the damage induced at the moment of injection. Finally, we identified a set of unique cell surface markers that were able to distinguish the RPE from other potential contaminating cell types or undifferentiated remnants and demonstrated their utility in monitoring differentiation efficiency and in increasing the purity and homogeneity of the final cell product. Through this work, we demonstrate that human embryonic stem cells hold enormous potential for modeling specific aspects of human development, which can help to elucidate the complex mechanisms governing lineage segregation and support the production of bona fide differentiated cell types to serve in future replacement therapies

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

Acquired Resilience: An Evolved System of Tissue Protection in Mammals.

This review brings together observations on the stress-induced regulation of resilience mechanisms in body tissues. It is argued that the stresses that induce tissue resilience in mammals arise from everyday sources: sunlight, food, lack of food, hypoxia and physical stresses. At low levels, these stresses induce an organised protective response in probably all tissues; and, at some higher level, cause tissue destruction. This pattern of response to stress is well known to toxicologists, who have termed it hormesis. The phenotypes of resilience are diverse and reports of stress-induced resilience are to be found in journals of neuroscience, sports medicine, cancer, healthy ageing, dementia, parkinsonism, ophthalmology and more. This diversity makes the proposing of a general concept of induced resilience a significant task, which this review attempts. We suggest that a system of stress-induced tissue resilience has evolved to enhance the survival of animals. By analogy with acquired immunity, we term this system \u27acquired resilience\u27. Evidence is reviewed that acquired resilience, like acquired immunity, fades with age. This fading is, we suggest, a major component of ageing. Understanding of acquired resilience may, we argue, open pathways for the maintenance of good health in the later decades of human life

Real-time bioimpedance measurements of stem cellbased disease models-on-a-chip

In vitro disease models are powerful platforms for the development of drugs and novel therapies. Stem-cell based approaches have emerged as cutting-edge tools in disease modelling, allowing for deeper insights into previously unknown disease mechanisms. Hence the significant role of these disease-in-a-dish methods in therapeutics and translational medicine. Impedance sensing is a non-invasive, quantitative technique that can monitor changes in cellular behaviour and morphology in real-time. Bioimpedance measurements can be used to characterize and evaluate the establishment of a valid disease model, without the need for invasive end-point biochemical assays. In this work, two stem cell-based disease models-on-a-chip are proposed for acute liver failure (ALF) and age-related macular degeneration (AMD). The ALF disease model-on-a-chip integrates impedance sensing with the highly-differentiated HepaRG cell line to monitor in real-time quantitative and dynamic response to various hepatotoxins. Bioimpedance analysis and modelling has revealed an unknown mechanism of paracetamol hepatotoxicity; a temporal, dose-dependent disruption of tight junctions (TJs) and cell-substrate adhesion. This disruption has been validated using ultrastructural imaging and immunostaining of the TJ-associated protein ZO-1. Age-related macular degeneration (AMD) is the leading cause of blindness in the developed world with a need for disease models for its currently incurable forms. Human induced pluripotent stem cells (hiPSCs) technology offers a novel approach for disease modelling, with the potential to impact translational retinal research and therapy. Recent developments enable the generation of Retinal Pigment Epithelial cells from patients (hiPSC-RPE), thus allowing for human retinal disease in vitro studies with great clinical and physiological relevance. In the current study, the development of a tissue-on- a-chip AMD disease model has been established using RPE generated from a patient with an inherited macular degeneration (case cell line) and from a healthy sibling (control cell line). A reproducible Electric Cell-substrate Impedance Sensing (ECIS) electrical wounding assay was conducted to mimic RPE damage in AMD. First, a robust and reproducible real-time quantitative monitoring over a 25-day period demonstrated the establishment and maturation of RPE layers on microelectrodes. A spatially-controlled RPE layer damage that mimicked cell loss in AMD was then initiated. Post recovery, significant differences in migration rates were found between case and control cell lines. Data analysis and modelling suggested this was due to the lower cell-substrate adhesion of the control cell line. These findings were confirmed using cell adhesion biochemical assays. Moreover, different-sized, individually-addressed square microelectrode arrays with high spatial resolution were designed and fabricated in-house. ECIS wounding assays were performed on these chips to study immortalized RPE migration. Migration rates comparable to those obtained with ECIS circular microelectrodes were determined. The two proposed disease-models-on-a-chip were then used to explore the therapeutic potential of the antioxidant N-Acetyl-Cysteine (NAC) on hiPSC-RPE and HepaRG cell recovery. Addition of 10 mM NAC at the end of a 24h paracetamol challenge caused a slight increase in the measured impedance, suggesting partial cell recovery. On the other hand, no effect on case hiPSC-RPE migration has been observed. More experiments are needed to examine the effect of different NAC concentrations and incubation periods. The therapeutic potential of electrical stimulation has also been explored. A preliminary study to evaluate the effect of electrical stimulation on RPE migration has been conducted. An externally applied direct current electric field (DC EF) of 300 mV/mm was found to direct the migration of the immortalized RPE cell line (hTERT-RPE1) perpendicular to the EF. The cells were also observed to elongate and to realign their long axes perpendicular to the applied EF. The proposed tissue-on-a-chip disease models are powerful platforms for translational studies. The potential of such platforms has been demonstrated through revealing unknown effects of acetaminophen on the liver as well as providing deeper insights into the underlying mechanisms of macular degeneration. Combining stem cell technology with impedance sensing provides a high throughput platform for studying patient-specific diseases and evaluating potential therapies

Preclinical Animal Modeling in Medicine

The results of preclinical animal research have been successfully implemented in various medical and biological practices. The use of animals in medicine is based on significant anatomical, physiological, and molecular similarities between humans and animals. Particularly, mammals that have vast biological commonalities with humans represent not only a valuable model to explore the mechanisms of varied human diseases, but also to define new diagnostic and treatment strategies. This book covers broad but important aspects of animal modeling for scientific medicine as well as for translational systems and biological sciences. Alternative methods such as cell culture and in vitro experiments that do not require the sacrifice of an animal are encouraged for scientific and medical studies

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

An Optoelectronic Stimulator for Retinal Prosthesis

Retinal prostheses require the presence of viable population of cells in the inner retina. Evaluations of retina with Age-Related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP) have shown a large number of cells remain in the inner retina compared with the outer retina. Therefore, vision loss caused by AMD and RP is potentially treatable with retinal prostheses. Photostimulation based retinal prostheses have shown many advantages compared with retinal implants. In contrary to electrode based stimulation, light does not require mechanical contact. Therefore, the system can be completely external and not does have the power and degradation problems of implanted devices. In addition, the stimulating point is flexible and does not require a prior decision on the stimulation location. Furthermore, a beam of light can be projected on tissue with both temporal and spatial precision. This thesis aims at fi nding a feasible solution to such a system. Firstly, a prototype of an optoelectronic stimulator was proposed and implemented by using the Xilinx Virtex-4 FPGA evaluation board. The platform was used to demonstrate the possibility of photostimulation of the photosensitized neurons. Meanwhile, with the aim of developing a portable retinal prosthesis, a system on chip (SoC) architecture was proposed and a wide tuning range sinusoidal voltage-controlled oscillator (VCO) which is the pivotal component of the system was designed. The VCO is based on a new designed Complementary Metal Oxide Semiconductor (CMOS) Operational Transconductance Ampli er (OTA) which achieves a good linearity over a wide tuning range. Both the OTA and the VCO were fabricated in the AMS 0.35 µm CMOS process. Finally a 9X9 CMOS image sensor with spiking pixels was designed. Each pixel acts as an independent oscillator whose frequency is controlled by the incident light intensity. The sensor was fabricated in the AMS 0.35 µm CMOS Opto Process. Experimental validation and measured results are provided