The validity of corneal confocal microscopy (CCM) in assessing peripheral neuropathy has been studied extensively in several studies with a large cohort of subjects with diabetes and in a handful of studies with small sample sizes in subjects with other systemic conditions. The non-invasive nature of this technique as well as its high reproducibility, moderate to high sensitivity and specificity, and ease of use make it an ideal biomarker for diagnosing onset, severity and progression of peripheral neuropathy. This thesis aims to further investigate the potential of CCM by evaluating abnormalities in the corneal sub-basal nerve plexus, Langerhans Cells (LCs) and epithelial cells in neuropathy related to diabetes and cancer. This thesis has established that evaluating the sub-basal nerve plexus in the centre and at the inferior whorl increases the diagnostic performance of CCM. In addition to diagnosing clinical and subclinical neuropathy in children and adults with diabetes CCM can also identify sub-clinical nerve damage in patients with upper gastrointestinal cancer and assess the effects of chemotherapy. CCM also identifies differences in small fibre pathology between diabetic patients with and without painful neuropathy. Although there was an increased prevalence and severity of dry eye and LCs' density, this was not related to an abnormality of corneal nerves in diabetic patients with no or mild neuropathy. Epithelial cell morphology was not associated with corneal nerve damage and did not alter in patients with Type 1 diabetes. In conclusion, CCM has been shown to be an ideal marker for quantifying early small fibre pathology and assessing peripheral neuropathies.

The accurate detection and quantification of human diabetic somatic polyneuropathy (DSPN) are important to define at risk patients, anticipate deterioration, and assess new therapies. Current methods lack sensitivity, require expert assessment and have major shortcomings when employed to define therapeutic efficacy. In recent years, in vivo corneal confocal microscopy (IVCCM) has shown potential as a surrogate endpoint for DSPN.This study aims to investigate fundamental aspects of IVCCM such as repeatability and optimal scanning methodology and establish changes in corneal nerve morphology in relation to the severity of DSPN and regeneration in response to normalisation of hyperglycaemia. Furthermore, it aims to provide a novel fully automated image analysis algorithm for the quantification of corneal nerve morphology and establish the diagnostic ability of CCM.IVCCM shows high repeatability which is enhanced with more experienced observers. Central corneal innervation is comparable to adjacent peripheral innervation in mild diabetic neuropathy but the central cornea may be more sensitive to change. Corneal nerve loss is symmetrical and progressive with increasing neuropathic severity and corneal nerves show significant regenerative capacity following rapid normalisation of glycaemic control after simultaneous pancreas and kidney transplantation. The novel image analysis algorithm strongly correlates with human expert annotation and therefore represents a rapid, objective and repeatable means of assessing corneal nerve morphology. Automated image quantification may replace human manual assessment with high diagnostic validity for DSPN.

Yes / Endothelial dysfunction and damage underlie cerebrovascular disease and ischemic stroke. We undertook corneal confocal microscopy (CCM) to quantify corneal endothelial cell and nerve morphology in 146 patients with an acute ischemic stroke and 18 age-matched healthy control participants. Corneal endothelial cell density was lower (P<0.001) and endothelial cell area (P<0.001) and perimeter (P<0.001) were higher, whilst corneal nerve fbre density (P<0.001), corneal nerve branch density (P<0.001) and corneal nerve fbre length (P=0.001) were lower in patients with acute ischemic stroke compared to controls. Corneal endothelial cell density, cell area and cell perimeter correlated with corneal nerve fber density (P=0.033, P=0.014, P=0.011) and length (P=0.017, P=0.013, P=0.008), respectively. Multiple linear regression analysis showed a signifcant independent association between corneal endothelial cell density, area and perimeter with acute ischemic stroke and triglycerides. CCM is a rapid non-invasive ophthalmic imaging technique, which could be used to identify patients at risk of acute ischemic stroke. / Qatar National Research Fund Grant BMRP20038654

Yes / Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the nerve structures can assist the early diagnosis of this disease. This paper proposes a robust, fast and fully automatic nerve segmentation and morphometric parameter quantification system for corneal confocal microscope images. The segmentation part consists of three main steps. First, a preprocessing step is applied to enhance the visibility of the nerves and remove noise using anisotropic diffusion filtering, specifically a Coherence filter followed by Gaussian filtering. Second, morphological operations are applied to remove unwanted objects in the input image such as epithelial cells and small nerve segments. Finally, an edge detection step is applied to detect all the nerves in the input image. In this step, an efficient algorithm for connecting discontinuous nerves is proposed. In the morphometric parameters quantification part, a number of features are extracted, including thickness, tortuosity and length of nerve, which may be used for the early diagnosis of diabetic polyneuropathy and when planning Laser-Assisted in situ Keratomileusis (LASIK) or Photorefractive keratectomy (PRK). The performance of the proposed segmentation system is evaluated against manually traced ground-truth images based on a database consisting of 498 corneal sub-basal nerve images (238 are normal and 260 are abnormal). In addition, the robustness and efficiency of the proposed system in extracting morphometric features with clinical utility was evaluated in 919 images taken from healthy subjects and diabetic patients with and without neuropathy. We demonstrate rapid (13 seconds/image), robust and effective automated corneal nerve quantification. The proposed system will be deployed as a useful clinical tool to support the expertise of ophthalmologists and save the clinician time in a busy clinical setting.

Yes / Background and Objective Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. Methods First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). Results The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland–Altman plot shows that 95% of the data are between the 2SD agreement lines. Conclusions We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image.

Yes / The quantification of corneal endothelial cell (CEC) morphology using manual and semi-automatic software enables an objective assessment of corneal endothelial pathology. However, the procedure is tedious, subjective, and not widely applied in clinical practice. We have developed the CellsDeepNet system to automatically segment and analyse the CEC morphology. The CellsDeepNet system uses Contrast-Limited Adaptive Histogram Equalization (CLAHE) to improve the contrast of the CEC images and reduce the effects of non-uniform image illumination, 2D Double-Density Dual-Tree Complex Wavelet Transform (2DDD-TCWT) to reduce noise, Butterworth Bandpass filter to enhance the CEC edges, and moving average filter to adjust for brightness level. An improved version of U-Net was used to detect the boundaries of the CECs, regardless of the CEC size. CEC morphology was measured as mean cell density (MCD, cell/mm2), mean cell area (MCA, µm2), mean cell perimeter (MCP, µm), polymegathism (coefficient of CEC size variation), and pleomorphism (percentage of hexagonality coefficient). The CellsDeepNet system correlated highly significantly with the manual estimations for MCD (r = 0.94), MCA (r = 0.99), MCP (r = 0.99), polymegathism (r = 0.92), and pleomorphism (r = 0.86), with p

Yes / Confocal microscopy is employed as a fast and non-invasive way to capture a sequence of images from different layers and membranes of the cornea. The captured images are used to extract useful and helpful clinical information for early diagnosis of corneal diseases such as, Diabetic Peripheral Neuropathy (DPN). In this paper, an automatic corneal subbasal nerve registration system is proposed. The main aim of the proposed system is to produce a new informative corneal image that contains structural and functional information. In addition a colour coded corneal image map is produced by overlaying a sequence of Cornea Confocal Microscopy (CCM) images that differ in their displacement, illumination, scaling, and rotation to each other. An automatic image registration method is proposed based on combining the advantages of Fast Fourier Transform (FFT) and phase correlation techniques. The proposed registration algorithm searches for the best common features between a number of sequenced CCM images in the frequency domain to produce the formative image map. In this generated image map, each colour represents the severity level of a specific clinical feature that can be used to give ophthalmologists a clear and precise representation of the extracted clinical features from each nerve in the image map. Moreover, successful implementation of the proposed system and the availability of the required datasets opens the door for other interesting ideas; for instance, it can be used to give ophthalmologists a summarized and objective description about a diabetic patient’s health status using a sequence of CCM images that have been captured from different imaging devices and/or at different times

Introduction: Relation of diabetes mellitus (DM) to the diabetic keratopathy and various stages of corneal nerve fiber damage has been well accepted. A possible association between changes in the cornea of diabetic patients and diabetic retinopathy (DR), DM duration, and age at the time of DM diagnosis were evaluated. Neuropathies are among the most common long-term complications of diabetes mellitus. Good glycemic control is essential in prevention of this complication. DM patients with similar mean glucose levels or glycated hemoglobin (HbA1c) levels often exhibit differences in evaluation of diabetic complications. One reason for these differences may be the differences in glucose variability. DM patients with similar mean glucose levels or HbA1c levels often exhibit differences in glucose variability Hypothesis: Diabetes mellitus damages the subbasal nerve fibers of the corneal and affects the density of epithelial, endothelial and stromal cells. Corneal changes in patients with DM are dependent on the degree of diabetic retinopathy (DR), age at diagnosis, duration of DM, and compensation parameters. Purpose: To compare changes in cell density in individual layers of cornea and status of subbasal nerve fibers in patients with type 1 DM (DM 1) and in healthy subjects. To evaluate the dependence...

Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the corneal epithelium nerve structures and the corneal endothelial cell can assist early diagnosis of this disease and other corneal diseases, which can lead to visual impairment and then to blindness. In this thesis, fully-automated segmentation and quantification algorithms for processing and analysing sub-basal epithelium nerves and endothelial cells are proposed for early diagnosis of diabetic neuropathy in Corneal Confocal Microscopy (CCM) images. Firstly, a fully automatic nerve segmentation system for corneal confocal microscope images is proposed. The performance of the proposed system is evaluated against manually traced images with an execution time of the prototype is 13 seconds. Secondly, an automatic corneal nerve registration system is proposed. The main aim of this system is to produce a new informative corneal image that contains structural and functional information. Thirdly, an automated real-time system, termed the Corneal Endothelium Analysis System (CEAS) is developed and applied for the segmentation of endothelial cells in images of human cornea obtained by In Vivo CCM. The performance of the proposed CEAS system was tested against manually traced images with an execution time of only 6 seconds per image. Finally, the results obtained from all the proposed approaches have been evaluated and validated by an expert advisory board from two institutes, they are the Division of Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar and the Manchester Royal Eye Hospital, Centre for Endocrinology and Diabetes, UK.