Active clinical trials for "Macular Degeneration"

The primary goals of this study are to use optical coherence tomography (OCT) angiography (blood vessel mapping) to: diagnose the presence of new blood vessels in wet age-related macular degeneration (AMD) evaluate patients undergoing treatment for wet AMD determine if reduced flow to the choroid is a risk factor for developing wet AMD.

Comparison of high-resolution optical coherence tomography (High-Res-OCT) to conventional imaging modalities for the diagnosis of eye diseases

The investigators wish to better understand the role of the choriocapillaris (CC) in the formation and progression of non-exudative in age related macular degeneration (armd) by imaging the retinal pigment epithelium (rpe) and the choroidal microvasculature and by studying their inter-dependence to determine if the loss of the CC could prove useful as an anatomic clinical trial endpoint in future drug trials.

This is a single arm study of home monitoring with the NVHO for 5 weeks with office visits at enrollment, Week 1 and Week 5 (Exit Visit) and, when applicable, Interim Visit(s) triggered by ongoing review by the Reading Center. The study will enroll subjects diagnosed with NV-AMD in at least one eye with attention to the proportion of eyes with IRF and/or SRF. The enrolled eligible subjects will be instructed to self-image the study eye(s) once daily for 5 weeks using a NVHO device at home with scheduled in-office examinations at Week 1, Week 5 and Interim Visits, when applicable, with additional in-office Cirrus volume scans acquired at these office visits. The self-imaging data on the NVHO will be automatically uploaded to the Notal Health Cloud and from there the reconstructed volume scans will sent to the study database.

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss worldwide, and nearly two million Australians have some signs of AMD. This proposed project is a prospective, observational study that seeks to to understand the underlying aetiology of AMD, factors associated with differences between age-related macular degeneration (AMD) phenotypes or severities, or between AMD and healthy individuals. It also seeks to understand the natural history of AMD progression and the factors associated with the rate of progression. In this project, the disease phenotype, genotype and severity and rate of progression will be determined based on non-invasive clinical imaging or functional assessment of the retina, from obtaining biological samples from the participants, or from patient-reported outcomes.

Age-related macular degeneration (AMD) is the leading cause of visual impairment in the UK. The condition is characterised by damage to the region of the retina (macula) responsible for detailed central vision, this leading to problems with tasks such as reading and face-recognition. The ability to accurately measure vision is central to the detection and management of AMD. The most common test (visual acuity) typically requires patients to identify black letters of varying size on a white background, with the smallest letter read representing the limit of vision. Conventional tests are however known to be variable, making it difficult to determine if a true change in vision has occurred. Previous work has found the Moorfields Acuity Chart, which contains specially constructed letters composed of a black core and white border, to be more sensitive to early AMD compared to standard charts. Despite this advantage, it is unclear if there is an associated increase in measurement variability with the Moorfields Acuity Chart and if this changes with the severity of disease. In this study, the relationship between vision test sensitivity and measurement variability will be quantified with both conventional visual acuity tests and the new Moorfields Acuity Chart to identify the optimal vision test to detect and monitor AMD in the clinic.

The aim of the study is to identify morphological and functional biomarkers of post-operative recovery after vitreoretinal surgery, using decisional support systems (DSS), based on multimodal big-data analysis by means of machine learning techniques in daily clinical practice

To collect, preserve, and/or distribute annotated biospecimens and associated medical data to institutionally approved, investigator-directed biomedical research to discover and develop new treatments, diagnostics, and preventative methods for specific and complex conditions.

In this pilot study we want to investigate morphological features acquired by the novel image modality and gain information regarding disease pathomechanism, development and future possible influence on disease management for patients affected by those diseases.

The purpose of this study is to discover early biomarkers in circulating endothelial cells for diabetes complications, by investigating circulating endothelial cells in blood samples from patients with newly diagnosed proliferative diabetic retinopathy, newly diagnosed maculopathy, patients with diabetes without eye diseases, and individuals without diabetes by single-cell RNA sequencing. The single-cell RNA sequencing analysis will make it possible to fully phenotype diabetes circulating endothelial cells at single-cell level and reveal the first atlas of circulating endothelial cells in humans at both healthy and diabetes conditions.