Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.790026
Title: Cellular imaging and assessment of ocular flow dynamics
Author: Agrawal, R.
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2015
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Abstract:
Diabetic retinopathy (DR), age related macular degneration (AMD) and uveitis are potentially bliding disorders associated with microvascular complication and inflammation. Alterations in the blood flow can lead to visual loss in patients with DR; however, the specific mechanism is still unclear with contradictory reports of decreased or increased blood flow. There is now established role of inflammation in AMD; however there is a lack of a good model to demonstrate cellular and vascular changes in AMD and uveitis. Currently, it is uncertain if early visual deficits in DR are caused by vascular compromise or other non-vascular factors. Using advanced non invasive vascular image analysis, retinal vascular calibers and choroidal vasculature has been objectively quantified. Along with retinal vascular caliber changes, blood components such as leukocytes, erythrocytes and platelets are thought to be involved in the control of circulatory processes by numerous mechanisms. Qualitative and quantitative assessment of leukocyte and erythrocyte dynamics in vitro and in vivo in the retinal and choroidal circulation can provide additional insight into the disease mechanism and severity in DR, AMD and uveitis. Using the Ins2Akita (Akita) mouse, a well established genetic model of DR, an AMD mouse model and in vitro cell dynamics, we have evaluated the flow dynamics of cells both in vivo and in vitro to propose a composite model of cellular dynamics in DR, AMD and uveitis. The immediate significance of this mechanistic study is the development of a microvascular model for DR, AMD and uveitis, and the identification of new insights into disease pathogenesis. The wider long-term significance is the potential to predict disease progression and develop a model to study treatment response to new therapeutic agents for vasoproliferative disorders.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.790026  DOI: Not available
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