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7 March 2019 Estimating retinal vascular permeability from human fluorescein videoangiography data: optimization and sensitivity analysis of kinetic models
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Abstract
Diabetic retinopathy is a degenerative disease that can lead to irreversible blindness in patients with long-term diabetes. The mechanism of tissue damage is through inflammatory response to high blood sugar levels degrade blood vessels throughout the body, and in the retina, this can lead to microbleeds and damage to photoreceptors. It is hypothesized that a change in vascular permeability could be an early indicator of an eventual progression to retinopathy, yet no clinical methods exist to date that are capable of measuring vascular permeability accurately. We have developed mathematical models that aim to quantify blood flow and vascular permeability in the retina using clinically collectable fluorescein videoangiography data. Recently, the method was demonstrated to be effective identifying early levels of retina damage in a rat model of diabetic retinopathy. Here we present a sensitivity analysis in a simulation study and the first results from a clinical study involving 4 diabetic patients and 3 healthy controls. While there were no significant differences in measured blood flow between the groups, the “extraction fraction” (a surrogate parameter of vascular permeability) was found to be significantly higher in diabetic patients than controls (0.082 ± 0.041 vs. 0.001 ± 0.001, p < 0.001). These results highlight the potential for kinetic modeling applied to fluorescein videoangiography to identify early signs of retinopathy in diabetic patients, such that therapy can be enacted at an earlier stage of the disease when the damage is not irreversible.
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elif Kayaalp-Nalbant, Jennifer J. Kang-Mieler, and Kenneth M. Tichauer "Estimating retinal vascular permeability from human fluorescein videoangiography data: optimization and sensitivity analysis of kinetic models", Proc. SPIE 10863, Photonic Diagnosis and Treatment of Infections and Inflammatory Diseases II, 108630F (7 March 2019); https://doi.org/10.1117/12.2513215
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