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Owhofasa Agbedia, Eman Magdy, Mohamed Ibrahim, Yasir Sepah, Raafay Sophie, Millena Bittencourt, Mostafa Hanout, Diana Do, Ahmed Fahmy, Quan Dong Nguyen; Reliability of Automated Leakage Quantification of Fluorescein Angiography in Eyes with Diabetic Macular Edema. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5514.
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© ARVO (1962-2015); The Authors (2016-present)
The traditional method for visualizing and evaluating diabetic macular edema (DME) has been fluorescein angiography (FA) where assessment is often based on subjective interpretation. The advancement of spectral domain optical coherence tomography (SD-OCT) has increased the capacity to provide detailed visualization of the retina. A novel method using FA that enables automatic segmentation and quantitative evaluation of leakage in DME has been described. In this longitudinal study, we evaluated the reliability of Automatic Leakage Quantification from Fluorescein Angiography (ALQFA) in patients with DME.
FA images (early and late time frames) and images of the central retina obtained by SD-OCT in 38 patients (38 eyes) with DME were analyzed. Images were obtained at baseline visit, months 3, 6, 9, 12, 18 and 24 of participants currently enrolled in a clinical trial for DME. We modeled the macular image in the early time frame using 2D Gaussian surfaces to correct irregular hyper-fluorescent areas. The model was subtracted from the late time frame image of the macula to enhance DME areas. Intensity values of the resulting Difference Image (DI) were mapped to predicted retinal thickness using a linear transformation that maps minimum and maximum gray levels to 250 and 600 microns respectively. We evaluated the reproducibility of the amount of leakage as assessed by the segmentation of DME in fluorescein angiograms compared to the amount of excess retinal fluid as measured by SD-OCT. Multi-level modeling was used to investigate the quantitative assessment of FA images. We also examined the reliability of ALQFA in monitoring and predicting retinal thickness in the clinical course of DME.
Using a three-level model with random intercept, the intra-class correlation (ICC) which measures the magnitude of dependency between each subfield within- and between-individual variances was 0.72. The variability in retinal thickness measurements on the same subject was 53 microns (SD 46.9-60.9) while the variability in ALQFA was 33.05 microns (SD 20.42-38.63)
Our results have shown that reliable quantitative clinical information such as active retinal vascular leakage may be obtained using ALQFA, which correlates strongly with the retinal thickness generated by the SD-OCT. ALQFA may play a role in the management of patients with DME.
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