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Diabetic macular edema (DME) is a leading cause of vision loss in diabetic patients. The underlying cause for the onset of DME is the degradation of the blood-retinal barrier, whose primary function is maintaining the extracellular fluid at an optimal range. Vascular endothelial growth factor (VEGF) has proven to be a catalyst in altering the permeability of the blood-retinal barrier, thereby initiating a cascade of events that ultimately results in a loss of visual acuity.1 The primary imaging techniques to recognize and diagnose DME are fluorescein angiography (FA) and spectral-domain optical coherence tomography (SD-OCT). Taking a multimodal approach of FA in combination with SD-OCT provides images of vasculature and other eye structures to help better identify key features such as level, location, and amount of leakage.2 First-line treatments for DME have now evolved to using anti-VEGF to inhibit the effects VEGF has on increasing the permeability of the blood-retinal barrier.3 Because VEGF also increases the chance of leakage, we can also expect anti-VEGF treatments to decrease the amount of leakage DME patients suffer from. Anti-VEGF treatments also have a peripheral effect of modifying the disease burden and allowing for extended time in between treatments.4 Although current conventional treatment parameters exist to determine the efficacy of such VEGF treatments, many of these markers rely on clinicians to make a judgment call based on a minor qualitative difference of retinal scans or involve clinicians taking a fluid assessment, an option deemed too invasive to demand from all patients. In this work, we seek to find new imaging features that derive from a sub-visual feature analysis, and ideally provide a prognostic metric for clinicians to help streamline the diagnostic process. The rationale for these new biomarkers derives from leakage properties and their activity in the retina once edema develops. A decrease in leakage within certain structures in the eye would also lead to a change in the densities of leakage patterns, correlating with better clinical outcomes. In this work, we use morphological and graph-based attributes to model the global properties and spatial distribution of leakage areas on baseline FA scans of patients subsequently treated with intravitreal anti-VEGF therapy (i.e. aibercept). The features were then used in conjunction with a classifier to distinguish between eyes tolerating extended dosing intervals (N=15) and those eyes requiring more frequent dosing (N=12), based on initial response following treatment interval extension. The cross-validated area under the receiver operating characteristic curve (AUC) was found to be 0.74±0.11% using the computed imaging attributes. Edge length disorder of minimum spanning tree showed a statistically significant difference (p=0.007) between the two groups. Clinical parameters such as central subfield thickness and macular volume were not statistically significantly different. Our results indicate that there may be differences in spatial distribution of leakage areas between eyes that will exhibit favorable response to extended interval aibercept dosing and eyes that require more frequent dosing.
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