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Spatial Arrangement of Leakage Patterns in Diabetic Macular Edema is Associated with Tolerance of Aibercept Treatment Interval Length: Preliminary Findings

机译:糖尿病黄斑水肿中泄漏模式的空间排列与耐受性有关ibercept治疗间隔长度:初步调查结果

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Diabetic macular edema (DME) is a leading cause of vision loss in diabetic patients. The underlying cause forthe onset of DME is the degradation of the blood-retinal barrier, whose primary function is maintaining theextracellular uid at an optimal range. Vascular endothelial growth factor (VEGF) has proven to be a catalystin altering the permeability of the blood-retinal barrier, thereby initiating a cascade of events that ultimatelyresults in a loss of visual acuity. The primary imaging techniques to recognize and diagnose DME are uoresceinangiography (FA) and spectral-domain optical coherence tomography (SD-OCT). Taking a multimodal approachof FA in combination with SD-OCT provides images of vasculature and other eye structures to help better identifykey features such as level, location, and amount of leakage. First-line treatments for DME have now evolved tousing anti-VEGF to inhibit the effects VEGF has on increasing the permeability of the blood-retinal barrier.Because VEGF also increases the chance of leakage, we can also expect anti-VEGF treatments to decrease theamount of leakage DME patients suffer from. Anti-VEGF treatments also have a peripheral effect of modifyingthe disease burden and allowing for extended time in between treatments. Although current conventionaltreatment parameters exist to determine the e cacy of such VEGF treatments, many of these markers rely onclinicians to make a judgment call based on a minor qualitative difference of retinal scans or involve clinicianstaking a uid assessment, an option deemed too invasive to demand from all patients. In this work, we seek to nd new imaging features that derive from a sub-visual feature analysis, and ideally provide a prognostic metricfor clinicians to help streamline the diagnostic process. The rationale for these new biomarkers derives fromleakage properties and their activity in the retina once edema develops. A decrease in leakage within certainstructures in the eye would also lead to a change in the densities of leakage patterns, correlating with betterclinical outcomes.In this work, we use morphological and graph-based attributes to model the global properties and spatialdistribution of leakage areas on baseline FA scans of patients subsequently treated with intravitreal anti-VEGFtherapy (i.e. aibercept). The features were then used in conjunction with a classifier to distinguish betweeneyes tolerating extended dosing intervals (N=15) and those eyes requiring more frequent dosing (N=12), basedon initial response following treatment interval extension. The cross-validated area under the receiver operatingcharacteristic curve (AUC) was found to be 0.74 0.11% using the computed imaging attributes. Edge lengthdisorder 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 significantlydifferent. Our results indicate that there may be differences in spatial distribution of leakage areas between eyesthat will exhibit favorable response to extended interval aibercept dosing and eyes that require more frequentdosing.
机译:糖尿病黄斑水肿(DME)是糖尿病患者视力丧失的主要原因。潜在的原因DME的发作是血质视网膜屏障的降解,其主要函数保持在细胞外UID在最佳范围内。血管内皮生长因子(VEGF)已被证明是一种催化剂改变血质视网膜屏障的渗透率,从而启动最终的级联事件导致视力丧失。识别和诊断DME的主要成像技术是Uoratecein.血管造影(FA)和光谱 - 域光学相干断层扫描(SD-OCT)。采取多式化方法FA与SD-OCT结合提供脉管系统和其他眼部结构的图像,以帮助更好地识别级别,位置和泄漏量等主要功能。 DME的一线治疗现已发展到使用抗VEGF来抑制VEGF对VEGF的增加,提高了血质视网膜屏障的渗透性。因为VEGF也增加了泄漏的可能性,我们也可以预计抗VEGF治疗减少泄漏DME患者的患者患有。抗VEGF治疗也具有改变的外周效果治疗之间的疾病负担和允许延长时间。虽然目前是常规的存在治疗参数以确定这种VEGF治疗的e cacy,其中许多标记依赖于此临床医生根据视网膜扫描的次要定性差异或涉及临床医生进行审判服用A.UID评估,一种选择过于侵入所有患者的选择。在这项工作中,我们寻求 ND从子视觉特征分析中获得的新成像功能,理想情况下提供预后度量对于临床医生,帮助简化诊断过程。这些新生物标志物的理由来自一旦水肿发展,视网膜的泄漏性质及其活性。在某些情况下降低泄漏眼睛中的结构也会导致泄漏模式的密度的变化,与更好的相关性临床结果。在这项工作中,我们使用基于形态和基于图形的属性来模拟全局属性和空间基线FA扫描泄漏区域的分布随后用玻璃体内抗VEGF治疗治疗(即aibercept)。然后将该特征与分类器结合使用以区分耐受延长给药间隔的眼睛(n = 15)和需要更频繁给药(n = 12)的那些眼睛处理间隔延伸后的初始响应。接收器下的交叉验证区域使用计算的成像属性,发现特征曲线(AUC)为0.74 0.11%。边缘长度最小生成树的紊乱显示两组之间的统计学上显着差异(p = 0.007)。临床参数如中央子场厚度和黄斑卷没有统计学显着不同的。我们的结果表明,眼睛之间可能存在泄漏区域的空间分布差异这将表现出对延长间隔a的有利反应ibercept剂量和眼睛需要更频繁给药。

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