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Corneal Segmentation Analysis Increases Glaucoma Diagnostic Ability of Optic Nerve Head Examination, Heidelberg Retina Tomograph's Moorfield's Regression Analysis, and Glaucoma Probability Score

机译:角膜分割分析提高了视神经乳头检查的青光眼诊断能力,海德堡视网膜断层扫描仪的Moorfield回归分析和青光眼概率评分

摘要

Purpose. To study whether a corneal thickness segmentation model, consisting in a central circular zone of 1 mm radius centered at the corneal apex (zone I) and five concentric rings of 1 mm width (moving outwards: zones II to VI), could boost the diagnostic accuracy of Heidelberg Retina Tomograph's (HRT's) MRA and GPS. Material and Methods. Cross-sectional study. 121 healthy volunteers and 125 patients with primary open-angle glaucoma. Six binary multivariate logistic regression models were constructed (MOD-A1, MOD-A2, MOD-B1, MOD-B2, MOD-C1, and MOD-C2). The dependent variable was the presence of glaucoma. In MOD-A1, the predictor was the result (presence of glaucoma) of the analysis of the stereophotography of the optic nerve head (ONH). In MOD-B1 and MOD-C1, the predictor was the result of the MRA and GPS, respectively. In MOD-B2 and MOD-C2, the predictors were the same along with corneal variables: central, overall, and zones I to VI thicknesses. This scheme was reproduced for model MOD-A2 (stereophotography along with corneal variables). Models were compared using the area under the receiver operator characteristic curve (AUC). Results. MOD-A1-AUC: 0.771; MOD-A2-AUC: 0.88; MOD-B1-AUC: 0.736; MOD-B2-AUC: 0.845; MOD-C1-AUC: 0.712; MOD-C2-AUC: 0.838. Conclusion. Corneal thickness variables enhance ONH assessment and HRT's MRA and GPS diagnostic capacity.
机译:目的。要研究由以半径1 amm为中心的圆形区域(以I区为中心)和五个宽度为1 widthmm的同心环(向外移动:II至VI区)组成的角膜厚度分割模型是否可以增强诊断海德堡视网膜断层扫描(HRT)的MRA和GPS的准确性。材料与方法。横断面研究。 121名健康志愿者和125例原发性开角型青光眼患者。构建了六个二元多元logistic回归模型(MOD-A1,MOD-A2,MOD-B1,MOD-B2,MOD-C1和MOD-C2)。因变量是青光眼的存在。在MOD-A1中,预测指标是视神经乳头(ONH)立体摄影分析的结果(存在青光眼)。在MOD-B1和MOD-C1中,预测变量分别是MRA和GPS的结果。在MOD-B2和MOD-C2中,预测变量与角膜变量相同:中心厚度,整体厚度以及I至VI区域的厚度。对于MOD-A2模型(立体摄影以及角膜变量)复制了该方案。使用接收器操作员特征曲线(AUC)下的面积比较模型。结果。 MOD-A1-AUC:0.771; MOD-A2-AUC:0.88; MOD-B1-AUC:0.736; MOD-B2-AUC:0.845; MOD-C1-AUC:0.712; MOD-C2-AUC:0.838。结论。角膜厚度变量可增强ONH评估以及HRT的MRA和GPS诊断能力。

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