Fully Automated Prediction of Geographic Atrophy Growth Using Quantitative Spectral-Domain Optical Coherence Tomography Biomarkers
Fully Automated Prediction of Geographic Atrophy Growth Using Quantitative Spectral-Domain Optical Coherence Tomography Biomarkers
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DOI：
10.1016/j.ophtha.2016.04.042
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发表时间：
2016-08-01
期刊：
影响因子：
13.7
通讯作者：
Leng, Theodore
中科院分区：
文献类型：
--
作者：
Niu, Sijie;de Sisternes, Luis;Leng, Theodore
目的：建立一个基于地理萎缩(GA)定量特征的预测模型，以预测GA未来的潜在生长区域。设计：进展研究和预测模型。参与者：118例38只眼的光谱域(SD)光学相干断层扫描(OCT)。方法：GA的成像特征量化其范围和位置，以及每个地形图位置的特征与单个视网膜层厚度和反射率、病理特征(如网状假性萎缩或光感受器丢失)的存在，以及其他已知的GA生长危险因素，是从29名患者的118次SD OCT扫描中自动提取的，平均随访时间为2.25年。主要观察指标：GA生长的潜在区域。结果：按出袋特征重要性从大到小的顺序，预测GA生长未来区域的SD OCT生物标志物是11-14带的厚度损失(5.66)，11-12带的反射率(5.37)，网状假性黄斑厚度(5.01)，5-11带的厚度(4.82)，7-11带的反射率(4.78)，GA投影图(4.73)、最小视网膜强度图增加(4.59)、GA偏心度(4.49)。在3个测试场景中预测的GA区域与观察到的地面真实情况相比，Dice指数的平均+/-标准差分别为0.81+/-0.12、0.84+/-0.10和0.87+/-0.06。仅考虑基线时没有GA证据的区域，预测的GA增长区域显示出相对较高的Dice指数，分别为0.72+/-0.18、0.74+/-0.17和0.72+/-0.22。中心凹GA生长速度和GA未来受累程度的预测值和实际值具有很高的相关性。结论：实验结果表明，我们的预测模型有潜力预测未来GA可能生长的区域，并识别最具区分性的早期指标(条带11到14的厚度损失)。(C)2016年由美国眼科学会颁发。
Purpose: To develop a predictive model based on quantitative characteristics of geographic atrophy (GA) to estimate future potential regions of GA growth.Design: Progression study and predictive model.Participants: One hundred eighteen spectral-domain (SD) optical coherence tomography (OCT) scans of 38 eyes in 29 patients.Methods: Imaging features of GA quantifying its extent and location, as well as characteristics at each topographic location related to individual retinal layer thickness and reflectivity, the presence of pathologic features (like reticular pseudodrusen or loss of photoreceptors), and other known risk factors of GA growth, were extracted automatically from 118 SD OCT scans of 38 eyes from 29 patients collected over a median follow-up of 2.25 years. We developed and evaluated a model to predict the magnitude and location of GA growth at given future times using the quantitative features as predictors in 3 possible scenarios.Main Outcome Measures: Potential regions of GA growth.Results: In descending order of out-of-bag feature importance, the most predictive SD OCT biomarkers for predicting the future regions of GA growth were thickness loss of bands 11 through 14 (5.66), reflectivity of bands 11 and 12 (5.37), thickness of reticular pseudodrusen (5.01), thickness of bands 5 through 11 (4.82), reflectivity of bands 7 through 11 (4.78), GA projection image (4.73), increased minimum retinal intensity map (4.59), and GA eccentricity (4.49). The predicted GA regions in the 3 tested scenarios resulted in a Dice index mean +/- standard deviation of 0.81 +/- 0.12, 0.84 +/- 0.10, and 0.87 +/- 0.06, respectively, when compared with the observed ground truth. Considering only the regions without evidence of GA at baseline, predicted regions of future GA growth showed relatively high Dice indices of 0.72 +/- 0.18, 0.74 +/- 0.17, and 0.72 +/- 0.22, respectively. Predictions and actual values of GA growth rate and future GA involvement in the central fovea showed high correlations.Conclusions: Experimental results demonstrated the potential of our predictive model to predict future regions where GA is likely to grow and to identify the most discriminant early indicator (thickness loss of bands 11 through 14) of regions susceptible to GA growth. (C) 2016 by the American Academy of Ophthalmology.