Horn Folkert K, Brenning Alexander, Jünemann Anselm G, Lausen Berthold
Department of Ophthalmology and University Eye Hospital, D-91054 Erlangen, Germany.
J Glaucoma. 2007 Jun-Jul;16(4):363-71. doi: 10.1097/IJG.0b013e318032e4c2.
The aim of this analysis was to evaluate the diagnostic usefulness of frequency doubling technology (FDT) perimetry and short-wavelength perimetry (SWAP). Moreover, to study a combination of both methods using the machine-learning technique double-bagging, which was recently established in glaucoma research.
Forty-three patients with "preperimetric" open-angle glaucoma (glaucomatous optic disc atrophy and no visual field defect in standard perimetry), 26 patients with "perimetric" open angle glaucoma (glaucomatous optic disc atrophy and visual field defect in standard perimetry), and 40 control subjects had FDT screening (protocol: C-20-5) and SWAP (Octopus 101, G2). Criteria for exclusion were color vision abnormalities, media opacities, and an age below 31 years or above 63 years. Data of 1 eye of each patient and control subject entered the statistical evaluation. A point wise evaluation of the diagnostic power of SWAP values was performed to derive spatial patterns of visual field loss. A double-bagging machine-learning algorithm was used to train classification rules on the basis of a combination of FDT scores and nerve fiber related visual field losses in SWAP. The diagnostic power of the classifiers was compared regarding their misclassification error rates and area under the receiver-operating characteristic curve.
The combination of FDT perimetry and SWAP yielded better diagnostic results compared with FDT or SWAP separately. The overall estimated misclassification error rate of the combined classifier was 24% compared with 28% for both SWAP and FDT perimetry. Regarding the estimated performance of classifier at high specificities (>80%) in control eyes as measured by the partial area under the receiver-operating characteristic curve, the combination of both instruments is also superior to the individual instruments.
A combination of SWAP and FDT perimetry, each targeting different neuronal pathways, may improve early glaucoma detection.
本分析旨在评估倍频技术（FDT）视野检查和短波长视野检查（SWAP）的诊断效用。此外，研究使用机器学习技术双重装袋法将这两种方法结合起来，该方法最近已应用于青光眼研究。
43例“视野检查前”开角型青光眼患者（青光眼性视盘萎缩且标准视野检查无视野缺损）、26例“视野检查确诊”开角型青光眼患者（青光眼性视盘萎缩且标准视野检查有视野缺损）以及40例对照受试者接受了FDT筛查（方案：C - 20 - 5）和SWAP（Octopus 101，G2）检查。排除标准为色觉异常、介质混浊以及年龄低于31岁或高于63岁。每位患者和对照受试者的一只眼睛的数据进入统计评估。对SWAP值的诊断能力进行逐点评估，以得出视野缺损的空间模式。使用双重装袋机器学习算法，根据FDT分数和SWAP中与神经纤维相关的视野缺损组合来训练分类规则。比较分类器的诊断能力，依据其误分类错误率和受试者操作特征曲线下面积。
与单独使用FDT或SWAP相比，FDT视野检查和SWAP相结合产生了更好的诊断结果。联合分类器的总体估计误分类错误率为24%，而SWAP和FDT视野检查均为28%。根据受试者操作特征曲线下部分面积测量，在对照眼中，当分类器具有高特异性（>80%）时，两种检查方法结合也优于单独使用的检查方法。
SWAP和FDT视野检查相结合，每种方法针对不同的神经元通路，可能会改善青光眼的早期检测。
