Application of an OCT data-based mathematical model of the foveal pit in Parkinson disease
Application of an OCT data-based mathematical model of the foveal pit in Parkinson disease
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DOI：
10.1007/s00702-014-1214-2
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发表时间：
2014-11-01
影响因子：
3.3
通讯作者：
Bodis-Wollner, Ivan
中科院分区：
文献类型：
--
作者：
Ding, Yin;Spund, Brian;Bodis-Wollner, Ivan
光谱域光学相干断层扫描(OCT)在视网膜疾病的研究中显示出显著的应用价值，并有助于描述帕金森病(PD)患者的中心凹。我们基于原始的OCT数据开发了一个详细的数学模型，以区分PD患者的中心凹和健康对照组。在我们测试的各种模型中，高斯和多项式的差异被发现具有“最好的拟合度”。根据模型对45只对照眼和50只PD眼的数据的适合性的数学评估做出决定。我们使用受试者操作特征(ROC)来比较两组的模型参数。单个参数可以区分70%的帕金森病患者的眼睛和对照组，而使用模型的八个参数中的七个参数可以区分76%的帕金森病患者。讨论了数学模型在弥漫性神经退行性疾病研究中的未来临床应用，这些疾病也影响中心凹。
Spectral-domain Optical coherence tomography (OCT) has shown remarkable utility in the study of retinal disease and has helped to characterize the fovea in Parkinson disease (PD) patients. We developed a detailed mathematical model based on raw OCT data to allow differentiation of foveae of PD patients from healthy controls. Of the various models we tested, a difference of a Gaussian and a polynomial was found to have "the best fit". Decision was based on mathematical evaluation of the fit of the model to the data of 45 control eyes versus 50 PD eyes. We compared the model parameters in the two groups using receiver-operating characteristics (ROC). A single parameter discriminated 70 % of PD eyes from controls, while using seven of the eight parameters of the model allowed 76 % to be discriminated. The future clinical utility of mathematical modeling in study of diffuse neurodegenerative conditions that also affect the fovea is discussed.