Local Variability of Parameters for Characterization of the Corneal Subbasal Nerve Plexus
Local Variability of Parameters for Characterization of the Corneal Subbasal Nerve Plexus
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DOI：
10.3109/02713683.2015.1010686
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发表时间：
2016-01-01
影响因子：
2
通讯作者：
Stachs, Oliver
中科院分区：
文献类型：
--
作者：
Winter, Karsten;Scheibe, Patrick;Stachs, Oliver
目的：角膜基底下神经丛(SNP)对糖尿病周围神经病变的早期诊断具有很高的潜力。共聚焦激光扫描显微镜(CLSM)可以在体内评估基底下神经纤维的变化，并使用特定的参数进行量化。虽然目前的研究结果在参数趋势上是一致的，但在绝对值方面有相当大的差异。材料和方法：在三名健康受试者中，我们使用了一种新的基于软件的大规模重建方法，提供中央角膜的SNP图像，将图像区域分解成与单个传统CLSM图像(0.16 mm(2))对应的所有可能的图像部分，并为每个图像部分计算一组参数。为了在重建的图像区域内进行大量的虚拟检查，实施了扩展的模拟程序(每个图像10,000次)。结果：3个分析图像的大小从3.75 mm(2)到4.27 mm(2)。基底下神经纤维网络的空间构型在整个角膜上差异很大，因此导致严重依赖于位置的结果以及评估的参数的宽值范围。SNP参数值在三幅图像之间的分布差异很大，并且对于计算的每个参数，在所有图像之间显示出显著差异(P<；0.001)。结论：常规评估的SNP区域相对较小是导致SNP参数变异性较高的一个因素。基于多个CLSM帧的参数值的平均不一定导致整个图像区域的相应参考值的良好近似。这说明了在选择中央角膜区域的SNP图像时，检查者存在偏见的可能性。
Purpose: The corneal subbasal nerve plexus (SNP) offers high potential for early diagnosis of diabetic peripheral neuropathy. Changes in subbasal nerve fibers can be assessed in vivo by confocal laser scanning microscopy (CLSM) and quantified using specific parameters. While current study results agree regarding parameter tendency, there are considerable differences in terms of absolute values. The present study set out to identify factors that might account for this high parameter variability.Materials and methods: In three healthy subjects, we used a novel method of software-based large-scale reconstruction that provided SNP images of the central cornea, decomposed the image areas into all possible image sections corresponding to the size of a single conventional CLSM image (0.16 mm(2)), and calculated a set of parameters for each image section. In order to carry out a large number of virtual examinations within the reconstructed image areas, an extensive simulation procedure (10,000 runs per image) was implemented.Results: The three analyzed images ranged in size from 3.75 mm(2) to 4.27 mm(2). The spatial configuration of the subbasal nerve fiber networks varied greatly across the cornea and thus caused heavily location-dependent results as well as wide value ranges for the parameters assessed. Distributions of SNP parameter values varied greatly between the three images and showed significant differences between all images for every parameter calculated (p < 0.001 in each case).Conclusions: The relatively small size of the conventionally evaluated SNP area is a contributory factor in high SNP parameter variability. Averaging of parameter values based on multiple CLSM frames does not necessarily result in good approximations of the respective reference values of the whole image area. This illustrates the potential for examiner bias when selecting SNP images in the central corneal area.