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学術論文

Local variability of parameters for characterization of the corneal subbasal nerve plexus

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引用

Karsten, W., Scheibe, P., Köhler, B., Allgeier, S., Guthoff, R. F., & Stachs, O. (2016). Local variability of parameters for characterization of the corneal subbasal nerve plexus. Current Eye Research, 41(2), 186-198. doi:10.3109/02713683.2015.1010686.


引用: https://hdl.handle.net/21.11116/0000-0005-6536-D
要旨
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 mm2), 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 mm2 to 4.27 mm2. 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.