Abstract
Purpose: To image, track and map the nerve fiber distribution in excised rabbit corneas over the entire stromal thickness using micro-optical coherence tomography (mu OCT) to develop a screening tool for early peripheral neuropathy. Methods: Excised rabbit corneas were consecutively imaged by a custom-designed mu OCT prototype and a commercial laser scanning fluorescence confocal microscope. The mu OCT images with a field of view of approximately 1 x 1 mm were recorded with axial and transverse resolutions of approximately 1 mu nn and approximately 4 mu nn, respectively. In the volumetric mu OCT image data, network maps of hyper-reflective, branched structures traversing different stromal compartments were segmented using semiautomatic image processing algorithms. Furthermore, the same corneas received beta III-tubulin antibody immunostaining before digital confocal microscopy, and a comparison between mu OCT image data and immunohistochemistry analysis was performed to validate the nerval origin of the tracked network structures. Results: Semiautomatic tracing of the nerves with a high range of different thicknesses was possible through the whole corneal volumes, creating a skeleton of the traced nerves. There was a good conformity between the hyper-reflective structures in the mu OCT data and the stained nerval structures in the immunohistochemistry data. Conclusions: This article demonstrates nerval imaging and tracking as well as a spatial correlation between mu OCT and a fluorescence corneal nerve standard for larger nerves throughout the full thickness of the cornea ex vivo. Translational Relevance: Owing to its advantageous properties, mu OCT may become useful as a noncontact method for assessing nerval structures in humans to screen for early peripheral neuropathy.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 2164-2591 |
Sprache: | Englisch |
Dokumenten ID: | 86943 |
Datum der Veröffentlichung auf Open Access LMU: | 25. Jan. 2022, 09:21 |
Letzte Änderungen: | 25. Jan. 2022, 09:21 |