Document Type
Article
Publication Date
4-3-2023
Abstract
Purpose: Our team previously identified the presence of five corneal resonant frequency (RF) peaks in healthy volunteers using vibrational optical coherence tomography (VOCT). Prior studies have suggested that the ≤100 Hz RF peak represents the cellular element of tissue. The aim of this study was to confirm that this peak reflects the human corneal cellular component using VOCT and histological analysis.
Methods: Two human research globes were obtained from the same donor, and VOCT measurements were collected from the full-thickness corneas. A microkeratome was then used to create serial-free corneal caps from each cornea, with VOCT performed on the residual stromal bed after each excision. All lamellar sections from both globes were sent for histological analysis to determine cellularity. Cell counts on the specimens were performed by two independent observers.
Results: The average of the normalized ≤100 Hz peak values before lamellar sectioning was significantly higher than the average of this peak values after the first, second, and third cuts (P = 0.023), which was 33.9% less than before any cuts. The cell count values in the first slice were significantly higher than the average cell count values of the three deeper slices (P < 0.001), and the cell count dropped 84.4% after the first slice was removed.
Conclusions: The findings of this study suggest that the ≤100 Hz corneal peak identified by VOCT corresponds to the cellular component of the cornea.
Translational relevance: This work furthers our understanding of the origin of the corneal ≤100 Hz peak identified using VOCT.
Recommended Citation
Daher, Nathalie D.; Saad, Ahmed Saeed; Jimenez, Hiram J.; Milman, Tatyana; Gonzalez-Martinez, Orlando G.; Deshmukh, Tanmay S.; Pulido, Jose S.; Silver, Frederick H.; Benedetto, Dominick A.; Rapuano, Christopher J.; and Syed, Zeba A., "Identification of the Vibrational Optical Coherence Tomography Corneal Cellular Peak" (2023). Wills Eye Hospital Papers. Paper 180.
https://jdc.jefferson.edu/willsfp/180
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
PubMed ID
37043335
Language
English
Comments
This article is the author’s final published version in Translational vision science & technology, Volume 12, Issue 4, April 2023, Pages 11.
The published version is available at https://doi.org/10.1167/tvst.12.4.11. Copyright © Daher et al.