Abstract
Purpose :
To assess corneal biomechanical behavior using a modified technique for optical coherence elastography (OCE) in its first in vivo application.
Methods :
A previously described corneal elastography technique (Ford et al., JBO 2011) based on optical coherence tomography was modified and applied for the first time in an IRB-approved human subjects study. Corneal deformations are delivered using a flat lens attached to a linear actuator and rapid-sampling force transducers over a two-second perturbation. A cross-correlation algorithm is applied to track frame-by-frame intrastromal speckle displacement. Regional displacements for the anterior and posterior stroma were determined using custom software, and data were plotted in a force vs. displacement graph. Total displacement was defined as the vector sum of horizontal and vertical displacements, for both the anterior and posterior corneas. A displacement/force relationship was established by dividing the maximum total displacement by the maximum force for the anterior (Ka) and posterior cornea (Kp).
Results :
Six eyes from three subjects were measured in this pilot study. The correlation analysis showed a mean value of 0.66 ± 0.04 across the regions of interest, which satisfies previously published criteria for accurate feature tracking. A graph of force vs. displacement for one case (Figure 1) demonstrates that, for the same amount of applied force, anterior stromal displacements were lower (indicating stiffer behavior) than posterior stromal displacements. This behavior was confirmed across all eyes (mean Ka = 0.78 N/mm ± 0.33 N/mm and mean Kp = 0.70 N/mm ± 0.29 N/mm, thus giving Ka/Kp = 1.114 ± 0.047).
Conclusions :
OCE is a clinically feasible, non-invasive method to assess corneal biomechanical behavior. Furthermore, the technique proved useful to differentiate distinct behaviors between the anterior and the posterior cornea. Efforts are underway to apply inverse computational modeling to the displacement data to extract elasticity estimates.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.