Bimodal Ex Vivo Biomechanical Characterization of Corneal UVA-Crosslinking via Optical Coherence Elastography and Nanoindentation under Physiological Conditions.
Riboflavin-mediated UVA corneal crosslinking (CXL) stabilizes corneal ectasia, but its biomechanical effects remain difficult to quantify. This study combines Optical Coherence Elastography (OCE), an imaging technique which provides spatially resolved deformation maps across the corneal volume, with Nanoindentation (NI), a technique that relies on direct force measurements at predefined locations on the cornea, to assess corneal biomechanics before and after CXL. Ten human donor corneas were incubated for 24 hours in a medium containing 15 % dextran to control hydration and thickness. A custom-made sample mount exerting adjustable retrocorneal fluid pressure enabled ex vivo characterization of the entire cornea while maintaining its natural shape and physiological tension. Each cornea was analyzed with both OCE and NI before and after standard Dresden protocol CXL. Linear mixed-effects models revealed significant CXL-induced stiffening across both methods, most pronounced in the central cornea and a decreasing peripherally. OCE showed a central reduction in axial strain () of 2.6 ‰ (p < 0.01), while NI revealed a consistent central increase in Hertz elastic modulus () of ∼ 14 kPa (p < 0.01) across both loading rates (300 and 600 μN / min). Although baseline stiffness increased with loading rate (128 kPa vs. 147 kPa), the CXL stiffening effect remained constant. Both techniques confirmed significant regional differences in the CXL response from central to peripheral (p < 0.05). This study provides spatially resolved, quantitative insight into corneal biomechanics using two fundamentally different mechanical testing modalities. The integration of imaging-based OCE with force-based NI establishes a robust experimental foundation for in silico numerical modeling, enabling CXL treatment optimization and predictive simulations.
Institutions
- Bioengineering Center (RU)
- Artificial Intelligence in Medicine (Canada) (CA)
Publication Details
- Journal
- Open Access CRIS of the University of Bern
- Published
- 2025-09-24
- DOI
- https://doi.org/10.48620/91691
- Primary Topic
- Protist diversity and phylogeny
- Type
- article
- Field-Weighted Citation Impact
- 0.00