Kling, Sabine; Frigelli, Matteo; Aydemir, M Enes; Tahsini, Vahoora; Torres-Netto, Emilio A; Kollros, Leonard; Hafezi, Farhad (2024). Optical coherence tomography quantifies gradient refractive index and mechanical stiffness gradient across the human lens. Communications medicine, 4(162) Springer Nature 10.1038/s43856-024-00578-9
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BACKGROUND
As a key element of ocular accommodation, the inherent mechanical stiffness gradient and the gradient refractive index (GRIN) of the crystalline lens determine its deformability and optical functionality. Quantifying the GRIN profile and deformation characteristics in the lens has the potential to improve the diagnosis and follow-up of lenticular disorders and guide refractive interventions in the future.
METHODS
Here, we present a type of optical coherence elastography able to examine the mechanical characteristics of the human crystalline lens and the GRIN distribution in vivo. The concept is demonstrated in a case series of 12 persons through lens displacement and strain measurements in an age-mixed group of human subjects in response to an external (ambient pressure modulation) and an intrinsic (micro-fluctuations of accommodation) mechanical deformation stimulus.
RESULTS
Here we show an excellent agreement between the high-resolution strain map retrieved during steady-state micro-fluctuations and earlier reports on lens stiffness in the cortex and nucleus suggesting a 2.0 to 2.3 times stiffer cortex than the nucleus in young lenses and a 1.0 to 7.0 times stiffer nucleus than the cortex in the old lenses.
CONCLUSIONS
Optical coherence tomography is suitable to quantify the internal stiffness and refractive index distribution of the crystalline lens in vivo and thus might contribute to reveal its inner working mechanism. Our methodology provides new routes for ophthalmic pre-surgical examinations and basic research.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory |
UniBE Contributor: |
Kling, Sabine, Frigelli, Matteo |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
2730-664X |
Publisher: |
Springer Nature |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
13 Aug 2024 14:19 |
Last Modified: |
13 Aug 2024 14:19 |
Publisher DOI: |
10.1038/s43856-024-00578-9 |
PubMed ID: |
39134623 |
BORIS DOI: |
10.48350/199664 |
URI: |
https://boris.unibe.ch/id/eprint/199664 |