Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
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ARVO Annual Meeting Abstract  |   June 2020
Multimodal optical elastography of ex vivo porcine lens
Author Affiliations & Notes
  • Yogeshwari Sanjayrao Ambekar
    Biomedical Engineering , University of Houston, Houston, Texas, United States
  • Manmohan Singh
    Biomedical Engineering , University of Houston, Houston, Texas, United States
  • Jitao Zhang
    Fischell Department of Bioengineering, University of Maryland, College park, Maryland, United States
  • Achuth Nair
    Biomedical Engineering , University of Houston, Houston, Texas, United States
  • Salavat Aglyamov
    Biomedical Engineering , University of Houston, Houston, Texas, United States
  • Giuliano Scarcelli
    Fischell Department of Bioengineering, University of Maryland, College park, Maryland, United States
  • Kirill Larin
    Biomedical Engineering , University of Houston, Houston, Texas, United States
  • Footnotes
    Commercial Relationships   Yogeshwari Sanjayrao Ambekar, None; Manmohan Singh, None; Jitao Zhang, None; Achuth Nair, None; Salavat Aglyamov, None; Giuliano Scarcelli, None; Kirill Larin, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 4643. doi:
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      Yogeshwari Sanjayrao Ambekar, Manmohan Singh, Jitao Zhang, Achuth Nair, Salavat Aglyamov, Giuliano Scarcelli, Kirill Larin; Multimodal optical elastography of ex vivo porcine lens. Invest. Ophthalmol. Vis. Sci. 2020;61(7):4643.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Biomechanical properties of the crystalline lens can provide information for disease detection and guiding therapeutic interventions. Previous work assessing lens elasticity noninvasively has been limited to qualitative measurements. Optical coherence elastography (OCE) can provide quantitative measurements of viscoelasticity rapidly but relies on backscattered light, so imaging transparent samples is a challenge. Whereas, Brillouin microscopy can map the Brillouin frequency shift with micro-scale resolution in transparent samples. However, Brillouin microscopy imaging times are long, and translating the Brillouin frequency shift to quantitative parameters is still a challenge. In order to overcome the drawbacks of individual optical elastography modalities, we demonstrate a multimodal optical elastography technique combining OCE and Brillouin microscopy.

Methods : The combined system was first validated with tissue mimicking phantoms of varying elasticities. The Young’s modulus obtained from OCE was first validated using uniaxial mechanical testing. Then the OCE data was used to calibrate the Brillouin shift measurements to obtain the Young’s modulus of the phantoms. After validation, OCE and Brillouin measurements were performed on ex vivo porcine lens (N=6), and the derived Young’s modulus of the lenses was spatially mapped.

Results : There was strong correlation between Young’s moduli measured by OCE and longitudinal moduli measured by Brillouin microscopy. The correlation coefficients were R=0.98 for the gelatin phantoms and R = 0.89 for the lenses. The average Brillouin moduli of the nucleus, anterior, and posterior regions for all lenses were 4.33±0.13 GPa, 3.43±0.18 GPa, and 3.59±0.16 GPa respectively. Based on the correlation between Young’s modulus from OCE and longitudinal modulus, the derived average Young’s modulus for all lenses in those three regions were 12.92±2.75 kPa, 2.72±0.89 kPa and 3.80±1.25 kPa.

Conclusions : By combining OCE and Brillouin microscopy, we have shown that these techniques can map the Young’s modulus completely noninvasively in transparent tissues such as the crystalline lens.

This is a 2020 ARVO Annual Meeting abstract.

 

Figure(a)Log-log scaled correlation between the Brillouin modulus and OCE-measured Young’s modulus of the (red:6%, green:10%, blue:12%) gelatin phantoms (b)Correlation between the Brillouin modulus and OCE-measured Young’s modulus of the porcine lenses (c)Young’s modulus distribution across the lens derived from Brillouin modulus

Figure(a)Log-log scaled correlation between the Brillouin modulus and OCE-measured Young’s modulus of the (red:6%, green:10%, blue:12%) gelatin phantoms (b)Correlation between the Brillouin modulus and OCE-measured Young’s modulus of the porcine lenses (c)Young’s modulus distribution across the lens derived from Brillouin modulus

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