July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Intra-Ocular Lens Power Calculation using 3D OCT-based Personalized Computer Eye Models
Author Affiliations & Notes
  • Alberto De Castro
    Instituto de Óptica, CSIC, Madrid, Madrid, Spain
  • Eduardo Martinez-Enriquez
    Instituto de Óptica, CSIC, Madrid, Madrid, Spain
  • Miriam Velasco-Ocana
    Instituto de Óptica, CSIC, Madrid, Madrid, Spain
  • Sonia Duran
    Fundación Jiménez Díaz, Madrid, Madrid, Spain
  • Ignacio Jimenez-Alfaro
    Fundación Jiménez Díaz, Madrid, Madrid, Spain
  • Susana Marcos
    Instituto de Óptica, CSIC, Madrid, Madrid, Spain
  • Footnotes
    Commercial Relationships   Alberto De Castro, None; Eduardo Martinez-Enriquez, IO-CSIC (P); Miriam Velasco-Ocana, None; Sonia Duran, None; Ignacio Jimenez-Alfaro, None; Susana Marcos, IO-CSIC (P)
  • Footnotes
    Support  European Research Council (ERC) under European Union’s Horizon 2020 research and innovation programme H2020-MSCA-COFUND-2015-FP-713694, Spanish government grant FIS2014-56643-R, European Research Council under the European Union’s Seventh Framework programme ERC-2011-AdG-294099, Patent P201130685, Patent US2016 62/329,392​.
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 6463. doi:https://doi.org/
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      Alberto De Castro, Eduardo Martinez-Enriquez, Miriam Velasco-Ocana, Sonia Duran, Ignacio Jimenez-Alfaro, Susana Marcos; Intra-Ocular Lens Power Calculation using 3D OCT-based Personalized Computer Eye Models. Invest. Ophthalmol. Vis. Sci. 2019;60(9):6463. doi: https://doi.org/.

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

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Abstract

Purpose : To develop a new paradigm for intraocular lens (IOL) power selection based on personalized eye models from 3-D optical coherence tomography (OCT) anatomical information, virtual ray tracing and wavefront-based best-focus metrics.

Methods : Custom quantitative 3-D OCT was used to collect images of the anterior segment of the eye in 12 eyes from 7 patients (age: 79±5 years; pre-op SE: -2 to 3.25 D), pre- and post- cataract surgery. Custom image processing tools were used to estimate anterior and posterior corneal elevation, anterior chamber depth (ACD) and full 3-D shape the crystalline lens. The estimated lens position (ELP) was obtained using pre-op lens parameters (equatorial lens diameter, lens thickness and pre-op ACD, Martinez-Enriquez, Sci Rep 2018) and the IOL position was measured in the post-op images. Custom personalized computer eye models were built using MATLAB routines and an optical design program (Zemax, OpticStudio) with the OCT images and an aspheric monofocal IOL from a known catalog. The axial length was set to match the spherical equivalent measured with auto-refractometry (Topcon). We compared the impact on IOL selection of: (1) estimated ELP, (2) the use of different optical quality metrics (Point Spread Function (PSF), Modulation Transfer Function (MTF) Strehl and Visual MTF Strehl) and (3) pupil diameter.

Results : (1) The IOL power that optimizes the metric chosen changed with the ELP by 2.01, 2.06, 1.99 and 1.99 D/mm for paraxial refraction, PSF, MTF, and Visual MTF respectively. The difference between the ELP and the measured lens position was on average 65 μm which will result in a change in the IOL power selection by 0.12 D, on average. (2) The difference between the power selected optimizing the different metrics ranged from 0 to 1 D (mean 0.42±0.29 D) for 2 mm pupils and 0 to 1.5 D (mean 0.8±0.6 D) for 5 mm pupils. (3) Changing the pupil diameter in the custom model eye (2-5 mm) resulted in a change in the selected IOL power by 0.50±0.30, 0.42±0.29 and 0.38±0.31 D for PSF, MTF and VMTF metrics.

Conclusions : Personalized computer model eyes hold promise as a tool for selection of IOL power in cataract surgery as they account for the individual’s eye anatomy and are suited for retinal-image quality based metrics for refraction estimation and optical quality. These models can be used to study the influence of factors such as the pupil diameter and ELP in the IOL power selection.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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