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Modeling the Influence of Large Particles on Optical Properties of Nuclear Cataracts: Insights from Enhanced LOCS
Chi-Hung Lee1, Yu-Jung Chen2, Yung-Chi Chuang2
1Department of Electrical Engineering, Feng Chia University, Taichung 407, Taiwan.
Abstract:
Background: Nuclear cataracts cause visual degradation through light scattering by aggregated proteins and particles within the crystalline lens. Existing computational models mainly consider submicron scatterers, while the optical impact of micrometer-scale particles observed in human nuclear cataracts remains underexplored. Objective: This study extends a LOCS III-based computational cataract model by incorporating micrometer-scale particles and quantitatively evaluates their effects on forward and backward light scattering across nuclear cataract grades. Methods: A physics-based scattering model was implemented using optical simulation software (LightTools). Three particle populations-nanometer-scale (S-type), submicron-scale (M-type), and micrometer-scale (L-type)-were uniformly distributed within the lens. Retinal luminance reduction was analyzed for forward scattering, while slit-lamp-based backward scattering simulations were used to evaluate luminance distributions and chromaticity changes. Particle concentrations were varied within clinically reported ranges corresponding to LOCS III grades. Results: Micrometer-scale particles had minimal impact in early nuclear cataract grades but significantly increased forward scattering and luminance loss in advanced grades (NO5-NO6). Backward scattering simulations revealed pronounced luminance enhancement and yellow chromaticity shifts with increasing micrometer-scale particle concentration. One micrometer-scale particle produced a luminance-reduction effect equivalent to approximately 6-7 submicron particles, depending on cataract severity. Conclusions: Including micrometer-scale particles enables a more complete optical representation of nuclear cataracts, linking retinal image degradation with slit-lamp appearance. The model provides a physically grounded framework for offline analysis and reference data generation to support clinical interpretation of cataract grading.
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