Nonlinear and Asymmetric Refractive Sensitivity to Effective Lens Position Errors in Pseudophakic Eye Models.

PURPOSE: To perform a theoretical analysis of refractive sensitivity to effective lens position (ELP) errors in pseudophakic eyes using an explicit vergence-based optical model, and to quantify how this sensitivity depends on axial length (AL) and corneal power across a wide biometric range.

METHODS

A paraxial two-lens thin-lens model of the pseudophakic eye was developed, explicitly parameterised by AL, total corneal power (TCP), intraocular lens (IOL) power and effective lens position (ELP). Refraction was calculated at the corneal plane using vergence propagation. For a fixed reference ELP, the emmetropic IOL power was derived analytically for each combination of AL and TCP, and subsequently held constant while ELP was perturbed by ±1.0 mm. Simulations were performed for ALs from 19 to 31 mm and corneal powers from 38 to 50 dioptres. Refractive changes were approximated using families of quadratic regression models as functions of AL.

RESULTS

Refractive sensitivity to ELP errors was dominated by AL. Short eyes exhibited large refractive changes per millimetre of ELP error, whereas long eyes showed markedly reduced sensitivity. The relationship between refractive error and ELP displacement was nonlinear, resulting in asymmetric refractive effects for equal-magnitude anterior and posterior ELP deviations. TCP continuously modulated refractive sensitivity indirectly through its influence on the emmetropic IOL power required for a given optical configuration.

CONCLUSIONS

Refractive sensitivity to ELP errors in pseudophakic eye models is inherently nonlinear and asymmetric. This sensitivity is primarily governed by AL, with TCP acting as a secondary but systematic modulator through its effect on emmetropic IOL power. By explicitly separating optical sensitivity from ELP prediction, this vergence-based framework provides a physical basis for understanding ELP-related refractive variability across the biometric spectrum.