Purpose:
To examine the effects of varying mechanical property gradients on the optomechanical behavior of the lens using finite element analysis, thereby giving insight into how such gradients may be manipulated in lens refill materials to maximize accommodative amplitude.
Methods:
The Burd et al. (Vision Res. 42:2235-2251, 2002) geometric model of the 29-year-old human lens was selected for the geometry. Body forces were used to model zonular tension using the method of Hermans et al. (Vision Res. 46:3642-3650, 2006). The finite element space was constructed in StressCheck v8.0 (ESRD, Inc., St. Louis, MO). Concentric circles emanating from the center of the nucleus were constructed. Each annular zone was then assigned an elastic modulus. The outermost zone was assigned an elastic modulus at various ratios relative to the lens capsule (i.e. E0/Ecap varied from 0.005 to 0.1). The modulus of the remaining zones was assigned using the formula Ei=kEi-1, where k is a constant describing the stiffness gradient (e.g. if k<1, the lens is softer in the center than on the periphery).
Results:
Accommodative amplitude generally decreased as k increased (Fig. 1). Very soft lenses (E0/Ecap<<0.01) behaved in a non-Helmholtzian manner, indicating that some minimum stiffness is required to restore accommodation. All lenses with near-physiological stiffness exhibited Helmholtzian accommodation at low k values, no accommodative amplitude when the modulus was uniform everywhere in the lens (k=1), and more complex behavior when the center of the lens was stiffer than the peripheral regions, culminating in an asymptote of no accommodation at high k values.
Conclusions:
The magnitude and direction of the lens’ elasticity gradient is an essential feature of an accommodating lens. The ability to synthesize such elasticity profiles in vivo may be an essential feature of a successful lens refill material.Figure 1: Relationship between lens mechanical property gradient characteristics and accommodative amplitude.
Keywords: accommodation • presbyopia • computational modeling