Cerebrospinal Fluid Pressure (CSFP) and the Constraints on the Optic Nerve at the Orbit Exit (CON) Can Influence Optic Nerve Head (ONH) Biomechanics

Abstract

Purpose : To determine the role of CSFP and the CON in ONH biomechanics.

Methods : We extended our previous numerical model of the ONH (IOVS. 2005; 46: 4189-4199) to include more detailed anatomy (Fig. 1). The model was parameterized on 28 factors representing tissue geometry, material properties, pressures (CSFP, IOP and central retinal artery blood pressure [BP]) and the CON (free or fully fixed). 8,350 unique models were generated to examine factor influences in two steps: a fractional factorial design of experiments (DOE) to identify the ten most influential factors, followed by a response surface methodology (RSM) to determine factor effects precisely. Standard DOE and RSM techniques were used to determine the contributions of the factors and their interactions to the variances of 94 response measures.

Results : CSFP was the sixth most influential factor (Fig. 2a). Particularly strong were its contributions to the variations in the lamina cribrosa (LC) stretch and the peripapillary sclera (PPS) rotation. In fact, CSFP influence on PPS rotation was more than twice that of IOP. The effects of CSFP elevation were distinct from those of IOP (Fig. 2b). The CON had a large effect on the ONH response. Its influence on the LC displacement was 15 times more than that of IOP. The displacement and rotation of the PPS, as well as the rotation of the canal wall were also more sensitive to the CON than IOP. BP influence on the responses was 633 smaller than that of IOP.

Conclusions : CSFP is an important factor in ONH biomechanics, with a stronger influence than the scleral thickness and the lamina radius. CSFP and IOP affect different aspects of ONH biomechanics, suggesting that translaminar pressure difference (IOP-CSFP) may be insufficient to predict glaucomatous optic nerve damage. The CON may drastically affect the geometric responses of the ONH and should be considered when conducting ex-vivo inflation testing.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

Fig. 1 ONH model.

 

Fig. 2 (a) Strength of factor influences on a set of representative responses. Factor interactions were calculated, but are not shown. (b) Contour plots of computed distributions of maximum tissue stretch in the ONH for one example model. CSFP primarily acted on the post-laminar tissues while IOP acted on the lamina and pre-laminar tissue. IOP and CSFP did not balance out.