Abstract
Purpose :
Topography-guided treatments have been recently approved by the FDA for the correction of refractive error as a custom-treatment. A parameter that may affect results is the assumed cyclorotation (cyclotorsion) of the eye that may occur between the imaging (upright sitting) position of the patient and the treatment (supine) position of the patient. The purpose of this study was to comparatively investigate the efficacy of a topography-guided treatment procedure for keratoconic eyes that incorporates cyclorotation compensation (Group-A), as compared with the previously applied procedure (Group-B), in which no cyclorotation compensation was used.
Methods :
In group-A (cyclo nA=110 eyes), cyclorotation compensation was applied, while in group-B (non-cyclo nB=110), no cyclorotation compensation was applied. Analysis was based on digital processing of Scheimpflug-imaging derived topographic curvature difference maps. Differences between targeted (surgical planning) and achieved ablation patterns were objectively measured. The vector (r, θ) corresponding to the steepest (peak topographic) corneal point on the pre-operative surgical planning map (rp, θp) and the curvature difference map (rd, θd) was computed, and the difference between the peak topographic angular data: Δθ=|θp - θd| and the weighted angular difference WΔθ=ΔθxΔr was calculated.
Results :
For group-A (cyclo) average Δθ was 7.18±7.53 (range 0 to 34°) and WΔθ was 3.43±4.76 (range 0.00 to 21.41mm). For group-B (non-cyclo), average Δθ was 14.50±12.65 (range 0 to 49°) and WΔθ was 10.23±15.15 (range 0.00 to 80.56mm). The cyclo group-A had on average a smaller angular difference as well as weighted angular difference by a statistically significant margin (Δθ p=0.0058 and WΔθ p=0.015).
Conclusions :
This study introduces an objective technique for evaluation of cyclorotation compensation in excimer laser ablation. The data indicates that incorporation of cyclorotation compensation in customized topography-guided treatment leads to improved correlation between targeted and achieved changes.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.