Abstract
Abstract: :
Purpose: Soft toric lenses can be complicated and unpredictable to fit. Quantitative topographic descriptors were incorporated into a new soft toric fitting nomogram which was prospectively evaluated against two traditional soft toric nomograms. The topographic nomogram utilized shape and asymmetry descriptors analyzed previously in a multivariate logistic regression model as factors which predicted empirical fitting failures of a traditional nomogram. In those eyes predicted to fail, new parameters were suggested. Methods: Videokeratography was performed with the Humphrey Atlas (v. A6) instrument on 100 eyes of 50 patients. The raw data files were downloaded to the OSU Corneal Topography Tool and analyzed for specific quantitative descriptors of shape, asymmetry, and peripheral astigmatism that were previously determined to predict fitting success or failure. Up to 3 pairs of a back surface toric, prism ballasted, soft contact lens (tetrafilcon A, Preference Toric) were ordered and evaluated in a masked fashion for each patient which varied by the nomogram used to select lens base curve and power. The nomograms tested were: N1. original Preference Toric nomogram, N2. ToriTrack nomogram utilizing corneal diameter, and N3. topographic based nomogram. Results: 90 eyes were available for analysis. Success rates of each nomogram were N1: 36.7%, N2: 35.6%, N3: 55.6%. N3 was significantly better than N1 and N2 in obtaining a clinically acceptable lens to dispense without reordering (p<0.01). There was no difference between N1 and N2. 82/90 (91%) eyes were ultimately successful after unsuccessful trial lenses were adjusted and reordered. Of the 82 eyes that could be fit into Preference Toric, empirical success rates were: N1: 40%, N2: 39%, N3: 61%. N3 selected base curve appropriately in 58/82 (71%) eyes lens compared to N1 and N2 which had success rates of 56% and 61%, respectively. N3 selected power appropriately in 52/82 (63%) eyes compared to N1 and N2 which had success rates of 55% and 49%, respectively. Conclusions: A topographic based soft toric fitting algorithm improves the empirical selection of base curve and power compared to published nomograms which utilize keratometry data and sagittal depth. To our knowledge, this is the first application of quantitative central and peripheral corneal shape descriptors to prospective soft lens fitting.
Keywords: contact lens • imaging/image analysis: clinical • topography