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EJ Sarver, RA Applegate, CA Sarver; Simulation of Adaptive Algorithm to Predict LASIK Postoperative Wavefront Aberrations . Invest. Ophthalmol. Vis. Sci. 2002;43(13):3948.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: To develop an adaptive algorithm for the prediction of LASIK postoperative wavefront aberrations. Methods: A simulated database of 1000 LASIK cases was generated consisting of (1) preoperative corneal topography, (2) preoperative wavefront aberrations, and (3) postoperative wavefront aberrations. The simulated corneal surface consisted of samples of a biconic with apical radii Rx and Ry (mean=7.8 mm, sd=0.2 mm) and conic coefficients Px and Py (mean=0.75, sd=0.1). The simulated preoperative wavefront aberration was generated for a spectacle correction S (mean=-4.0 D, sd=1.0 D). The ablation plan was designed to yield a spherical cornea computed according to paraxial optics. The simulated postoperative wavefront aberration was computed where the cornea had a constant postoperative oblate shape factor surprise simulated by conic coefficient P=1.1 and a constant postoperative spectacle correction of -0.5 D. A ray transfer element (RTE) software module was developed which provides both a means to generate an optical model that is consistent with exam data and a means to adapt the modeling to past surgical procedures so that prediction of postoperative outcomes is improved for future surgeries. The algorithm consisted of six steps: 1. Given preoperative corneal surface and wavefront, compute optical model for the remainder of the eye using an RTE. 2. Given preoperative corneal surface and wavefront, compute desired postoperative corneal surface. 3. Given desired postoperative corneal surface and RTE from step 1, compute predicted postoperative wavefront. 4. Given actual postoperative wavefront and the desired postoperative corneal surface, compute an RTE to represent the remainder of the eye. 5. Find the difference between the RTE calculated in step 1 and the RTE calculated in step 4. 6. Find a weighted mean of the differences computed in step 5 and use to correct the RTE used in step 3 of future cases. Results: The mean error in the predicted postoperative spectacle spherical equivalent (SEQ) for the 1000 simulated cases was 0.00003 D. The algorithm was able to predict 90.0% of the RMS higher-order wavefront aberrations (third-order and above). The mean computation time per case was 0.36 seconds on a 1.8 GHz PC. Conclusion: Our approach provides a means to predict LASIK postoperative wavefront aberrations. The results indicate the algorithm works well for simulated cases and further study with a large clinical LASIK data set is warranted. In addition, the near real-time computation times indicate that the algorithm may be suitable for clinical applications.
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