Optimization of surgical parameters based on patient‐specific models: Application to arcuate keratotomy. Issue 8 (August 2019)

• Record Type: Journal Article
• Authors: Truffer, Oskar; Abler, Daniel; Pajic, Bojan; Grabner, Günther; Kraker, Hannes; Büchler, Philippe
• Is Part Of: Journal of cataract and refractive surgery. Volume 45:Issue 8(2019)
• Publication Date: 2019-08
• Subjects: 617.7
• DOI: 10.1016/j.jcrs.2019.02.022
• Languages: English
• ISSNs: 0886-3350

Abstract

Abstract : Purpose : To determine surgical parameters for arcuate keratotomy by simulating the intervention with a patient‐specific model. Setting : University Eye Clinic Salzburg, Paracelsus Medical University, Austria, and Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland. Design : Computational modeling study. Methods : A new approach to plan arcuate keratotomy based on personalized finite element simulations was developed. Using this numeric tool, an optimization algorithm was implemented to determine the incision parameters that best met the surgeon's requirements while preserving the orientation of the astigmatism. Virtual surgeries were performed on patients to compare the performance of the simulation‐based approach with results based on the Lindstrom and Donnenfeld nomograms and with intrastromal interventions. Results : Retrospective data on 28 patients showed that personalized simulation reproduced the surgically induced change in astigmatism (Pearson correlation = 0.8). Patient‐specific simulation was used to examine strategies for arcuate interventions on 621 corneal topographies. The Lindstrom nomogram resulted in low postoperative astigmatism (mean 0.03 diopter [D] ± 0.3 [SD]) but frequent overcorrections (20%). The Donnenfeld nomogram and intrastromal incisions resulted in a small amount of overcorrection (1.5%) but a wider spread in astigmatism (mean 0.63 ± 0.35 D and 0.48 ± 0.50 D, respectively). In contrast, the new numeric parameter optimization approach led to postoperative astigmatism values (mean 0.40 ± 0.08 D, 0.20 ± 0.08 D, and 0.04 ± 0.13 D) that closely matched the target astigmatism (0.40 D, 0.20 D, and 0.00 D), respectively, while keeping the number of overcorrections low (<1.5%). Conclusion : Using numeric modeling to optimize surgical parameters for arcuate keratotomy led to more reliable postoperative astigmatism, limiting the risk for overcorrection.