Predicting intraocular lens tilt using a machine learning concept".

Aim of this study was to use a combination of partial least squares regression and a machine learning approach to predict IOL tilt using pre-operative biometry data. Patients scheduled for cataract surgery at the Kepler University Clinic Linz. Prospective single center study. Optical coherence tomography, autorefraction and subjective refraction was performed at baseline and 8 weeks after cataract surgery. In analysis I only one eye per patient was included and a tilt prediction model was generated. In analysis II a pair-wise comparison between right and left eyes was performed. In analysis I 50 eyes of 50 patients were analysed. Difference in amount, orientation and vector from pre- to post-operative lens tilt was -0.13°, 2.14° and 1.20° respectively. A high predictive power (variable importance for projection) for post-operative tilt prediction was found for pre-operative tilt (VIP=2.2), pupil decentration (VIP=1.5), lens thickness (VIP=1.1), axial eye length (VIP=0.9) and pre-operative lens decentration (VIP=0.8). These variables were applied to a machine learning algorithm resulting in an out of bag score of 0.92°. In analysis II 76 eyes of 38 patients were included. The difference of pre- to post-operative IOL tilt of right and left eyes of the same individuum was statistically relevant. Post-operative IOL tilt showed excellent predictability using pre-operative biometry data and a combination of partial least squares regression and a machine learning algorithm. Pre-operative lens tilt, pupil decentration, lens thickness, axial eye length and pre-operative lens decentration were found to be the most relevant parameters for this prediction model. Copyright © 2024 Published by Wolters Kluwer on behalf of ASCRS and ESCRS.

Citation

Klemens Waser, Andreas Honeder, Nino Hirnschall, Haidar Khalil, Leon Pomberger, Peter Laubichler, Siegfried Mariacher, Matthias Bolz. Predicting intraocular lens tilt using a machine learning concept". Journal of cataract and refractive surgery. 2024 Mar 26

PMID: 38529959

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