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Author Spotlight: Advancements in Refractive Surgical Correction for Presbyopia and Exploring Postoperative Visual Acuity
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Author Spotlight: Advancements in Refractive Surgical Correction for Presbyopia and Exploring Postoperative Visual Acuity

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New simulation software to predict postoperative corneal stiffness before laser vision correction.

Mathew Francis1, Rohit Shetty, Prema Padmanabhan

  • 1From the Imaging, Biomechanics and Mathematical Modelling Solutions, Narayana Nethralaya Foundation, Bangalore, India (Francis, Sinha Roy); Department of Corneal and Refractive surgery, Narayana Nethralaya, Bangalore, India (Shetty, Matalia, Khamar, Chinnappaiah); Medical Research Foundation, Sankara Nethralaya, Chennai, Tamil Nadu, India (Padmanabhan, Mukundan); Humanitas San Pio X Hospital, Milan, Italy (R. Vinciguerra); The School of Engineering, University of Liverpool, Liverpool, United Kingdom (R. Vinciguerra); Humanitas Clinical and Research Center-IRCCS, Milan, Italy (P. Vinciguerra, Lippera); Department of Biomedical Sciences, Humanitas University, Milan, Italy (P. Vinciguerra, Lippera); Department of Ophthalmology, Maastricht University Medical Centre, Maastricht, the Netherlands (Nuijts).

Journal of Cataract and Refractive Surgery
|February 15, 2023
PubMed
Summary

A new virtual surgery simulation platform accurately predicts corneal stiffness after laser vision correction. This AI-powered tool aids in assessing ectasia risk, enhancing patient safety in refractive surgery.

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Area of Science:

  • Ophthalmology
  • Biomechanical Engineering
  • Artificial Intelligence

Background:

  • Corneal stiffness is a critical factor in refractive surgery outcomes.
  • Accurate prediction of postoperative corneal stiffness is essential for patient safety and preventing complications like ectasia.
  • Current methods for assessing corneal biomechanics have limitations.

Purpose of the Study:

  • To develop and validate a novel virtual surgery simulation platform for predicting postoperative corneal stiffness (Kc mean) after laser vision correction (LVC).
  • To assess the platform's ability to differentiate between normal and ectatic corneas.
  • To integrate artificial intelligence (AI) for enhanced accuracy in stiffness prediction.

Main Methods:

  • A retrospective observational case series included 529 eyes, with 10 post-small-incision lenticule extraction (SMILE) ectasia eyes.
  • The AcuSimX software utilized finite element analysis with preoperative Corvis-ST and Pentacam data to derive corneal biomechanical properties.
  • An AI model (Orange AI) adjusted software-computed stiffness for measurement uncertainties, and a decision tree was developed for ectasia classification.

Main Results:

  • The virtual surgery simulation platform demonstrated high accuracy in predicting corneal stiffness, with mean absolute errors of 6.24 N/m and 6.47 N/m in training and test cohorts, respectively.
  • Intraclass correlation coefficients were 0.84 in both cohorts, indicating excellent reliability.
  • The AI-adjusted software-computed stiffness closely matched in vivo measurements in ectasia eyes (P = .96), and the decision tree achieved an area under the receiver operating characteristic curve of 1.0 for ectasia classification.

Conclusions:

  • The developed virtual surgery simulation platform offers an easy-to-use tool for clinicians to predict postoperative corneal stiffness after LVC.
  • The platform shows promise in identifying ectasia risk in eyes that have undergone SMILE.
  • Further validation in diverse post-surgical ectasia cases is warranted.