Development and validation of a new intraocular pressure estimate for patients with soft corneas

J Cataract Refract Surg. 2019 Sep;45(9):1316-1323. doi: 10.1016/j.jcrs.2019.04.004. Epub 2019 Jul 18.


Purpose: To introduce and clinically validate a new method of estimating intraocular pressure (IOP) in patients with keratoconus and soft corneas with the aim of significantly reducing dependence on corneal biomechanics.

Setting: Vincieye Clinic, Milan, Italy, and Rio de Janeiro Corneal Tomography and Biomechanics Study Group, Brazil.

Design: Retrospective case series.

Method: This study comprised participants enrolled at two hospitals on two continents. Numerical analysis based on the finite element method was performed to simulate the effect of tonometric air pressure of the Corvis ST dynamic Scheimpflug analyzer on eye globes with wide variations in thickness, geometry, and tissue. The numerical predictions of ocular behavior were used to develop a new algorithm to produce predictions of the biomechanically corrected IOP (bIOP) in eyes with a soft cornea (bIOPs). Predictions of the bIOPs were assessed in the keratoconic clinical datasets (because on average these corneas are softer) and compared with the previously developed bIOP algorithm predictions obtained for normal healthy eyes.

Results: The study comprised 722 eyes (722 participants). The main outcome was the absence of a significant difference in IOP between healthy eyes and keratoconic eyes when the bIOP and bIOPs algorithms were used (P > .05). There was, however, a significant difference with the uncorrected Scheimpflug analyzer IOP in both groups (P < .001). Furthermore, the bIOPs predictions were significantly less affected by corneal thickness and patient age than the Scheimpflug analyzer IOP.

Conclusion: The bIOPs algorithm was more reliable at estimating the IOP in eyes with a soft cornea and was validated for use in eyes with keratoconus.

Publication types

  • Multicenter Study
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Algorithms
  • Biomechanical Phenomena
  • Cornea / physiology*
  • Corneal Pachymetry
  • Corneal Topography
  • Datasets as Topic
  • Female
  • Healthy Volunteers
  • Humans
  • Intraocular Pressure / physiology*
  • Keratoconus / physiopathology*
  • Male
  • Middle Aged
  • Reproducibility of Results
  • Retrospective Studies
  • Tonometry, Ocular / methods*
  • Young Adult