Abstract
Purpose: :
Measuring corneal biomechanical properties may help detect keratoconus suspect corneas and eliminate the risk for ectasia after LASIK.
Methods: :
We retrospectively reviewed data of 504 eyes separated into three groups: normal (n=252), keratoconus suspect (n=80) and keratoconus (n=172). The Corneal Hysteresis (CH) and Corneal Resistance Factor (CRF) were measured by the Ocular Response Analyzer (ORA). Segregation of the three groups was based on the results of the Nidek OPD scan videokeratograph (Nidek CO., LTD, Gamagori, Japan). The Nidek Corneal Navigator (NCN) uses an artificial intelligence technique to train a computer neural network to recognize specific classifications of corneal topography. Waveform numerical scores (WS) derived from 37 parameters of the ORA corneal deformation signals were assigned by a neural network to analyze the signal curves characteristics.
Results: :
The mean corneal hysteresis was 10.6 +/- 1.4 (SD) mmHg in the normal group compared to 10.0 +/- 1.6 mmHg in the keratoconus suspect group and 8.1 +/- 1.4 mmHg in the keratoconus group. The mean CRF was 10.6 +/- 1.6 mmHg in the normal group compared to 9.7 +/- 1.7 in the keratoconus suspect group and 7.1 +/- 1.6 mmHg in the keratoconus group. The mean CH and CRF were significantly different between the 3 groups (p< 0.001). Analysis of signal curves characteristics obtained with the ORA device differentiates between keratoconus suspect corneas and normal corneas with a sensitivity of 80%.
Conclusions: :
CH and CRF were significantly lower in the keratoconus suspect group but their clinical relevance was small. The analysis of signal curves characteristics may help to increase the sensitivity of keratoconus suspect detection.
Keywords: cornea: clinical science • cornea: stroma and keratocytes • refractive surgery