Complementary Keratoconus Indices Based on Topographical Interpretation of Biomechanical Waveform Parameters: A Supplement to Established Keratoconus Indices

Abstract

Purpose. To build new models with the Ocular Response Analyzer (ORA) waveform parameters to create new indices analogous to established topographic keratoconus indices. Method. Biomechanical, tomographic, and topographic measurements of 505 eyes from the Homburger Keratoconus Centre were included. Thirty-seven waveform parameters (WF) were derived from the biomechanical measurement with the ORA. Area under curve (ROC, receiver operating characteristic) was used to quantify the screening performance. A logistic regression analysis was used to create two new keratoconus prediction models based on these waveform parameters to resample the clinically established keratoconus indices from Pentacam and TMS-5. Results. ROC curves show the best results for the waveform parameters p1area, p2area, h1, h2, dive1, mslew1, aspect1, aplhf, and dslope1. The new keratoconus prediction model to resample the Pentacam topographic keratoconus index (TKC) was WF_TKC = -4.068 + 0.002 × p2area - 0.005 × dive1 - 0.01 × h1 - 2.501 × aplhf, which achieves a sensitivity of 90.3% and specificity of 89.4%; to resample the TMS-5 keratoconus classification index (KCI) it was WF_KCI = -3.606 + 0.002 × p2area, which achieves a sensitivity of 75.4% and a specificity of 81.8%. Conclusion. In addition to the biomechanically provided Keratoconus Index two new indices which were based on the topographic gold standards (either Pentacam or TMS-5) were created. Of course, these do not replace the original topographic measurement.

Figure 1

Explanation of the parameters which were used for the model for WF_TKC and WF_KCI: dive1 as maximum single decrease in the fall of peak 1 or longest continuous line without a break, height 1 (h1) as the distance from the lowest to the highest point in peak 1, p2area as area under the second peak, and aplhf as high frequency “noise” in region between peaks.

Figure 2

Receiver operating characteristic curves for the new models based on TKC: WF_TKC (a) and based on KCI: WF_KCI (b). With the model for WF_TKC the area under the curve (AUC) is 0.944. With the model for WF_KCI AUC the area is 0.821.

Figure 3

Congruence of WF_TKC and WF_KCI. The upper right and lower left side show identical decisions; the upper left and lower right side show the different decisions of WF_TKC and WF_KCI.