1. Mathematical Description of the Ocular Response Analyzer Applanation Signal in Post-LASIK Ectasia Mujtaba A. Qazi, M.D. 1,2 David A. Luce, Ph.D. 3 Jay S. Pepose, M.D., Ph.D. 1,2 1. Washington University School of Medicine 2. Pepose Vision Institute, St. Louis, Missouri 3. Reichert Inc.

2.  Dr. Pepose has received research support from Reichert.  Dr. Luce is an employee with Reichert. Financial Disclosure

3. Ocular Response Analyzer Uses air pulse to produce 2 (inward and outward) applanation events: AIR PULSEINFRARED AIR PULSE & INFRARED Signals IOP-g (Goldmann equivalent) IOP-cc (Cornea Compensation): IOP calculated as a function of CH IOP-cc (Cornea Compensation): IOP calculated as a function of CH Corneal Hysteresis (CH): ability of cornea to dampen or absorb applied force = P1-P2 (mean value in normal population ~ 10) Corneal Hysteresis (CH): ability of cornea to dampen or absorb applied force = P1-P2 (mean value in normal population ~ 10) Corneal Resistance Factor (CRF): ability of cornea to resist or rebound from applied force = P1-0.43xP2 (mean value in normal population ~10) Corneal Resistance Factor (CRF): ability of cornea to resist or rebound from applied force = P1-0.43xP2 (mean value in normal population ~10)

4. Study Design  ORA waveforms captured in series of eyes with clinical diagnosis of Post-LASIK Ectasia (n=14)  Compared to pachymetry-matched:  Pre-LASIK, Control eyes from pool of preoperative keratorefractive surgery patients (n=7)  Post-LASIK, Control eyes (n=17)  Keratoconus eyes (n=22)  Along with IOP & Biomechanical metrics,  38 novel ORA signal parameters evaluated  ORA signals then entered into 11 x 36 Matrix Neural Net

5. ORA Measurements Pachymetry- matched KCN, pre- and post-LASIK Controls, and post-LASIK Ectasia Pre-LASIKPost-LASIKKCN LASIK Ectasia N7172214 CCT µm 458.8 ± 15.4 420.8 ± 30.6 434.3 ± 37.4 409.0 ± 58.9 IOP-g mmHg 12.0 ± 3.4 10.0 ± 2.4 9.6 ± 2.7 8.2 ± 1.3 IOP-cc mmHg 14.5 ± 2.7 13.7 ± 2.2 13.8 ± 2.3 13.2 ± 2.2 CH mmHg 8.0 ± 1.1 7.3 ± 0.9 7.6 ± 1.2 7.1 ± 1.5 CRF mmHg 7.0 ± 1.6 5.9 ± 1.0 5.8 ± 1.5 5.4 ± 1.3 CRF: CRF: Pre-LASIK to LASIK Ectasia approaches statistical significance (p=0.06, ANOVA with Bonferroni correction)

6. Applanation Waveform analyzed using 38 mathematical metrics, such as:  Height of Peak 1 & 2  Width of Peak 1 & 2  Ratio of Height : Width of Peak 1 & 2  Slope of the rising and descending portions of Peak 1 & 2  Acceleration of the slopes of Peak 1 & 2  Slope of upper half of Peak 1 & 2  Ascending segments minus descending segments of rising portion of Peak1 & 2 (“chatter”)  Ratio of width of upper half : width of lower half of Peak 1 & 2  Pre-LASIK Control  Post- LASIK Control  Post- LASIK Ectasia

10. Neural Net Analysis There was a statistically significant difference in the mean Neural Net Scores of these 4 populations (p<0.01)

11. Neural Net Scores Unoperated Normal Post-LASIK Normal KCN Post-LASIK Ectasia

12. Summary:   There is a trend for lower CRF (and CH) values in the Post- LASIK Ectasia group compared to pachymetry-matched control and Keratoconic eyes.   There is no difference in mean IOPcc for all groups evaluated.   The applanation signals are altered by corneal pathology or surgery. This may be due to a smaller area of applanation or a dynamic misalignment due to non-uniform deformation of the asymmetric corneal surface with air-pulse application.   Novel ORA signal metrics, applied through a Neural Net, may be used to assist in the diagnosis of corneal ectasia.   A larger sample size is needed to fully evaluate the utility of this technique for differentiating between early or forme fruste ectasia and normal eyes and to validate the Neural Net.