1. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group Comparative Study of Corneal Biomechanical Properties Based on Waveform–Derived Parameters and Tomographic Thickness in Normal and Keratoconic Eyes Ana Laura C. Canedo, MD Renato Ambrósio Jr, MD, PhD; Ricardo Lousada, MD; Marcella Salomão, MD; Bruno Valbon, MD; Frederico P. Guerra, MD; Michael W. Belin, MD, FACS

2. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group e-Poster Diagnosis of keratoconus and ectatic conditions is a critical part for screening refractive candidates to prevent ectasia. Biomechanical assessments are promising for assessing ocular rigidity and ectasia susceptibility. The Reichert ORA (Ocular Response Analyzer) is the first clinically available instrument. Classical metrics are Corneal Hysteresis (CH), Corneal Resistance Factor (CRF) and gold standard (Goldmann)-correlated intraocular pressure (IOPg) and corneal-compensated intraocular pressure (IOPcc). Introduction CH and CRF are statistically different among keratoconus and normals but there is significant overlap. Other metrics derived from the waveform provide more detail beyond CH and CRF about corneal biomechanics

3. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group Ocular Response Analyzer (ORA, Reichert) Measurement Corneal response to a collimetric air pulse is monitored by the infrared light reflection (applanation => peak) Detects two applanation events correlated with the air pulse pressure (INWARD - p1 and OUTWARD - p2) The delay of p2 is caused by corneal viscous damping [CH = p1 – p2] and [CRF = p1 - (K * p2)] Normal Values: CH: 10.17 ± 1.82 (3.23 to 14.58) (Fontes et. Al, JRS 2008) CRF: 10.14 ± 1.8 (5.45 to 15.1) Ectasia leads to lower CH and CRF and altered signals CH or CRF < 8.8mmHg is considered a relative contra indication for LASIK based on normal population values New parameters and waveform score (WS) derive from the ORA signal. ORA Signal To CH, CRF IOPcc, IOPg and the novel ORA waveform–derived parameters in normal and keratoconic eyes. Settings: Instituto de Olhos Renato Ambrósio; Rio de Janeiro Corneal Tomography and Biomechanics Study Group Purpose Purpose

4. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group Methods 226 normal corneas from 113 patients and 88 keratoconic eyes from 44 pa tients. Eyes were diagnosed as keratoconus based on clinical examination, including corneal topography (Placido) and tomography (rotating Scheimpflug). CH, CRF and 38 new parameters derived from the ORA waveform signal were extracted from the 2.0 ORA software. The best waveform signal was chosen from the exam of each eye. Statistical analysis were accomplished by the BioEstat 5.0 and MedCalc 11.2 Using unpaired Ttest and Mann Whitney test were used to evaluate statistical significance between groups Receiver operating characteristic (ROC) curves were used to determine the test’s overall predictive accuracy (area under the curve) and to identify optimal cutoff points to maximize sensitivity and specificity in discriminating keratoconus from normals. Comparison of ROC Curves were accomplished to evaluate the superiority of the best waveform-derived parameters than CH and CRF.

5. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group Results Statistical significant differences between keratoconus and normals were found in all but 6 parameters: IOPcc; dslope2; W2; dslope21; w1; w21. The parameters correlated to the area under the applanation signals and first applanation signal height had the best performances to separate the groups. CRF and CH had best cut off values of 8.3 and 9.1mmHg respectively. The sensitivity and specificity of CRF were 84,1% and 82,7% and for CH, 81.8 and 78.3%. CRF ranked as the 8th and CH, as 16th parameter on the AUROC. P1area had sensitivity and specificity of 84.1% and 92% and P2- area1, 87.5% and 87.2% respectively. SensitivitySpecificityCriterionAUROC Standard Error p1area84,192<=2778.8750,9450,0133 p2area8392,5<=17330,940,015 p1area188,684,1<=1329.750,9290,0163 p2area187,587,2<=8130,9250,0178 h181,885,8<=353.4380,9190,0159 h1181,885,8<=235.6250,9190,0159 CRF84,182,7<=8.30,8920,0245 h277,384,5<=276.9380,8780,0218 h2177,384,5<=184.6250,8780,0218 CH81,878,3<=9.10,8540,0246

6. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group p1areap2areap2area1p1area1CH p1area 10,7390,2080,0010.001 p2area 10,0060,441<0.001 p2area1 10,8460.005 p1area1 10.007 CH 1 P-value for ROC Comparisons Corneal Hysteresis (CH) p1 area and p2 area and height derived parameters outperformed CH to diagnose keratoconus h1h11h2h21CH h1 110,039 0,024 h11 10,039 0,024 h2 110,421 h21 10,421 CH 1

7. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group p1areap2areap2area1p1area1CRF p1area 10,7390,2080,0010,04 p2area 10,0060,4410,044 p2area1 10,8460,173 p1area1 10,173 CRF 1 P-value for ROC Comparisons Corneal Resistance Factor (CRF) h1h11h2h21CRF h1 110,039 0,324 h11 10,039 0,324 h2 110,646 h21 10,646 CRF1

8. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group CH and CCT are not enough. Case examples: A-CCT: 500µm; B-CCT: 531µm; CH is 9.1 mmHg in both. Thickness Profile, CRF and Waveform signal provided critical information for correct diagnostic interpretation! A - Topography Normal Thin Cornea B – Topography: Keratoconus A - Normal Thin Cornea CCT: 500µm B - Keratoconus CCT: 536 µm

9. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group Conclusions There were significantly higher ORA metrics in normals than in keratoconic eyes. IOPcc was not significantly different among normals and keratoconus eyes. Novel metrics derived from the ORA waveform signal provided better performance to identify keratoconus than CH and CRF. A combination of waveform parameters and tomographic parameters is likely to improve diagnostic performance and provides great potential for artificial intelligence methods for detecting ectasia and its susceptibility.

10. e-Poster ALC Canedo, MD 2010 Rio de Janeiro CornealTomograhyandBiomechanics Study Group Study Group e-Poster alccanedo@gmail.com