Ana Laura C. Canedo, MD
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Transcript of Ana Laura C. Canedo, MD
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics Study Group
Comparative Study of Corneal Biomechanical Properties Based on Waveform–Derived Parameters and Tomographic Thickness in Normal
and Keratoconic EyesAna 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
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics 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
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics 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
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics Study Group
Methods226 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.
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics 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.Sensitivity Specificity Criterion AUROC
Standard Error
p1area 84,1 92 <=2778.875 0,945 0,0133p2area 83 92,5 <=1733 0,94 0,015
p1area1 88,6 84,1 <=1329.75 0,929 0,0163p2area1 87,5 87,2 <=813 0,925 0,0178
h1 81,8 85,8 <=353.438 0,919 0,0159h11 81,8 85,8 <=235.625 0,919 0,0159CRF 84,1 82,7 <=8.3 0,892 0,0245
h2 77,3 84,5 <=276.938 0,878 0,0218h21 77,3 84,5 <=184.625 0,878 0,0218CH 81,8 78,3 <=9.1 0,854 0,0246
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics Study Group
p1area p2area p2area1 p1area1 CH
p1area 1 0,739 0,208 0,001 0.001
p2area 1 0,006 0,441 <0.001
p2area1 1 0,846 0.005
p1area1 1 0.007
CH 1
P-value for ROC Comparisons
Corneal Hysteresis (CH)
p1 area and p2 area and height derived parameters outperformed CH to
diagnose keratoconush1 h11 h2 h21 CH
h1 1 1 0,039 0,039 0,024
h11 1 0,039 0,039 0,024
h2 1 1 0,421
h21 1 0,421
CH 1
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics Study Group
p1area p2area p2area1 p1area1 CRF
p1area 1 0,739 0,208 0,001 0,04
p2area 1 0,006 0,441 0,044
p2area1 1 0,846 0,173
p1area1 1 0,173
CRF 1
P-value for ROC Comparisons
Corneal Resistance Factor (CRF)
h1 h11 h2 h21 CRF
h1 1 1 0,039 0,039 0,324
h11 1 0,039 0,039 0,324
h2 1 1 0,646
h21 1 0,646
CRF 1
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics 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 - TopographyNormal Thin Cornea
B – Topography: Keratoconus
A - Normal Thin CorneaCCT: 500µm
B - KeratoconusCCT: 536 µm
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics 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.
e-Poster
ALC Canedo, MD2010
Rio de JaneiroCorneal
Tomograhyand
Biomechanics Study Group
e-Poster