Dataset Information

Enhanced Combined Tomography and Biomechanics Data for Distinguishing Forme Fruste Keratoconus.

ABSTRACT: To evaluate the performance of the Ocular Response Analyzer (ORA) (Reichert Ophthalmic Instruments, Depew, NY) variables and Pentacam HR (Oculus Optikgeräte GmbH, Wetzlar, Germany) tomographic parameters in differentiating forme fruste keratoconus (FFKC) from normal corneas, and to assess a combined biomechanical and tomographic parameter to improve outcomes.Seventy-six eyes of 76 normal patients and 21 eyes of 21 patients with FFKC were included in the study. Fifteen variables were derived from exported ORA signals to characterize putative indicators of biomechanical behavior and 37 ORA waveform parameters were tested. Sixteen tomographic parameters from Pentacam HR were tested. Logistic regression was used to produce a combined biomechanical and tomography linear model. Differences between groups were assessed by the Mann-Whitney U test. The area under the receiver operating characteristics curve (AUROC) was used to compare diagnostic performance.No statistically significant differences were found in age, thinnest point, central corneal thickness, and maximum keratometry between groups. Twenty-one parameters showed significant differences between the FFKC and control groups. Among the ORA waveform measurements, the best parameters were those related to the area under the first peak, p1area1 (AUROC, 0.717 ± 0.065). Among the investigator ORA variables, a measure incorporating the pressure-deformation relationship of the entire response cycle was the best predictor (hysteresis loop area, AUROC, 0.688 ± 0.068). Among tomographic parameters, Belin/Ambrósio display showed the highest predictive value (AUROC, 0.91 ± 0.057). A combination of parameters showed the best result (AUROC, 0.953 ± 0.024) outperforming individual parameters.Tomographic and biomechanical parameters demonstrated the ability to differentiate FFKC from normal eyes. A combination of both types of information further improved predictive value. [J Refract Surg. 2016;32(7):479-485.].

SUBMITTER: Luz A

PROVIDER: S-EPMC6028187 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Enhanced Combined Tomography and Biomechanics Data for Distinguishing Forme Fruste Keratoconus.

Luz Allan A Lopes Bernardo B Hallahan Katie M KM Valbon Bruno B Ramos Isaac I Faria-Correia Fernando F Schor Paulo P Dupps William J WJ Ambrósio Renato R

Journal of refractive surgery (Thorofare, N.J. : 1995) 20160701 7

<h4>Purpose</h4>To evaluate the performance of the Ocular Response Analyzer (ORA) (Reichert Ophthalmic Instruments, Depew, NY) variables and Pentacam HR (Oculus Optikgeräte GmbH, Wetzlar, Germany) tomographic parameters in differentiating forme fruste keratoconus (FFKC) from normal corneas, and to assess a combined biomechanical and tomographic parameter to improve outcomes.<h4>Methods</h4>Seventy-six eyes of 76 normal patients and 21 eyes of 21 patients with FFKC were included in the study. Fif ...[more]

PMID: 27400080

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Project description:Purpose:The study aimed to evaluate the visual quality of forme fruste keratoconus (FFK) and mild and moderate keratoconus by using an optical quality analysis system II (OQAS-II) and to explore the correlation between optical quality parameters and the disease progression. Methods:Twenty-one normal eyes, twenty-one FFK eyes, twenty-one mild keratoconus eyes, and twenty-one moderate keratoconus eyes were included in this prospective study. The optical quality parameters, such as object scatter index (OSI), modulation transfer function cutoff (MTF cutoff), strehl ratio (SR), and OQAS-II values at contrasts of 100% (OV-100), 20% (OV-20), and 9% (OV-9), were measured by OQAS-II. The repeatability of these parameters was analyzed by intraclass correlation coefficient (ICC), repeatability coefficient (RC), and coefficient of variation (CVw). Correlations between optical quality parameters and mean central keratometry readings (K mean) were evaluated. The sensitivity and specificity of the parameters were analyzed using the receiver operating characteristic (ROC). Results:All the optical quality parameters among four groups showed good repeatability (all ICC?0.75). The MTF cutoff, SR, OV-100, OV-20, OV-9 in FFK, mild and moderate keratoconus eyes were significantly lower than those in the normal group (all P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all K mean) were evaluated. The sensitivity and specificity of the parameters were analyzed using the receiver operating characteristic (ROC). r?=?-0.710, P < 0.05). The ROC analyses of the MTF cutoff, SR, OV-100, OV-20, and OV-9 showed significant area under the curve (AUC) in discriminating FFK form normal, mild keratoconus from FFK, and moderate keratoconus from mild keratoconus (all. Conclusion:The repeatability of OQAS-II is good in measuring visual quality of normal as well as FFK, mild, and moderate keratoconus. The visual quality of the FFK, mild, and moderate keratoconus is worse than that in normal eyes. The OQAS-II has the potential value in screening FFK from normal eyes and might be a useful tool for evaluating the progression of keratoconus.

Project description:PURPOSE:To determine optimal objective, machine-derived variables and variable combinations from Scheimpflug and spectral-domain (SD) OCT imaging to distinguish the clinically unaffected eye in patients with asymmetric keratoconus (AKC) from a normal control population. DESIGN:Retrospective case-control study. PARTICIPANTS:Thirty clinically unaffected eyes with no physical findings on slit-lamp examination, no definitive abnormalities on corneal imaging, and corrected distance acuity of 20/20 or better from 30 patients with highly AKC eyes and 60 eyes from 60 normal control patients who had undergone uneventful LASIK with at least 2 years of stable follow-up (controls). METHODS:Scheimpflug and SD OCT imaging were obtained in all eyes, and receiver operating characteristic (ROC) curves were generated to determine area under the curve (AUC), sensitivity, and specificity for each machine-derived variable and variable combination. MAIN OUTCOME MEASURES:Distinguishing AKC eyes from controls as determined by AUC, sensitivity, and specificity. RESULTS:No individual machine-derived metric from Scheimpflug or SD OCT technology yielded an AUC higher than 0.75. Combining 5 Scheimpflug metrics (index height decentration [IHD], index vertical asymmetry [IVA], pachymetry apex, inferior-superior value, and Ambrosio's Relational Thickness Maximum [ARTmax]) yielded the best Scheimpflug results (AUC 0.86, sensitivity 83%, specificity 83%). Combining 11 SD OCT thickness metrics (minimum-median, temporal outer, superior nasal outer, minimum, epithelium minimum-maximum, epithelial standard deviation, superior inner, superior outer, superior temporal outer, superior nasal inner, central) yielded the best SD OCT results (AUC 0.96, sensitivity 89%, specificity 89%). Combining 13 total Scheimpflug/SD OCT metrics yielded the best results overall (AUC 1.0, sensitivity 100%, specificity 100%). The most impactful variables in combined models included epithelial thickness variability and total focal corneal thickness variability from SD OCT and anterior curvature and topometric indices from Scheimpflug technology. No posterior corneal metrics were impactful in modeling. CONCLUSIONS:Individual machine-derived metrics from Scheimpflug and SD OCT imaging poorly distinguished normal eyes from minimally affected eyes from patients with highly AKC. Combined SD OCT metrics performed better than combined Scheimpflug metrics. Combining anterior curvature and asymmetry indices from Scheimpflug with regional total thickness and epithelial thickness variability metrics from SD OCT clearly distinguished the 2 populations. Posterior corneal indices were not useful in distinguishing populations.

Project description:BackgroundThe steep cornea in keratoconus can greatly impair eyesight. The etiology of keratoconus remains unclear but early injury that weakens the corneal stromal architecture has been implicated. To explore keratoconus mechanics, we conducted two numerical simulation studies.MethodsA finite-element model describing the five corneal layers and the heterogeneous mechanical behaviors of the ground substance and lamellar collagen-fiber architecture in the anterior and posterior stroma was developed using the Holzapfel-Gasser-Ogden constitutive model. The geometry was from a healthy subject. Its stroma was divided into anterior, middle, and posterior layers to assess the effect of changing regional mechanical parameters on corneal displacement and maximum principal stress under intraocular pressure. Specifically, the effect of softening an inferocentral corneal button, the collagen-based tissues throughout the whole cornea, or specific stromal layers in the button was examined. The effect of simply disorganizing the orthogonally-oriented posterior stromal fibers in the button was also assessed. The healthy cornea was also subjected to eye rubbing-like loading to identify the corneal layer(s) that experienced the most tensional stress.ResultsConical deformation and corneal thinning emerged when the corneal button or the mid-posterior stroma of the button underwent gradual softening or when the collagen fibers in the mid-posterior stroma of the button were dispersed. Softening the anterior layers of the button or the whole cornea did not evoke conical deformation. Button softening greatly increased and disrupted the stress on Bowman's membrane while mid-posterior stromal softening increased stress in the anterior layers. Eye rubbing profoundly stressed the deep posterior stroma while other layers were negligibly affected.DiscussionThese observations suggest that keratoconus could be initiated, at least partly, by mechanical instability/damage in the mid-posterior stroma that then imposes stress on the anterior layers. This may explain why subclinical keratoconus is marked by posterior but not anterior elevation on videokeratoscopy.

Dataset Information

Enhanced Combined Tomography and Biomechanics Data for Distinguishing Forme Fruste Keratoconus.

Publications

Enhanced Combined Tomography and Biomechanics Data for Distinguishing Forme Fruste Keratoconus.

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