Corneal Descriptive Indices in the Fellow Eye of Unilateral Keratoconus

Lema, M; Romero, Paloma; Mato, Jose Luis; Feijóo, Elío Díez

doi:10.1097/icl.0b013e318198be6e

Cited by 10 publications

(11 citation statements)

References 25 publications

(37 reference statements)

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“…New parameters, such as corneal volume, pachymetric progression and elevation maps are of SD= standard deviation; min= minimum; max= maximum; D= diopters; μm= micrometers; mm= millimeters; mmHg= millimeters of mercury; K-Ave= central keratometry; CA= corneal astigmatism ; CCT= central corneal thickness; AC depth= anterior chamber depth; CV= corneal volume; CH= corneal hysteresis; CRF= corneal resistance factor great utility in clinical practice (8)(9)(10)(13)(14)(33)(34)(35)(36) . In the present study, we were able to detect statistical difference in all anterior segment parameters given by the Pentacam rotating Scheimpflug camera.…”

Section: Discussionmentioning

confidence: 99%

Ability of corneal biomechanical metrics and anterior segment data in the differentiation of keratoconus and healthy corneas

Fontes¹,

Ambrósio²,

Jardim³

et al. 2010

Arq. Bras. Oftalmol.

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Purpose: To evaluate the sensitivity, specificity, and test accuracy of corneal biomechanical metrics and anterior segment data in differentiating keratoconus from healthy corneas. Methods: Comparative case series. Patients with and without keratoconus (gender and age-matched) were submitted for complete eye examinations including corneal hysteresis (CH) and corneal resistance factor (CRF) as measured by the Ocular Response Analyzer and anterior segment data as gathered through Pentacam assessments. The anterior segment data measurement included average central keratometric readings (K-Ave), corneal astigmatism (CA), central corneal thickness (CCT), anterior chamber depth (AC depth) and corneal volume (CV). All parameters were assessed, compared and analyzed. A receiver operating characteristic (ROC) curve was used to identify the best cutoff point by which to maximize the sensitivity and specificity of discriminating keratoconus from normal corneas for each data category. Results: Seventy seven eyes from forty three patients (24 male, 19 female) with keratoconus and eighty six eyes from forty three (24 male, 19 female) healthy controls were enrolled. ROC curve analysis showed poor overall predictive accuracy for all studied parameters in differentiating keratoconus from normal corneas. The highest sensitivity (79.2%) was obtained for both AC depth and CH (cutoff points 3.22 mm and 9.39 mmHg respectively). The best specificity (89.5%) and test accuracy (80.34%) were obtained for CA (cutoff point of 2.2 D). Conclusion: When considered together, studied parameters showed statistical differences between groups. However, when considered independently they presented low sensitivity, specificity and test accuracy in differentiating keratoconus from healthy corneas. Keywords: Cornea; Corneal diseases; Corneal topography; Biomechanics; Keratoconus. RESUMOObjetivo: Avaliar a sensibilidade, especificidade e acurácia de parâmetros biomecânicos e anatômicos do segmento anterior isolados na diferenciação de córneas saudáveis e com ceratocone. Métodos: Estudo tipo série de casos comparativa. Pacientes com ceratocone e controles saudáveis foram pareados (idade e sexo) e submetidos a exame oftalmológico completo, incluindo avaliação biomecânica (ORA) e tomográfica (Pentacam). Ceratometria central média, astigmatismo corneano, espessura corneana central, profundidade da câmara anterior, volume corneano, CH e CRF foram estabelecidos, avaliados e comparados. Curvas ROC (Receiver operating characteristic) foram utilizadas para identificar o melhor valor de corte que apresentasse a maior sensibilidade e especificidade na discriminação entre ceratocone e córneas saudáveis para cada dado estudado. Resultados: Setenta e sete olhos de 43 pacientes com ceratocone (24 homens e 19 mulheres) e 86 olhos de pacientes saudáveis (24 homens e 19 mulheres) foram incluídos no estudo. Curvas ROC mostraram baixa acurácia na predição do diagnóstico de ceratocone em todos os parâmetros isolados estudados. Maior sensibilidade encontrada foi 79,...

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Section: Discussionmentioning

confidence: 99%

Ability of corneal biomechanical metrics and anterior segment data in the differentiation of keratoconus and healthy corneas

Fontes¹,

Ambrósio²,

Jardim³

et al. 2010

Arq. Bras. Oftalmol.

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“…Several parameters to help the physician conclude that an eye is normal or abnormal have been suggested. 15,[26][27][28][29][30][31][32][33][34][35][36][37][38] Keratoconus progression in the fellow eye of the patient who has keratoconus can help us understand the characteristics of the early keratoconic eye. However, even with corneal curvature and thickness measurements, it is difficult to differentiate the fellow eye of a patient with keratoconus from a normal eye.…”

Section: Detection Of Eyes That May Progress To Ectasia Naturallymentioning

confidence: 99%

“…However, even with corneal curvature and thickness measurements, it is difficult to differentiate the fellow eye of a patient with keratoconus from a normal eye. 38 Computer-assisted videokeratoscopy, corneal tomography, and Scheimpflug imaging are available for clinical use for diagnosing keratoconus using parameters developed from analysis of eyes with known keratoconus. [39][40][41][42][43][44][45][46][47] High-resolution ultrasound epithelial and stromal thickness measurement may be a sensitive way of detecting epithelial thinning that would mask an irregular anterior stromal surface in the early stages of keratoconus, in which the epithelium tries to compensate for the cone by thinning over the cone and thickening around the cone 48 …”

Section: Detection Of Eyes That May Progress To Ectasia Naturallymentioning

confidence: 99%

Photorefractive keratectomy in eyes with atypical topography

Hardten¹,

Gosavi²

2009

Journal of Cataract and Refractive Surgery

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Laser correction of refractive errors is one of the most effective surgical procedures today. Even so, the selection of patients who will have the outcomes they expect remains a major challenge. Corneal ectasia, a frustrating problem that can occur naturally with diseases such as keratoconus, has also been reported after refractive surgery. This review addresses the issues surrounding the use of surface refractive surgery in patients who may have atypical topography, which is a risk factor for ectasia. At present, available tests for predicting future corneal stability can give false positives and false negatives. Although the technology for treating irregular corneal astigmatism has improved, results in eyes with irregular astigmatism are less predictable than in eyes with regular astigmatism, even when wavefront- and topography-driven treatments are used. An increased risk for corneal instability may be associated with laser vision correction (LVC), although instability is generally thought to be less of a risk with surface ablation or photorefractive keratectomy than with laser in situ keratomileusis. Surface LVC has shown good success in improving uncorrected distance visual acuity with a relatively low rate of complications, even in eyes with topographic irregularities.

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“…1 Advances in topographic algorithms 2–7 and then tomographic algorithms 8–15 have greatly improved the ability to detect keratoconus at earlier and earlier stages.…”

mentioning

confidence: 99%

“…Several reports have evaluated the fellow eye in unilateral keratoconus as a test bed for assessment of methods for early diagnosis of occult keratoconus using topography, tomography, and biomechanical indicators. 7,10–13,24 …”

mentioning

confidence: 99%

Detection of Keratoconus in Clinically and Algorithmically Topographically Normal Fellow Eyes Using Epithelial Thickness Analysis

Reinstein¹,

Archer²,

Urs³

et al. 2015

J Refract Surg

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PURPOSE To assess the effectiveness of a keratoconus-detection algorithm derived from Artemis very high-frequency (VHF) digital ultrasound (ArcScan Inc., Morrison, CO) epithelial thickness maps in the fellow eye from a series of patients with unilateral keratoconus. METHODS The study included 10 patients with moderate to advanced keratoconus in one eye but a clinically and algorithmically topographically normal fellow eye. VHF digital ultrasound epithelial thickness data were acquired and a previously developed classification model was applied for identification of keratoconus to the clinically normal fellow eyes. Pentacam (Oculus Optikgeräte, Wetzlar, Germany) Belin-Ambrósio Display (BAD) data (5 of 10 eyes), and Orbscan (Bausch & Lomb, Rochester, NY) SCORE data (9 of 10 eyes) were also evaluated. RESULTS Five of the 10 fellow eyes were classified as keratoconic by the VHF digital ultrasound epithelium model. Five of 9 fellow eyes were classified as keratoconic by the SCORE model. For the 5 fellow eyes with Pentacam and VHF digital ultrasound data, one was classified as keratoconic by the VHF digital ultrasound model, one (different) eye by a combined VHF digital ultrasound and Pentacam model, and none by BAD-D alone. CONCLUSIONS Under the assumption that keratoconus is a bilateral but asymmetric disease, half of the ‘normal’ fellow eyes could be found to have keratoconus using epithelial thickness maps. The Orbscan SCORE or the combination of topographic BAD criteria with epithelial maps did not perform better.

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Corneal Descriptive Indices in the Fellow Eye of Unilateral Keratoconus

Abstract: The proposed cutoff values between controls and patients at risk for keratoconus may prove useful for screening purposes.

Cited by 10 publications

References 25 publications

Ability of corneal biomechanical metrics and anterior segment data in the differentiation of keratoconus and healthy corneas

Ability of corneal biomechanical metrics and anterior segment data in the differentiation of keratoconus and healthy corneas

Photorefractive keratectomy in eyes with atypical topography

Detection of Keratoconus in Clinically and Algorithmically Topographically Normal Fellow Eyes Using Epithelial Thickness Analysis

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