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1.
Indian J Ophthalmol ; 71(3): 818-823, 2023 03.
Artigo em Inglês | MEDLINE | ID: mdl-36872685

RESUMO

Purpose: The purpose of the study is to investigate the effects of combined 0.8% tropicamide and 5% phenylephrine on the corneal parameters using Pentacam. Methods: The study was performed on 200 eyes of 100 adult patients visiting the ophthalmology clinic for evaluation of refractive errors or cataract screening. Mydriatic drops (Tropifirin; Java, India) containing tropicamide 0.8%, phenylephrine hydrochloride 5%, and chlorbutol 0.5% (as a preservative) were instilled into the eyes of the patients three times every 10 minutes. The Pentacam was repeated after 30 minutes. The measurement data of various corneal parameters from different Pentacam displays (keratometry, pachymetry, densitometry, and Zernike analysis) was manually compiled on an Excel spreadsheet and analyzed using Statistical Package for the Social Sciences (SPSS) 20 software. Results: Analysis of Pentacam refractive maps revealed a statistically significant increase (P < 0.05) in the values of radius peripheral (cornea front), pupil center Pachymetry, pachymetry apex, thinnest location Pachymetry, and cornea volume. However, pupil dilation did not affect the Q-value (asphericity). Analysis of the densitometry values revealed significant increase in all zones. Aberrations maps revealed statistically significant increase in the value of spherical aberration after the induction of mydriasis, but the values of Trefoil 0º, Trefoil 30º, Koma 90º, and Koma 0º were not affected significantly. We did not observe any untoward effect of the drug, except transient blurring of vision. Conclusion: The current study showed that routine mydriasis in the eye clinics leads to a significant increase in various corneal parameters including corneal pachymetry, cornea densitometry, and spherical aberration as measured by Pentacam, which can influence the decision-making in the management of various corneal diseases. The ophthalmologists should be aware of these issues and make adjustments in their surgical planning accordingly.


Assuntos
Midríase , Midriáticos , Adulto , Humanos , Tropicamida , Fenilefrina , Córnea , Soluções Oftálmicas
2.
Surv Ophthalmol ; 65(2): 187-204, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31560871

RESUMO

The measurement of regional corneal epithelial thickness and characterization of its behavior in response to changes in corneal architecture are increasingly drawing interest in clinical practice. The epithelium has tremendous capacity for remodeling and does so in response to underlying stromal pathology or changes in anterior corneal curvature. Various remodeling patterns have been identified that help distinguish between ectatic and nonectatic corneal conditions. Epithelial mapping has also facilitated more precise, individualized corneal surface disorder treatments. We highlight the different imaging modalities for epithelium measurement, epithelial remodeling patterns in ectatic disorders and after corneal refractive surgery, discuss utility of epithelial measurement in therapeutic refractive surgery planning, and discuss controversies that exist regarding epithelial remodeling, including its mechanisms and its relative importance in surgical planning and screening evaluations.


Assuntos
Paquimetria Corneana/métodos , Topografia da Córnea/métodos , Epitélio Corneano/diagnóstico por imagem , Ceratocone/diagnóstico , Tomografia de Coerência Óptica/métodos , Acuidade Visual , Epitélio Corneano/patologia , Humanos
3.
Semin Ophthalmol ; 34(4): 317-326, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31304857

RESUMO

Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector machines, and various types of neural networks. In general, these techniques demonstrate very good differentiation of normal and keratoconic eyes, as well as good differentiation of normal and form fruste keratoconus. However, it is difficult to directly compare these studies, as keratoconus represents a wide spectrum of disease. More importantly, no public dataset exists for research purposes. Despite these challenges, machine learning in keratoconus detection and refractive surgery screening is a burgeoning field of study, with significant potential for continued advancement as imaging devices and techniques become more sophisticated.


Assuntos
Diagnóstico por Computador/métodos , Ceratocone/diagnóstico , Aprendizado de Máquina , Programas de Rastreamento/métodos , Procedimentos Cirúrgicos Refrativos , Humanos , Seleção de Pacientes
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