March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
A Novel Analytical Method to Quantitatively Describe the Corneoscleral Junction Using Optical Coherence Tomography (OCT)
Author Affiliations & Notes
  • Bo Tan
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Andrew D. Graham
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Yixiu Zhou
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Avanti Ghanekar
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Joycelyn Niimi
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Wing Li
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Meng C. Lin
    Clinical Research Center, University of California, Berkeley, School of Optometry, Berkeley, California
  • Footnotes
    Commercial Relationships  Bo Tan, None; Andrew D. Graham, None; Yixiu Zhou, None; Avanti Ghanekar, None; Joycelyn Niimi, None; Wing Li, None; Meng C. Lin, None
  • Footnotes
    Support  UCB-CRC Research Fund
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 106. doi:
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      Bo Tan, Andrew D. Graham, Yixiu Zhou, Avanti Ghanekar, Joycelyn Niimi, Wing Li, Meng C. Lin; A Novel Analytical Method to Quantitatively Describe the Corneoscleral Junction Using Optical Coherence Tomography (OCT). Invest. Ophthalmol. Vis. Sci. 2012;53(14):106.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To demonstrate a technique to analyze OCT images of the corneoscleral junction (CSJ) and to calculate metrics descriptive of the CSJ angle and regional topography.

Methods: : Twenty nine subjects completed the study. A CSJ image was taken by a commercial SD-OCT (Bioptigen, Inc.) on four quadrants (nasal, temporal, superior, and inferior) of each eye. The surface edge of the CSJ was manually marked with 21 evenly distributed points spanning a 2 mm region on the CSJ. A linear regression was performed on these 21 points. The CSJ is characterized by 5 metrics: the R-squared of the regression (R2), the sum of squared residuals (SSR), the sum of squared orthogonalized residuals (SSRn), and the standard deviations of both the residuals (SDr) and the orthogonalized residuals (SDrn). Repeatability and reproducibility (RR) were assessed, as were differences in the metrics across quadrants.

Results: : The RR study showed good repeatability and reproducibility with Limits of Agreement between visits closely centered on zero, and little variability between observers. Variance component analysis showed that the variability in all metrics due to eyes, visits, and observers was orders of magnitude smaller than the true variation between subjects. Mixed effects models of 29 subjects’ images showed that the nasal quadrant had significantly greater values of all of five metrics than the other three quadrants (p < 0.001 for all metrics), while the inferior quadrant had greater values (but not significantly so) than the temporal and the superior quadrants for all metrics except R2.

Conclusions: : Previous studies have used a measurement of angle to describe the CSJ. This method can give highly variable estimates due to the infinite number of choices in drawing lines tangential to the two aspherical curves (cornea and sclera), especially when the roughness of the CSJ surface is high or the concave and convex surfaces form a deep but flat valley. Our method provides a set of metrics that quantify the characteristics of the CSJ region more reliably and comprehensively than previously reported methods. These metrics will be particularly appropriate for future studies assessing the relationships among ocular characteristics, contact lens fitting parameters and subjective comfort.

Keywords: cornea: clinical science • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • imaging/image analysis: clinical 
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