Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa
Background: Though the development and fitting of scleral contact lenses are expanding steadily, there is no simple method to provide scleral metrics for scleral contact lens fitting yet. The aim of this study was to establish formulae for estimation of the axial radius of curvature (ARC) of the an...
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BioMed Central
2016
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Online Access: | http://hdl.handle.net/1721.1/105388 https://orcid.org/0000-0003-3681-7410 |
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author | Lee, Sang-Mok Choi, Hyuk Jin Kim, Mee Kum Wee, Won Ryang Choi, Heejin |
author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Lee, Sang-Mok Choi, Hyuk Jin Kim, Mee Kum Wee, Won Ryang Choi, Heejin |
author_sort | Lee, Sang-Mok |
collection | MIT |
description | Background: Though the development and fitting of scleral contact lenses are expanding steadily, there is no simple method to provide scleral metrics for scleral contact lens fitting yet. The aim of this study was to establish formulae for estimation of the axial radius of curvature (ARC) of the anterior sclera using ocular biometric parameters that can be easily obtained with conventional devices. Methods: A semi-automated stitching method and a computational analysis tool for calculating ARC were developed by using the ImageJ and MATLAB software. The ARC of all the ocular surface points were analyzed from the composite horizontal cross-sectional images of the right eyes of 24 volunteers; these measurements were obtained using anterior segment optical coherence tomography for a previous study (AS-OCT; Visante). Ocular biometric parameters were obtained from the same volunteers with slit-scanning topography and partial coherence interferometry. Correlation analysis was performed between the ARC at 8 mm to the axis line (ARC[8]) and other ocular parameters (including age). With ARC obtained on several nasal and temporal points (7.0, 7.5, 8.0, 8.5, and 9.0 mm from the axis line), univariate and multivariate linear regression analyses were performed to develop a model for estimating ARC with the help of ocular biometric parameters. Results: Axial length, spherical equivalent, and angle kappa showed correlations with temporal ARC[8] (tARC[8]; Pearson’s r = 0.653, −0.579, and −0.341; P = 0.001, 0.015, and 0.015, respectively). White-to-white corneal diameter (WTW) and anterior chamber depth (ACD) showed correlation with nasal ARC[8] (nARC[8]; Pearson’s r = −0.492 and −0.461; P = 0.015 and 0.023, respectively). The formulae for estimating scleral curvatures (tARC, nARC, and average ARC) were developed as a function of axial length, ACD, WTW, and distance from the axis line, with good determinant power (72 − 80 %; SPSS ver. 22.0). Angle kappa showed strong correlation with axial length (Pearson’s r = −0.813, P <0.001), and the different correlation patterns of nasal and temporal ARC with axial length can be explained by the ocular surface deviation represented by angle kappa. Conclusions: Axial length, ACD, and WTW are useful parameters for estimating the ARC of the anterior sclera, which is important for the haptic design of scleral contact lenses. Angle kappa affects the discrepancies between the nasal and temporal scleral curvature. |
first_indexed | 2024-09-23T16:55:25Z |
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spelling | mit-1721.1/1053882024-03-20T19:30:17Z Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa Lee, Sang-Mok Choi, Hyuk Jin Kim, Mee Kum Wee, Won Ryang Choi, Heejin Massachusetts Institute of Technology. Institute for Medical Engineering & Science Choi, Heejin Background: Though the development and fitting of scleral contact lenses are expanding steadily, there is no simple method to provide scleral metrics for scleral contact lens fitting yet. The aim of this study was to establish formulae for estimation of the axial radius of curvature (ARC) of the anterior sclera using ocular biometric parameters that can be easily obtained with conventional devices. Methods: A semi-automated stitching method and a computational analysis tool for calculating ARC were developed by using the ImageJ and MATLAB software. The ARC of all the ocular surface points were analyzed from the composite horizontal cross-sectional images of the right eyes of 24 volunteers; these measurements were obtained using anterior segment optical coherence tomography for a previous study (AS-OCT; Visante). Ocular biometric parameters were obtained from the same volunteers with slit-scanning topography and partial coherence interferometry. Correlation analysis was performed between the ARC at 8 mm to the axis line (ARC[8]) and other ocular parameters (including age). With ARC obtained on several nasal and temporal points (7.0, 7.5, 8.0, 8.5, and 9.0 mm from the axis line), univariate and multivariate linear regression analyses were performed to develop a model for estimating ARC with the help of ocular biometric parameters. Results: Axial length, spherical equivalent, and angle kappa showed correlations with temporal ARC[8] (tARC[8]; Pearson’s r = 0.653, −0.579, and −0.341; P = 0.001, 0.015, and 0.015, respectively). White-to-white corneal diameter (WTW) and anterior chamber depth (ACD) showed correlation with nasal ARC[8] (nARC[8]; Pearson’s r = −0.492 and −0.461; P = 0.015 and 0.023, respectively). The formulae for estimating scleral curvatures (tARC, nARC, and average ARC) were developed as a function of axial length, ACD, WTW, and distance from the axis line, with good determinant power (72 − 80 %; SPSS ver. 22.0). Angle kappa showed strong correlation with axial length (Pearson’s r = −0.813, P <0.001), and the different correlation patterns of nasal and temporal ARC with axial length can be explained by the ocular surface deviation represented by angle kappa. Conclusions: Axial length, ACD, and WTW are useful parameters for estimating the ARC of the anterior sclera, which is important for the haptic design of scleral contact lenses. Angle kappa affects the discrepancies between the nasal and temporal scleral curvature. Korea (South). Ministry of Health & Welfare (Projects A084496 and A120018) 2016-11-21T20:05:58Z 2016-11-21T20:05:58Z 2016-10 2015-12 2016-10-08T04:01:46Z Article http://purl.org/eprint/type/JournalArticle 1471-2415 http://hdl.handle.net/1721.1/105388 Lee, Sang-Mok et al. “Estimation of Axial Curvature of Anterior Sclera: Correlation between Axial Length and Anterior Scleral Curvature as Affected by Angle Kappa.” BMC Ophthalmology 16.1 (2016): n. pag. https://orcid.org/0000-0003-3681-7410 en http://dx.doi.org/10.1186/s12886-016-0355-5 BMC Ophthalmology Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ The Author(s). application/pdf BioMed Central BioMed Central |
spellingShingle | Lee, Sang-Mok Choi, Hyuk Jin Kim, Mee Kum Wee, Won Ryang Choi, Heejin Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title | Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title_full | Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title_fullStr | Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title_full_unstemmed | Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title_short | Estimation of axial curvature of anterior sclera: correlation between axial length and anterior scleral curvature as affected by angle kappa |
title_sort | estimation of axial curvature of anterior sclera correlation between axial length and anterior scleral curvature as affected by angle kappa |
url | http://hdl.handle.net/1721.1/105388 https://orcid.org/0000-0003-3681-7410 |
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