Effect of Myopia on the Thickness of the Retinal Nerve Fiber Layer Measured by Cirrus HD Optical Coherence Tomography

Kang, Sei-Kwon; Hong, Seung Woo; Im, Seong Kyu; Lee, Sang Hyup; Ahn, Myeong Im

doi:10.1167/iovs.09-4737

Cited by 322 publications

(333 citation statements)

References 35 publications

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“…Furthermore, rotations of the optic nerve are expected to cause a shift of RNFL entering the optic nerve head. In these eyes, the automatic segmentation protocols used in commercially available OCT machines could not accurately measure the thickness of the RNFL, and therefore highly myopic patients were among the most difficult patients to evaluate for glaucoma 7,72,73 (Figure 5). The pattern of RNFL distribution was altered in high myopes with thinner average, superior, nasal, and inferior but thicker temporal nerve fiber layer thickness and a temporal shift in the superior and inferior peak locations.…”

Section: Optic Nerve Headmentioning

confidence: 99%

“…The pattern of RNFL distribution was altered in high myopes with thinner average, superior, nasal, and inferior but thicker temporal nerve fiber layer thickness and a temporal shift in the superior and inferior peak locations. 73 Torsion of the optic disc occurs when it is rotated along the coronal plane, and the direction of rotation is more commonly counterclockwise such that the superior aspect of the long axis is rotated temporally when viewing the right eye. The RNF from the temporal periphery courses around the central macula, converging on the optic canal either superiorly or inferiorly.…”

Section: Optic Nerve Headmentioning

confidence: 99%

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Advances of optical coherence tomography in myopia and pathologic myopia

Cheung

Luk

et al. 2016

Eye

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Section: Optic Nerve Headmentioning

confidence: 99%

Section: Optic Nerve Headmentioning

confidence: 99%

Advances of optical coherence tomography in myopia and pathologic myopia

Cheung

Luk

et al. 2016

Eye

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“…MS subjects with MME were excluded from our cohort. OCT has also contributed to the study of more traditional ophthalmological conditions such as glaucoma [7][8][9][10] and myopia [11], as well as to retinal vasculature [12,13], and to the exploration of more obliquely related conditions such as Alzheimer's disease (AD) [14][15][16] and diabetes [17,18]. The study of such a wide assortment of pathologies necessitates automated processing, which in the case of macular retinal OCT starts with segmentation of the various retinal cellular layers.…”

Section: Introductionmentioning

confidence: 99%

Multiple-object geometric deformable model for segmentation of macular OCT

Carass

Lang

Hauser

et al. 2014

Biomed. Opt. Express

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Optical coherence tomography (OCT) is the de facto standard imaging modality for ophthalmological assessment of retinal eye disease, and is of increasing importance in the study of neurological disorders. Quantification of the thicknesses of various retinal layers within the macular cube provides unique diagnostic insights for many diseases, but the capability for automatic segmentation and quantification remains quite limited. While manual segmentation has been used for many scientific studies, it is extremely time consuming and is subject to intra-and inter-rater variation. This paper presents a new computational domain, referred to as flat space, and a segmentation method for specific retinal layers in the macular cube using a recently developed deformable model approach for multiple objects. The framework maintains object relationships and topology while preventing overlaps and gaps. The algorithm segments eight retinal layers over the whole macular cube, where each boundary is defined with subvoxel precision. Evaluation of the method on single-eye OCT scans from 37 subjects, each with manual ground truth, shows improvement over a state-of-the-art method.

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“…Therefore, exact disc size in an eye with axial length other than 24.46 mm and/or refraction <0 D is different from printout values and manual correction of optic disc measurements is necessary. In order to correct axial length-related ocular magnification, Littmann formula (t=p·q·s), as modified by Bennet and later adopted by Leung et al and Kang et al was applied (12)(13)(14)(15). In this formula, t is actual fundus dimension, s is measurement on OCT, p is magnification factor related to imaging system, and q is magnification factor related to the eye.…”

Section: Methodsmentioning

confidence: 99%

Comparison of Corneal Biomechanical Properties Betweeen Physiological Macrodiscs and Glaucomatous Macrodiscs

Onmez¹

2017

Beyoglu Eye J

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Objectives:This study was designed to compare optic nerve head (ONH) parameters and corneal biomechanical properties of healthy and glaucomatous macrodiscs. Methods: This cross-sectional study included total of 234 eyes, of which 92 served as normal controls, 92 had healthy macrodiscs, and 50 had glaucomatous macrodiscs. Measurement of ONH parameters in all p¬atients was performed using optic coherence tomography (OCT). Corneal hysteresis (CH) was measured in each patient using Ocular Response Analyzer (ORA; Reichert, Inc., Depew, NY, USA). Central corneal thickness (CCT) was determined by ultrasonic pachymetry. All OCT and ORA parameters of healthy and glaucomatous macrodiscs were compared. Results: Optic disc area of healthy macrodiscs and glaucomatous macrodiscs was similar, and larger than observed in control group (p=0.70, p=0.0001, respectively). Rim area was significantly thinner in glaucoma group than healthy macrodisc group or control group. (p=0.0001, p=0.022, respectively) Mean cup area of glaucomatous discs was larger than healthy macrodiscs (p=0.001). Cup/disc (C/D) area ratio, and horizontal and vertical C/D ratios were higher in glaucoma group than healthy macrodisc group (p=0.002, p=0.002, p=0.018, respectively) ORA analyses revealed that CH of glaucoma patients was lower than that of healthy macrodisc or control group (p=0.048, p=0.035, respectively), whereas, mean CH of macrodisc group was similar to that of control group (p=0.988). Mean CCT of macrodisc group was higher than that observed in control or glaucoma patients (p=0.015, p=0.045). Conclusion: It was concluded that OCT analyses can help differentiate healthy macrodiscs from glaucomatous discs. CH and corneal thickness measurements of healthy macrodiscs are greater than those of glaucomatous optic discs.

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Effect of Myopia on the Thickness of the Retinal Nerve Fiber Layer Measured by Cirrus HD Optical Coherence Tomography

Cited by 322 publications

References 35 publications

Advances of optical coherence tomography in myopia and pathologic myopia

Advances of optical coherence tomography in myopia and pathologic myopia

Multiple-object geometric deformable model for segmentation of macular OCT

Comparison of Corneal Biomechanical Properties Betweeen Physiological Macrodiscs and Glaucomatous Macrodiscs

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