TY - JOUR
AU - Leung, Christopher K. S.
AB - Key Points Question Does the application of a myopic normative database improve the diagnostic performance for detection of retinal nerve fiber layer (RNFL) abnormalities in eyes with high myopia? Findings In this cross-sectional study, specificities of a myopic normative database for detection of glaucomatous RNFL abnormalities in the circumpapillary RNFL profile and in the RNFL thickness map were higher (63.0%-100%) compared with the normative database of the optical coherence tomography instrument (8.7%-87.0%) at a comparable level of sensitivities. Meaning Myopic normative databases should be included in optical coherence tomography instruments to improve the diagnostic specificity for detection of RNFL abnormalities. Abstract Importance Analysis of retinal nerve fiber layer (RNFL) abnormalities with optical coherence tomography in eyes with high myopia has been complicated by high rates of false-positive errors. An understanding of whether the application of a myopic normative database can improve the specificity for detection of RNFL abnormalities in eyes with high myopia is relevant. Objective To evaluate the diagnostic performance of a myopic normative database for detection of RNFL abnormalities in eyes with high myopia (spherical equivalent, –6.0 diopters [D] or less). Design, Setting, and Participants In this cross-sectional study, 180 eyes with high myopia (mean [SD] spherical equivalent, –8.0 [1.8] D) from 180 healthy individuals were included in the myopic normative database. Another 46 eyes with high myopia from healthy individuals (mean [SD] spherical equivalent, –8.1 [1.8] D) and 74 eyes from patients with high myopia and glaucoma (mean [SD] spherical equivalent, –8.3 [1.9] D) were included for evaluation of specificity and sensitivity. The 95th and 99th percentiles of the mean and clock-hour circumpapillary RNFL thicknesses and the individual superpixel thicknesses of the RNFL thickness map measured by spectral-domain optical coherence tomography were calculated from the 180 eyes with high myopia. Participants were recruited from January 2, 2013, to December 30, 2015. The following 6 criteria of RNFL abnormalities were examined: (1) mean circumpapillary RNFL thickness below the lower 95th or (2) the lower 99th percentile; (3) one clock-hour or more for RNFL thickness below the lower 95th or (4) the lower 99th percentile; and (5) twenty contiguous superpixels or more of RNFL thickness in the RNFL thickness map below the lower 95th or (6) the lower 99th percentile. Main Outcomes and Measures Specificities and sensitivities for detection of RNFL abnormalities. Results Of the 46 healthy eyes and 74 eyes with glaucoma studied (from 39 men and 38 women), the myopic normative database showed a higher specificity (63.0%-100%) than did the built-in normative database of the optical coherence tomography instrument (8.7%-87.0%) for detection of RNFL abnormalities across all the criteria examined (differences in specificities between 13.0% [95% CI, 1.1%-24.9%; P = .01] and 54.3% [95% CI, 37.8%-70.9%; P < .001]) except for the criterion of mean RNFL thickness below the lower 99th percentile, in which both normative databases had the same specificities (100%) but the myopic normative database exhibited a higher sensitivity (71.6% vs 86.5%; difference in sensitivities, 14.9% [95% CI, 4.6%-25.1%; P = .002]). Conclusions and Relevance The application of a myopic normative database improved the specificity without compromising the sensitivity compared with the optical coherence tomography instrument’s built-in normative database for detection of RNFL abnormalities in eyes with high myopia. Inclusion of myopic normative databases should be considered in optical coherence tomography instruments. Introduction Discerning glaucomatous changes to the optic nerve head is challenging in eyes with high myopia.1,2 Parapapillary atrophy and tilted disc configuration—2 highly prevalent optic disc findings in eyes with high myopia (spherical equivalent,–6.0 diopters [D] or less)3—often obfuscate reliable assessment of the neuroretinal rim configuration and optic disc excavation. Likewise, visualization of the retinal nerve fiber layer (RNFL) is difficult in eyes with high myopia. Although optical coherence tomography (OCT) affords reproducible measurement of the RNFL thickness,4-6 detection of RNFL abnormalities in eyes with high myopia is complicated by high rates of false-positive errors,7-12 which is likely related to the lack of inclusion of individuals with high myopia in the normative databases of many OCT instruments. For example, the mean (SD) refractive error of the 271 healthy individuals included in the normative database of the Cirrus high definition (HD)-OCT (Carl Zeiss Meditec)—a spectral-domain OCT instrument—was –0.82 [1.96] D.13 The convergence of the superotemporal and/or inferotemporal RNFL bundles toward the macula in eyes with high myopia may render the RNFL measurements at the superior and/or inferior quadrants relatively abnormal with reference to the built-in normative data.14 We hypothesize that incorporating a myopic normative database in the OCT instrument for analysis of RNFL thickness would be important to decrease the frequency of false-positive errors in eyes with high myopia. We calculated the normal reference ranges of RNFL thicknesses across the circumpapillary RNFL (cRNFL) profile, as well as in the individual superpixels of the RNFL thickness map (50 × 50 superpixels), obtained with the Cirrus HD-OCT instrument in healthy individuals with high myopia. We then compared the specificity and sensitivity of the myopic normative database and the Cirrus HD-OCT built-in normative database for detection of RNFL abnormalities in a separate group of healthy individuals with high myopia and patients with high myopia and glaucoma. Methods Participants A total of 315 individuals with myopia (spherical equivalent range, –2.25 to –17.13 D) seeking corneal refractive surgery at the University Eye Center, the Chinese University of Hong Kong, were consecutively recruited from January 2, 2013, to April 30, 2015. Among the 315 individuals with myopia, 351 eyes of 196 individuals with a spherical equivalent of –6.0 D or less were considered for inclusion in the myopic normative database. A separate group of 46 eyes with high myopia (spherical equivalent, –6.0 D or less) from 27 healthy individuals (the control group) were consecutively enrolled during another period between October 1 and December 30, 2015, for evaluation of the specificities of the myopic normative database. Seventy-four eyes with high myopia (spherical equivalent, –6.0 D or less) from 50 patients with glaucoma (the glaucoma group) were enrolled from the glaucoma clinic at Hong Kong Eye Hospital for evaluation of the sensitivities of the myopic normative database. All participants received a complete ophthalmic examination with intraocular pressure measured with Goldmann applanation tonometry, central corneal thickness measured with ultrasound pachymetry, and axial length (AL) measured with partial coherence laser interferometry (IOL master, Carl Zeiss Meditec). All eyes examined in the study were phakic at the time of examination, with best-corrected visual acuity of 20/40 or more. No individual had a history of macular disease, refractive or intraocular surgery, or neurologic disease that may result in visual field (VF) abnormalities. Color optic disc stereophotographs were taken with a fundus camera (TRC-50DX, Topcon), and the RNFL was imaged by the Cirrus HD-OCT instrument. Standard automated white-on-white perimetry (Swedish Interactive Threshold Algorithm standard 24-2; Humphrey Field Analyzer II-I, Carl Zeiss Meditec) was performed in eyes with evidence of glaucomatous optic disc changes (described below) among the 351 eyes to be considered for inclusion in the myopic normative database and in all eyes in the control group (46 eyes) and the glaucoma group (74 eyes). After excluding 13 individuals with glaucomatous optic disc changes (6 had perimetric and 7 had preperimetric glaucoma) and 3 individuals with nonglaucomatous optic neuropathies (described below) in at least 1 eye, 319 eyes of 180 participants were eligible for inclusion in the myopic normative database. If both eyes were eligible, only the right eye was selected. Consequently, 180 eyes with high myopia from 180 participants were included in the myopic normative database. No eyes in the control group displayed glaucomatous optic disc changes or VF abnormalities. All eyes in the glaucoma group had perimetric glaucoma. The study was conducted in accordance with the ethical standards stated in the 1964 Declaration of Helsinki and approved by the Kowloon Central/Kowloon East Research Ethics Committee with written informed consent obtained from all participants. Diagnosis of Glaucoma Perimetric glaucoma was diagnosed based on the presence of glaucomatous optic disc changes, which included narrowed neuroretinal rim and optic disc excavation with or without visible RNFL defects in color optic disc stereophotographs evaluated by a glaucoma specialist (C.L.) together with corresponding VF abnormalities (≥3 nonedge contiguous points significant at P < .05, including ≥1 point significant at the P < .01 level on the same side of the horizontal meridian in the pattern deviation plot) in a reliable VF (fixation losses, false-negative and false-positive errors ≤20%) that were repeatable in at least 2 consecutive VF tests. Eyes with glaucomatous optic disc changes but without VF abnormalities were diagnosed as preperimetric glaucoma. Eyes exhibiting neuroretinal rim pallor and RNFL loss but without narrowed neuroretinal rim or optic disc excavation were diagnosed as nonglaucomatous optic neuropathies.15 OCT Imaging of the RNFL The Cirrus HD-OCT Optic Disc Cube scan imaged and measured the RNFL thickness in the 6 × 6–mm2 optic disc region (200 × 200 pixels). Only images with signal strength of 6 or greater and without motion artifact were included. Retinal nerve fiber layer abnormalities in the cRNFL profile (scan diameter, 3.46 mm) and in the RNFL thickness deviation map (50 × 50 superpixels) were reported in the Cirrus HD-OCT RNFL analysis printout taking reference from the built-in normative database comprising 271 healthy individuals from 4 racial/ethnic groups (Chinese, Hispanic, African descent, and European descent).13 Individual clock-hour and superpixel RNFL thicknesses below the lower 99th and 95th percentiles were encoded in red and yellow, respectively, in the circumpapillary RNFL profile and in the RNFL thickness deviation map (Figure 1). Development of the Myopic Normative Database The individual superpixel RNFL thickness of the RNFL thickness map (50 × 50 superpixels; 6 × 6 mm2) of the 180 eyes with high myopia were exported from the Cirrus HD-OCT instrument via a research browser (version 6.5.0.772; a software package for export of raw data) provided by Carl Zeiss Meditec. With the use of a custom-designed computer program (MATLAB; MathWorks, Inc), the RNFL thickness maps were centered at the optic disc and superimposed. The RNFL thicknesses at the individual superpixel coordinates were registered. The lower 95th and 99th percentile RNFL thickness values of the individual superpixel coordinates of the RNFL thickness map and the mean and clock-hour for the cRNFL profile were derived. The lower 95th and 99th percentile values represented the cutoffs below which RNFL thickness measurements were encoded in yellow and red, respectively, in the RNFL thickness deviation map and in the clock-hour for the cRNFL profile (Figure 1). Definitions of RNFL Abnormalities Six criteria including (1) mean cRNFL thickness below the lower 95th percentile and (2) the lower 99th percentile; (3) one clock-hour for cRNFL thickness or more below the lower 95th percentile and (4) the lower 99th percentile; (5) twenty contiguous superpixels or more of RNFL thickness in the RNFL thickness map below the lower 95th percentile and (6) the lower 99th percentile were evaluated. These criteria were examined because they were widely adopted in clinical practice and clinical studies to determine RNFL abnormalities. Statistical Analysis Statistical analyses were performed using Stata, version 14.0 (StataCorp). Comparisons of spherical equivalent, AL, and age between the control and glaucoma groups were performed with linear mixed modeling. The sensitivities and specificities and positive and negative predictive values for detection of RNFL abnormalities determined by the Cirrus HD-OCT (as reported in the analysis printout) and the myopic normative databases were compared with a 2-sided McNemar test and generalized score statistic, respectively. Power calculation revealed the current sample size had a power of 0.835 at an α of 0.05 to detect a difference in the discordant proportions of 0.014 (1 of 74) and 0.149 (11 of 74) between the myopic normative database and the Cirrus HD-OCT normative database in the glaucoma group and a power of 0.846 at an α of 0.05 to detect a difference in the discordant proportions of 0.022 (1 of 46) and 0.239 (11 of 46) between the myopic normative database and the Cirrus HD-OCT normative database in the control group. Results A total of 180 eyes with high myopia from 180 healthy individuals were included in the development of the myopic normative database (Table 1). All participants were Chinese. The mean (SD) spherical equivalent and AL were –8.0 (1.8) D (range, –17.1 to –6.0 D) and 26.7 (1.0) mm (range, 24.4 to 29.9 mm), respectively. The mean cRNFL thickness was 89.6 (7.2) µm (range, 70 to 110 µm), which was positively correlated with spherical equivalent (β = 1.02; P = .001) and negatively correlated with AL (β = –0.92; P = .09). The mean (SD) intraocular pressure and central corneal thickness were 13.3 (2.4) mm Hg (range, 9-21 mm Hg) and 553.4 (31.2) µm (range, 488-656 µm), respectively. Specificities and Sensitivities for Detection of cRNFL Abnormalities Another 46 eyes with high myopia from 27 healthy individuals and 74 eyes with high myopia from 50 patients with glaucoma were included for evaluation of the specificities and sensitivities of the myopic normative database and the Cirrus HD-OCT normative database for detection of RNFL abnormalities (Table 1). The mean (SD) spherical equivalent and AL did not differ between the control and glaucoma groups (control group: spherical equivalent, –8.1 [1.8] and AL, 26.6 [1.0] mm; glaucoma group: spherical equivalent, –8.3 [1.9] and AL, 26.7 [1.1] mm; P ≥ .42), although individuals in the glaucoma group were older (mean [SD] age, control group, 36.0 [12.3] years; glaucoma group, 47.9 [8.6] years; P < .001). Across all the diagnostic criteria examined, the myopic normative database outperformed the Cirrus HD-OCT normative database for detection of RNFL abnormalities in eyes with high myopia (Table 2). For example, with use of the criterion of 1 clock-hour or more cRNFL thickness below the lower 99th percentile, higher sensitivity and specificity were observed for the myopic normative database (100% and 87.0%, respectively) compared with the Cirrus HD-OCT normative database (91.9% and 56.5%, respectively; P = .01 for sensitivity and P < .001 for specificity). With use of the lower 99th percentile of the mean cRNFL thickness as a cutoff to define RNFL abnormality, high specificities were seen for both the myopic normative and the Cirrus HD-OCT databases (100%), but the sensitivity was higher for the myopic normative database (86.5%) than the Cirrus HD-OCT database (71.6%; P = .002). The myopic normative database was more sensitive than the Cirrus HD-OCT normative database for detection of eyes with early glaucoma (mean deviation, more than –6 dB) (n = 35) and all eyes with glaucoma (n = 74) using the criterion of 1 clock-hour or more for cRNFL thickness below the lower 99th percentile (early glaucoma: myopic normative database, 100%; Cirrus HD-OCT normative database, 88.6%; P = .046; all glaucoma: myopic normative database, 100%; Cirrus HD-OCT database, 91.9%; P = .01) and the criterion of the mean cRNFL thickness below the lower 99th percentile (early glaucoma: myopic normative database, 77.1%; Cirrus HD-OCT database, 54.3%; P = .01; all glaucoma: myopic normative database, 86.5%; Cirrus HD-OCT database, 71.6%; P = .002). When the clock-hour and mean cRNFL abnormality criteria were defined with reference to the lower 95th percentile values, the myopic normative database showed higher specificities (63.0% and 100%, respectively) than did the Cirrus HD-OCT normative database (30.4% [P = .001] and 87.0% [P = .01], respectively) at comparable sensitivities (P ≥ .08). Specificities and Sensitivities for Detection of RNFL Abnormalities in the RNFL Thickness Map When RNFL abnormalities were defined with reference to 20 superpixels or more of RNFL thickness below the lower 99th percentiles in the RNFL thickness deviation map, the myopic normative database showed a higher specificity (89.1%) than did the Cirrus HD-OCT normative database (37.0%) (P < .001) at similar sensitivities (94.6% and 98.7%, respectively; P = .18). Similar findings were observed when the criterion of the 95th percentile was applied (Table 2). Figure 2 shows the distribution maps for frequency of RNFL abnormalities of the control group (ie, false-positive detection) constructed by overlaying their RNFL thickness deviation maps with reference to the lower 99th percentiles. Retinal nerve fiber layer abnormalities were located largely at the inferior and the nasal quadrants followed by the superior quadrant when the Cirrus HD-OCT normative database was applied (Figure 2A). By contrast, superpixels of RNFL abnormalities appeared to be randomly distributed when the myopic normative database was applied (Figure 2B). Positive and Negative Predictive Values The positive predictive values of the myopic normative database were higher (81.3%-100%) than those of the Cirrus HD-OCT normative database (63.8%-91.6%) except for the criterion of mean cRNFL thickness below the lower 99th percentile, in which both normative databases had a positive predictive value of 100% (Table 3). The negative predictive values were largely comparable between the normative databases, although the myopic normative database exhibited higher negative predictive values for the criteria based on the mean cRNFL thickness below the lower 95th and the lower 99th percentile (myopic normative database, 88.5%; Cirrus HD-OCT normative database, 81.6%; P = .03 for the lower 95th percentile; myopic normative database, 82.1%; Cirrus HD-OCT normative database, 68.7%; P = .001 for the lower 99th percentile). Discussion We demonstrated that integrating a myopic normative database for analysis of RNFL thickness is relevant for detection of RNFL abnormalities in eyes with high myopia. Using different criteria to define RNFL abnormalities in the cRNFL profile and in the RNFL thickness map, the myopic normative database always showed a higher specificity (63.0%-100%) than did the Cirrus HD-OCT built-in normative database (8.7%-87.0%) at similar sensitivities for detection of RNFL abnormalities in eyes with high myopia, except for the criterion of mean RNFL thickness below the lower 99th percentile, in which both normative databases showed a specificity of 100%. Our finding underscores the importance of incorporating a myopic normative database in OCT instruments for evaluation of RNFL measurements in individuals with high myopia. Optical coherence tomography RNFL measurements are generally smaller in eyes with high myopia compared with the healthy population. For instance, the mean (SD) cRNFL thickness of the myopic normative database was 89.6 (7.2) µm, whereas it was 97.2 (10.5) µm in a population-based study in healthy Chinese individuals with a mean spherical equivalent of –0.39 D using the same OCT instrument and scanning protocol.16 The smaller RNFL measurements in eyes with high myopia may in part contribute to an increase in false-positive errors when a normative database without data on eyes with high myopia is applied for analysis of RNFL thickness. In our study, 43.5% and 69.6% of eyes with high myopia in healthy individuals had false-positive errors detected by the Cirrus HD-OCT normative database when the criteria of RNFL abnormalities were based on 1 clock-hour or more of cRNFL thicknesses below the lower 99th and 95th percentiles, respectively (Table 2). False-positive errors were more obvious in the analysis of the RNFL thickness map, in which 63.0% and 91.3% of eyes with high myopia in healthy individuals had at least 20 contiguous superpixels of RNFL thickness below the lower 99th and 95th percentiles, respectively. As shown in the distribution map of the frequency of RNFL abnormalities (Figure 2A), the inferior and nasal RNFL measurements are more likely to be rendered abnormal by the Cirrus HD-OCT normative database. Although the nasal RNFL measurements are not typically affected in eyes with early and moderate glaucoma, the high frequency of false-positive errors at the inferior quadrant has weakened the diagnostic performance of OCT to detect RNFL abnormalities in eyes with high myopia. The myopic normative database (n = 180) differs from the Cirrus HD-OCT built-in normative database (n = 271) because it has eyes with a longer mean (SD) AL (26.7 [1.0] vs 23.9 [1.0] mm, respectively) and a more negative mean (SD) spherical equivalent (–8.0 [1.8] vs –0.8 [2.0] D, respectively).13 We were not able to compare the measurements of RNFL thickness between the normative databases because the Cirrus HD-OCT normative database was proprietary. The effect of applying the myopic normative database for analysis of RNFL thickness in eyes with high myopia is signified by the decreases in false-positive errors in analysis of both the cRNFL profile and the RNFL thickness map (Table 2). The improvement in specificities did not come at the cost of a reduction in sensitivity for detection of glaucoma. In fact, an improvement in sensitivity was observed when RNFL abnormalities were defined using the criterion of 1 clock-hour or more of cRNFL thickness below the lower 99th percentile and the criterion of the mean cRNFL thickness below the lower 99th percentile. Although the myopic normative database has considerably improved the specificity for detection of RNFL abnormalities in eyes with high myopia, 13.0% and 10.9% of healthy high myopic eyes remained false positives for the criteria of the circumpapillary clock hour (≥1 abnormal clock hour of RNFL thickness) and the RNFL thickness deviation map (≥20 superpixels) using the lower 99th percentile cutoffs, respectively. The fact that the criteria for detection of RNFL abnormalities in eyes with high myopia have not been optimized and that the influence of the orientation of the fovea relative to the Bruch membrane opening has not been considered might have negatively influenced the diagnostic performance of the myopic normative database.17,18 There are other limitations of the study. First, the application of the myopic normative data was not age-matched because the current sample size may not be sufficient to derive reliable RNFL thickness cutoff estimates at specific age ranges. Patients in the glaucoma group were older (mean [SD] age, 47.9 [8.6] years) than individuals included in the myopic normative database (37.5 [9.0] years) and those in the control group (36.0 [12.3] years). Had age matching been performed in the analysis of RNFL thickness using by the myopic normative database, the sensitivity for detection of RNFL abnormalities in the glaucoma group could have been enhanced (older individuals have thinner RNFL19). Second, the Cirrus HD-OCT database did not match race/ethnicity in the analysis of RNFL thickness. We contributed 63 healthy Chinese individuals to the development of the Cirrus HD-OCT normative database but the database also contained 208 healthy individuals from 3 other racial/ethnic groups (51 of African descent, 63 of European descent, and 35 of Hispanic descent), and the analysis of RNFL thickness in the Cirrus HD-OCT did not take racial/ethnic differences in RNFL thickness into consideration.13 Third, the Cirrus HD-OCT did not correct for ocular magnification for RNFL measurements. For example, the actual circumpapillary scan diameter would be greater than 3.46 mm for eyes with an AL longer than 24.46 mm and the relative increase in the scan diameter can underestimate the cRNFL thicknesses. Fourth, our analysis included only eyes with high myopia, as false-positive errors are more frequently encountered in eyes with high myopia than in those with mild to moderate myopia.7-12 Detecting RNFL abnormalities is more difficult in eyes with high myopia than in those with mild or moderate myopia. Finally, central corneal thickness of the myopic normative database was not small (mean [SD], 550.0 [37.0] µm), as what would have been expected in eyes with high myopia. Nevertheless, among eyes of Chinese individuals with myopia, central corneal thickness has been shown to distribute across a wide range and did not correlate with the degree of myopia.20 Conclusions Our study provides data supporting the application of a myopic normative database to improve the specificity for detection of glaucomatous RNFL abnormalities in eyes with high myopia. To our knowledge, none of the currently available OCT instruments incorporates a specific normative database collected from individuals with high myopia for analysis of RNFL thickness, although the retina scan–OCT (Nidek Co, Ltd) has a normative database for macula map analysis including eyes of Asian individuals with AL between 26 and 29 mm.21 With a high prevalence of myopia in Asia, there is an unmet need for implementation of myopic normative databases in OCT instruments for analysis of glaucoma. Back to top Article Information Correction: This article was corrected on September 22, 2016, to fix the Conflict of Interest Disclosures section. Accepted for Publication: May 27, 2016. Corresponding Author: Christopher K. S. Leung, MD, Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, People’s Republic of China (tlims00@hotmail.com). Published Online: July 21, 2016. doi:10.1001/jamaophthalmol.2016.2343 Author Contributions: Dr Leung and Mr Biswas had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Mrs Biswas and Chen contributed equally to the article. Study concept and design: Leung. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: All authors. Critical revision of the manuscript for important intellectual content: Biswas, Leung. Statistical analysis: All authors. Administrative, technical, or material support: Lin, Leung. Study supervision: Leung. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Leung reported receiving speaker honorarium and research support from Carl Zeiss Meditec. No other disclosures were reported. References 1. Chang RT, Singh K. Myopia and glaucoma: diagnostic and therapeutic challenges. Curr Opin Ophthalmol. 2013;24(2):96-101.PubMedGoogle ScholarCrossref 2. Hsu CH, Chen RI, Lin SC. Myopia and glaucoma: sorting out the difference. Curr Opin Ophthalmol. 2015;26(2):90-95.PubMedGoogle ScholarCrossref 3. Chang L, Pan CW, Ohno-Matsui K, et al. Myopia-related fundus changes in Singapore adults with high myopia. Am J Ophthalmol. 2013;155(6):991-999.e1.PubMedGoogle ScholarCrossref 4. Leung CK, Cheung CY, Weinreb RN, et al. Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: a variability and diagnostic performance study. Ophthalmology. 2009;116(7):1257-1263, 1263.e1-1263.e2.PubMedGoogle ScholarCrossref 5. Kim JS, Ishikawa H, Sung KR, et al. Retinal nerve fibre layer thickness measurement reproducibility improved with spectral domain optical coherence tomography. Br J Ophthalmol. 2009;93(8):1057-1063.PubMedGoogle ScholarCrossref 6. Mwanza JC, Gendy MG, Feuer WJ, Shi W, Budenz DL. Effects of changing operators and instruments on time-domain and spectral-domain OCT measurements of retinal nerve fiber layer thickness. Ophthalmic Surg Lasers Imaging. 2011;42(4):328-337.PubMedGoogle ScholarCrossref 7. Leung CK, Mohamed S, Leung KS, et al. Retinal nerve fiber layer measurements in myopia: an optical coherence tomography study. Invest Ophthalmol Vis Sci. 2006;47(12):5171-5176.PubMedGoogle ScholarCrossref 8. Vernon SA, Rotchford AP, Negi A, Ryatt S, Tattersal C. Peripapillary retinal nerve fibre layer thickness in highly myopic Caucasians as measured by Stratus optical coherence tomography. Br J Ophthalmol. 2008;92(8):1076-1080.PubMedGoogle ScholarCrossref 9. Aref AA, Sayyad FE, Mwanza JC, Feuer WJ, Budenz DL. Diagnostic specificities of retinal nerve fiber layer, optic nerve head, and macular ganglion cell-inner plexiform layer measurements in myopic eyes. J Glaucoma. 2014;23(8):487-493.PubMedGoogle ScholarCrossref 10. Leal-Fonseca M, Rebolleda G, Oblanca N, Moreno-Montañes J, Muñoz-Negrete FJ. A comparison of false positives in retinal nerve fiber layer, optic nerve head and macular ganglion cell-inner plexiform layer from two spectral-domain optical coherence tomography devices. Graefes Arch Clin Exp Ophthalmol. 2014;252(2):321-330.PubMedGoogle ScholarCrossref 11. Yamashita T, Kii Y, Tanaka M, et al. Relationship between supernormal sectors of retinal nerve fibre layer and axial length in normal eyes. Acta Ophthalmol. 2014;92(6):e481-e487.PubMedGoogle ScholarCrossref 12. Kim KE, Jeoung JW, Park KH, Kim DM, Kim SH. Diagnostic classification of macular ganglion cell and retinal nerve fiber layer analysis: differentiation of false-positives from glaucoma. Ophthalmology. 2015;122(3):502-510.PubMedGoogle ScholarCrossref 13. Knight OJ, Girkin CA, Budenz DL, Durbin MK, Feuer WJ; Cirrus OCT Normative Database Study Group. Effect of race, age, and axial length on optic nerve head parameters and retinal nerve fiber layer thickness measured by Cirrus HD-OCT. Arch Ophthalmol. 2012;130(3):312-318.PubMedGoogle ScholarCrossref 14. Leung CK, Yu M, Weinreb RN, et al. Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: interpreting the RNFL maps in healthy myopic eyes. Invest Ophthalmol Vis Sci. 2012;53(11):7194-7200.PubMedGoogle ScholarCrossref 15. Greenfield DS, Siatkowski RM, Glaser JS, Schatz NJ, Parrish RK II. The cupped disc: who needs neuroimaging? Ophthalmology. 1998;105(10):1866-1874.PubMedGoogle ScholarCrossref 16. Tun TA, Sun CH, Baskaran M, et al. Determinants of optical coherence tomography-derived minimum neuroretinal rim width in a normal Chinese population. Invest Ophthalmol Vis Sci. 2015;56(5):3337-3344.PubMedGoogle ScholarCrossref 17. Chauhan BC, Burgoyne CF. From clinical examination of the optic disc to clinical assessment of the optic nerve head: a paradigm change. Am J Ophthalmol. 2013;156(2):218-227.e2.PubMedGoogle ScholarCrossref 18. He L, Ren R, Yang H, et al. Anatomic vs. acquired image frame discordance in spectral domain optical coherence tomography minimum rim measurements. PLoS One. 2014;9(3):e92225.PubMedGoogle ScholarCrossref 19. Leung CK, Yu M, Weinreb RN, et al. Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: a prospective analysis of age-related loss. Ophthalmology. 2012;119(4):731-737.PubMedGoogle ScholarCrossref 20. Fam HB, How AC, Baskaran M, Lim KL, Chan YH, Aung T. Central corneal thickness and its relationship to myopia in Chinese adults. Br J Ophthalmol. 2006;90(12):1451-1453.PubMedGoogle ScholarCrossref 21. Nakanishi H, Akagi T, Hangai M, et al. Sensitivity and specificity for detecting early glaucoma in eyes with high myopia from normative database of macular ganglion cell complex thickness obtained from normal non-myopic or highly myopic Asian eyes. Graefes Arch Clin Exp Ophthalmol. 2015;253(7):1143-1152.PubMedGoogle ScholarCrossref
TI - Evaluation of a Myopic Normative Database for Analysis of Retinal Nerve Fiber Layer Thickness
JF - JAMA Ophthalmology
DO - 10.1001/jamaophthalmol.2016.2343
DA - 2016-09-01
UR - https://www.deepdyve.com/lp/american-medical-association/evaluation-of-a-myopic-normative-database-for-analysis-of-retinal-UwnCkhoStT
SP - 1032
EP - 1039
VL - 134
IS - 9
DP - DeepDyve
ER -