Autor: |
Firdaus, Salma, Pereira, Lívia Figueiredo, Yang, Ge, Huang-Link, Yumin |
Předmět: |
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Zdroj: |
Clinical Ophthalmology; Aug2024, Vol. 18, p2397-2406, 10p |
Abstrakt: |
Purpose: To compare the interocular symmetry and investigate the intermachine reproducibility of optic disc and macular data measured by spectral-domain high-definition optical coherence tomography (HD-OCT) Cirrus HD-OCT 4000 and HD-OCT 5000 from healthy subjects. Patients and Methods: Forty-three volunteers were examined with both HD-OCT 4000 and HD-OCT 5000 at the same visit. Optic nerve head (ONH) and macular data were acquired using ONH Cube 200× 200 scans and macular volume cube 512× 128 scans, respectively. Results: The average age of the participants was 33 ± 8.6 years. Interocular OCT parameters of ONH and macula showed a high correlation between the right and left eyes regardless of HD-OCT models, displaying a low coefficient of variation (CV). However, the average retinal nerve fiber layer (RNFL) was thicker (96.67± 11.19μm vs 95.3± 10.89μm, p< 0.01), and the average central subfield thickness (261.51± 17.45μm vs 262.51± 17.39 μm, p< 0.01) and cube average thickness (283.91± 13.59μm vs 286.55± 13.09μm, p< 0.05) were thinner when measured by Cirrus 4000 compared to 5000. Intermachine reproducibility and reliability of RNFL and macular parameters exhibited a high intraclass correlation coefficient (ICC) (0.985) and low CV (2.4%). Ganglion cell-inner plexiform layer (GCIPL) measured by two OCT models showed similar values with an average thickness of 85 μm and had high intermachine reproducibility with high ICC (0.993) and low CV (1.2%). Conclusion: High interocular symmetry was observed across both HD-OCT models. Intermachine reproducibility for RNFL and all macular parameters was also high. GCIPL showed minimal intermachine differences with high reproducibility and reliability. Thus, the results imply that GCIPL values measured by two Cirrus OCT models may be used interchangeably. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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