April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Factors Influencing Measurement of SD-OCT Minimum Rim Width (MRW),Correlation with Retinal Nerve Fiber Layer Thickness and Functional Measurements in Glaucoma
Author Affiliations & Notes
  • Nila Cirineo
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
  • Navid Amini
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
    UCLA Wireless Health Institute, Los Angeles, CA
  • Sara Nowroozizadeh
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
  • Sharon A Henry
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
  • Joseph Caprioli
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
  • Kouros Nouri-Mahdavi
    Glaucoma, Jules Stein Eye Institute, Los Angeles, CA
  • Footnotes
    Commercial Relationships Nila Cirineo, None; Navid Amini, None; Sara Nowroozizadeh, None; Sharon Henry, None; Joseph Caprioli, None; Kouros Nouri-Mahdavi, Allergan (C)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 4746. doi:https://doi.org/
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      Nila Cirineo, Navid Amini, Sara Nowroozizadeh, Sharon A Henry, Joseph Caprioli, Kouros Nouri-Mahdavi; Factors Influencing Measurement of SD-OCT Minimum Rim Width (MRW),Correlation with Retinal Nerve Fiber Layer Thickness and Functional Measurements in Glaucoma. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4746. doi: https://doi.org/.

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

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Abstract

Purpose: To determine factors affecting the accuracy of MRW measurements and explore its correlation with retinal nerve fiber layer (RNFL) thickness and functional measurements in glaucoma.

Methods: 124 glaucoma eyes (73 subjects) were prospectively recruited. Enrolled eyes were required to have RNFL and optic nerve head (ONH) images (EDI or non-EDI images) with Spectralis SD-OCT. ONH images consisted of 24 radial scans centered on the ONH (768 scans, 6mm). The tip of Bruch's membrane (BM) was marked by an experienced observer. MRW was calculated as the minimum distance between the BM tip and the vitreous-ILM boundary in MATLAB. Images where the tip of the BM could not be detected or the automated MRW measurement method failed were excluded. Parametric and nonparametric correlations were explored between MRW and RNFL thickness measurements, and both of these parameters vs. average loss on Garway-Heath visual field (VF) clusters.

Results: Reasons for exclusion were inadequate visibility of the BM tip commonly due to overlying vessels, vitreous-ILM not detectable especially on EDI images, or failure of MRW detection algorithm mostly caused by bean-pot shaped cupping. Final analyses are reported for 43 eyes of 32 subjects. The correlation coefficients between MRW and RNFL thickness varied between 0.287 (p=0.063, temporal sector) to 0.575 (p<0.001, inferotemporal sector). The structure-function correlations were significantly stronger (p<0.05) for RNFL than MRW for temporal (rho=0.403 vs. 0.132), inferotemporal (rho=0.614 vs. 0.309 for correlation with superior peripheral cluster, and 0.791 vs. 0.325 for correlation with superior mid-peripheral cluster) and superotemporal (rho=0.675 vs. 0.388 for inferior peripheral cluster and 0.747 vs. 0.472 for inferior mid-peripheral cluster) sectors, whereas MRW sectors showed stronger relationships with VF measurements in inferonasal (rho= 0.128 vs. 0.367 for superior peripheral cluster and 0.279 vs. 0.405 for superior mid-peripheral cluster), and superonasal sectors (0.416 vs. 0.622 for inferior mid-peripheral cluster, 0.444 vs. 0.469 for inferior peripheral cluster).

Conclusions: Factors affecting accurate MRW measurement include SD-OCT location of blood vessels, zero-delay line setting, and cup topography. Comparative performance of MRW and RNFL thickness measurements varies with position around the ONH.

Keywords: 550 imaging/image analysis: clinical • 438 Bruch's membrane • 496 detection  
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