June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Intersubject correlation between circumpapillary distribution of retinal nerve fiber layer and retinal vessels: comparison between optical coherence tomography and scanning laser polarimetry
Author Affiliations & Notes
  • Ivania Pereira
    Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
  • Stephan Holzer
    Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
  • Hemma Resch
    Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
  • Barbara Kiss
    Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
  • Georg Fischer
    Center for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management and Imaging, Medical University Vienna, Vienna, Austria
  • Clemens Vass
    Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 4800. doi:
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      Ivania Pereira, Stephan Holzer, Hemma Resch, Barbara Kiss, Georg Fischer, Clemens Vass; Intersubject correlation between circumpapillary distribution of retinal nerve fiber layer and retinal vessels: comparison between optical coherence tomography and scanning laser polarimetry. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4800.

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

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Abstract

Purpose: To assess circumpapillary retinal vessel thickness (cRVT) profiles and correlate them with retinal nerve fiber layer (RNFL) thickness measured by high resolution optical coherence tomography (HR-OCT) and scanning laser polarimetry (SLP).

Methods: A sample of 106 healthy volunteers underwent complete ophthalmologic examination, including HR-OCT scanning (Cirrus® Carl Zeiss Meditec Inc.) and SLP (GDx-VCC® and GDx-ECC ® Carl Zeiss Meditec Inc.). A proprietary software was developed in MATLAB® (Version R2009b, The Mathworks Inc.) for individual manual assessment of the optic disc (OD) border and cRVT, using the SLO image from Cirrus HR-OCT centered in the OD. For each measurable vessel, we established a line connecting its center point at the OD border with the OD center. The angle between this line and a horizontal line passing through OD center was determined. Individual cRVT measurements were convoluted with a Gaussian window, generating a cRVT profile dependent on the number of sectors measured in each device (256 sectors for HR-OCT or 64 sectors for both GDxVCC and GDxECC). Intersubject variability was determined using MATLAB.

Results: The median values for intersubject correlation between cRVT and RNFL thickness and the numbers of significant sectors as measured with Cirrus HR-OCT, GDx-ECC and GDx-VCC were 0.255 (186/256 sectors statistically significant), 0.192 (32/64) and 0.195 (33/64). 90% percentiles of the intersubject correlation were 0.400, 0.355 and 0.336, respectively.

Conclusions: Both SLP methods (GDx-VCC and GDx-ECC) yield comparable results regarding the intersubject correlation of the cRVT profile and the RNFL with about 50% of the sectors showing significant correlation. However, regarding the HR-OCT, our data showed a tendency towards a better correlation which was statistically significant in 70% of the sectors. Based on our results, up to 25% of the interindividual variation of the RNFL thickness might be explained by the variation of the cRVT.

Keywords: 610 nerve fiber layer • 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • 550 imaging/image analysis: clinical  
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