June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Volumes of retinal layers measured by spectral-domain optical coherence tomography and public domain software ImageJ
Author Affiliations & Notes
  • Albert Caramoy
    Department of Ophthalmology, University of Cologne, Cologne, Germany
  • Katharina Droge
    Department of Ophthalmology, University of Cologne, Cologne, Germany
  • Bernd Kirchhof
    Department of Ophthalmology, University of Cologne, Cologne, Germany
  • Carel Hoyng
    Department of Ophthalmology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
  • Sascha Fauser
    Department of Ophthalmology, University of Cologne, Cologne, Germany
  • Footnotes
    Commercial Relationships Albert Caramoy, Bausch & Lomb (F), Fluoron GmbH (F), Alamedics GmbH&Co. KG (F); Katharina Droge, None; Bernd Kirchhof, None; Carel Hoyng, None; Sascha Fauser, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 5538. doi:https://doi.org/
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      Albert Caramoy, Katharina Droge, Bernd Kirchhof, Carel Hoyng, Sascha Fauser; Volumes of retinal layers measured by spectral-domain optical coherence tomography and public domain software ImageJ. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5538. doi: https://doi.org/.

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

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Abstract

Purpose: To study inter- and intraindividual variability in volume of retinal layers in subjects over 60 years-of-age without macular pathology.

Methods: In fifty randomly chosen individuals without macular pathology from the Eugenda (European Genetic Database) spectral domain optical coherence tomography was performed (HRA Spectralis+OCT, Heidelberg Engineering, Heidelberg, Germany). The following retinal layers were delineated manually and volumes calculated using the ImageJ software (developed by Wayne Rasband, NIH, Bethesda, Maryland, USA): RNFL=retinal nerve fiber layer, GCLIPL=ganglion cell layer and inner plexiform layer, INL=inner nuclear layer, OPLONLPIS=outer plexiform, outer nuclear, Henle’s fiber layer and inner part of the photoreceptor layers, POSRPEBM=outer part of the photoreceptor layer, retinal pigment epithelium and Bruch’s membrane. In 20 eyes of 10 subjects the measurements were done twice to evaluate the test-retest reliability of the ImageJ measurement algorithm.

Results: Mean age was 67 ± 5 years. Twenty-one men and 29 women were analyzed. Mean volumes of the retinal layers were RNFL=0.291±0.023 mm3, GCLIPL=0.742±0.057 mm3, INL=0.310±0.024 mm3, OPLONLPIS=1.105±0.069 mm3, POSRPEBM=0.647±0.028 mm3. There was a moderate to high concordance for all retinal layers between the right and the left eyes (RNFL r=0.734, p<0.001; GCLIPL r=0.918, p<0.001; INL r=0.759, p<0.001; OPLONLPIS r=0.946, p<0.001; POSRPEBM r=0.855, p<0.001). In the test-retest reliability testing there was a correlation between the volume of two different measurements (RNFL r=0.905, p<0.001; GCLIPL r=0.966, p<0.001, INL r=0.808, p<0.05; OPLONLPIS r=0.999, p<0.001; POSRPEBM r=0.870, p<0.05). The concurrent validity showed a high correlation between macular volume measured using ImageJ and Heidelberg Eye Explorer software (right eye r=0.961, p<0.001; left eye r=0.969, p<0.001).

Conclusions: We developed an algorithm to measure retinal layers using public domain software ImageJ. Overall there is a good reliability and validity of the algorithm used. In this study we described the normal value of measured retinal layers.

Keywords: 688 retina • 550 imaging/image analysis: clinical  
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