April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Correlation Between AOSLO and SDOCT Photoreceptor Metrics in Macular Disease
Author Affiliations & Notes
  • Evan Lyall
    Vision Science,
    Bioengineering,
    University of California, Berkeley, Berkeley, California
  • Austin Roorda
    Vision Science,
    University of California, Berkeley, Berkeley, California
  • Jacque L. Duncan
    Ophthalmology, UCSF, San Francisco, California
  • Steven D. Schwartz
    Ophthalmology, Jules Stein Eye Inst/UCLA, Los Angeles, California
  • Kavitha Ratnam
    Ophthalmology, UCSF, San Francisco, California
  • Sanna Sundquist
    Ophthalmology, UCSF, San Francisco, California
  • Anna S. Solovyev
    Ophthalmology, UCSF, San Francisco, California
  • Brandon J. Lujan
    Vision Science,
    University of California, Berkeley, Berkeley, California
    West Coast Retina Medical Group, San Francisco, California
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 6571. doi:
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    • Get Citation

      Evan Lyall, Austin Roorda, Jacque L. Duncan, Steven D. Schwartz, Kavitha Ratnam, Sanna Sundquist, Anna S. Solovyev, Brandon J. Lujan; Correlation Between AOSLO and SDOCT Photoreceptor Metrics in Macular Disease. Invest. Ophthalmol. Vis. Sci. 2011;52(14):6571.

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

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Abstract
 
Purpose:
 

Disruption of the inner-segment/outer segment (IS/OS) junction on Spectral Domain Optical Coherence Tomography (SDOCT) images is used clinically as an indicator of loss or damage to macular photoreceptors. We sought to validate this interpretation by comparing cones visualized with AOSLO with registered en face SDOCT photoreceptor slab images.

 
Methods:
 

Patients with MacTel, AMD, and Best’s vitelliform dystrophy were imaged at multiple time points using SDOCT and AOSLO. AOSLO images were processed and registered to clinical images. Individual high quality AOSLO frames were selected such that well-resolved cone mosaics and regions of non-resolved cones were selected and individual cones were labeled. The individual cone photoreceptors and No Cone Regions (NCRs) were then labeled in these frames. En face IS/OS reflectivity slab images were created using an automated RPE segmentation (CZMI) and were registered to clinical images independently.

 
Results:
 

Regions where there is significantly decreased pixel intensity in the IS/OS slab images fit entirely within the NCRs seen with AOSLO. However, cone mosaics are sometimes not visible in AOSLO images where there appears to be an intact IS/OS junction on SDOCT. Regions of disagreement between AOSLO and SDOCT are discrete and in some situations follow the same border pattern (image). Data processed quantitatively by the use of a receiver operating characteristic (ROC) metric between the NCR and the SDOCT IS/OS data demonstrates the sensitivity and specificity between the modalities when defining high quality AOSLO locations as the gold standard.

 
Conclusions:
 

The strongest correlations exist between AOSLO NCRs and absent IS/OS slab intensity. One possible explanation for this is that structurally intact photoreceptors which can be visualized by SDOCT IS/OS slabs may not waveguide properly and thus not be visible on AOSLO.  

 
Keywords: imaging/image analysis: clinical • retina • anatomy 
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