April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Reproducibility of Retinal Blood Flow Measurements Derived from Semi-Automated Doppler OCT Analysis
Author Affiliations & Notes
  • Ranjith k. konduru
    Ophthalmology, Doheny Eye Institute, Los Angeles, California
  • Ou Tan
    Ophthalmology, Casey Eye Institute, Portland, Oregon
  • Muneeswar G. Nittala
    Ophthalmology, Doheny Eye Institute, Los Angeles, California
  • Srinivas R. Sadda
    Ophthalmology, Doheny Eye Institute, Los Angeles, California
  • David Huang
    Ophthalmology, Casey Eye Institute, Portland, Oregon
  • Footnotes
    Commercial Relationships  Ranjith K. konduru, None; Ou Tan, Optovue Inc. (F); Muneeswar G. Nittala, None; Srinivas R. Sadda, Heidelberg Engineering. (C), Optovue Inc., Carl Zeiss Meditec. (F), Topcon Medical Systems. (P); David Huang, Carl Zeiss Meditec. (P), Optovue Inc. (F, I, C, R)
  • Footnotes
    Support  NIH R01 EY013516
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 1710. doi:https://doi.org/
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    • Get Citation

      Ranjith k. konduru, Ou Tan, Muneeswar G. Nittala, Srinivas R. Sadda, David Huang; Reproducibility of Retinal Blood Flow Measurements Derived from Semi-Automated Doppler OCT Analysis. Invest. Ophthalmol. Vis. Sci. 2011;52(14):1710. doi: https://doi.org/.

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

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Abstract
 
Purpose:
 

To evaluate the reproducibility and inter-grader agreement of total retinal blood flow (TRBF) measurements obtained by semi-automated grading of Doppler Spectral Domain OCT (SD-OCT) scans.

 
Methods:
 

Doppler OCT scans from 20 eyes of 20 subjects were obtained using a circumpapillary dual circular scan protocol on the Optovue RTVue SD-OCT. These scans were analyzed using the Doppler OCT of Retinal Circulation (DOCTORC) software (version2) which automatically identifies candidate vessel locations. Human graders can then manually refine and correct the scans by adding or deleting vessels, changing vessel boundaries and identifying the vessels as veins or arteries. After this manual step, the software then calculates the venous blood flow (and hence TRBF) automatically using the Doppler signal and the vessel area. In this study, two masked graders independently refined the retinal vessel detections, and the agreement in TRBF values generated by the two graders was analyzed using SPSS software.

 
Results:
 

Mean (± SD, Max) TRBF of the subjects in this series was 38.49 µl/min (± 10.84, 57.14) for grader 1 and 39.04 µl/min (± 10.65, 57.14) for grader 2, with an intra-class correlation coefficient of 0.933 and a coefficient of variability of 0.96. Bland-Altman Plot (Figure 1) illustrates the agreement between graders. Limits of agreement were -11.1 and +10.0. Venous area measurements showed similar levels of agreement with a mean (± SD, Max) area of 47.27 mm2 (± 8.35, 61.01) for grader 1 and 50.18 mm2 (± 8.74, 67.84) for grader 2, with an intra-class correlation coefficient of 0.933.

 
Conclusions:
 

Using semi-automated software with manual refinement, reproducible measurements of TRBF can be obtained from Doppler OCT data. These findings should be of value in future studies evaluating retinal blood flow in various diseases.  

 
Keywords: imaging/image analysis: non-clinical • image processing 
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