March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Flow Quantification in Small Macular Vessels via Frame Averaging with Doppler Optical Coherence Tomography
Author Affiliations & Notes
  • Jason M. Tokayer
    Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California
  • Ou Tan
    Casey Eye Institute, Oregon Health and Science University, Portand, Oregon
  • David Huang
    Casey Eye Institute, Oregon Health and Science University, Portand, Oregon
  • Footnotes
    Commercial Relationships  Jason M. Tokayer, None; Ou Tan, Optovue Inc. (F); David Huang, Carl Zeiss Meditec Inc. (P), Optovue Inc. (F, I, C, R)
  • Footnotes
    Support  NIH R01 EY013516
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 2176. doi:
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    • Get Citation

      Jason M. Tokayer, Ou Tan, David Huang; Flow Quantification in Small Macular Vessels via Frame Averaging with Doppler Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2012;53(14):2176.

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

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Abstract
 
Purpose:
 

To measure flow in small macular vessels using Doppler Fourier-domain optical coherence tomography (FD-OCT).

 
Methods:
 

Normal eyes were scanned using the RTVue FD-OCT system (Optovue, Inc. Fremont, CA). A double circle scanning protocol (DCSP) centered at the fovea was used with diameters 1.9 mm and 2.2 mm, respectively. Blood vessel imprints in the ganglion cell layer are enhanced after high-pass filtering each complex OCT frame and axial summation of the intensity in this layer enables identification of the transverse positions of the vessels. Vessels in each frame are matched to nearby vessels in the other frames with the same circle diameter. The vessels are then aligned using a non-linear least squares registration algorithm that exploits the circular nature of the scans. Frame registration enables averaging of the Doppler frequency shifts which are computed using the phase-resolved (PR) algorithm. The PR algorithm is used here because high-pass filtering has been shown to distort velocity estimates. Doppler angles are calculated by matching vessels on the averaged images of each ring. Vessel diameters and flow are then computed.

 
Results:
 

The PR method generally fails to illustrate a clear image for small macular vessels due both to small Doppler phase shifts as well as near-perpendicular incidence. Frame averaging helps to alleviate this problem by significantly reducing phase noise (see attached image). Using the frame averaged Doppler images we compute flow in the three small vessels in the image. The vessel diameters are 47.7, 48.1 and 34.7 microns, respectively, and the respective flow rates are -0.83, 0.31 and -0.65 microliters per minute.

 
Conclusions:
 

Frame averaging can be used to quantify small retinal vessels in the macula by reducing the phase noise floor. This may provide a method for calculating total macular blood flow if it can be extended with automatic vessel detection.  

 
Keywords: image processing • macula/fovea 
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