Investigative Ophthalmology & Visual Science Cover Image for Volume 59, Issue 9
July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Enhanced quantification of retinal perfusion by improved discrimination of blood flow from bulk motion signal in OCTA
Author Affiliations & Notes
  • Acner Camino
    OHSU, Portland, Oregon, United States
  • Yali Jia
    OHSU, Portland, Oregon, United States
  • Miao Zhang
    Optovue, Fremont, California, United States
  • Liang Liu
    OHSU, Portland, Oregon, United States
  • JIE WANG
    OHSU, Portland, Oregon, United States
  • David Huang
    OHSU, Portland, Oregon, United States
  • Footnotes
    Commercial Relationships   Acner Camino, None; Yali Jia, Optovue (P), Optovue (F); Miao Zhang, Optovue (E); Liang Liu, None; JIE WANG, None; David Huang, Optovue (F), Optovue (I), Optovue (P), Optovue (R)
  • Footnotes
    Support  This work was supported by grants R01EY027833, DP3 DK104397, R01 EY024544, R01 EY023285, P30 EY010572 from the National Institutes of Health (Bethesda, MD), and by and William & Mary Greve Special Scholar Award and unrestricted departmental funding from Research to Prevent Blindness (New York, NY).
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 2853. doi:
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      Acner Camino, Yali Jia, Miao Zhang, Liang Liu, JIE WANG, David Huang; Enhanced quantification of retinal perfusion by improved discrimination of blood flow from bulk motion signal in OCTA. Invest. Ophthalmol. Vis. Sci. 2018;59(9):2853.

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

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Abstract

Purpose : We have previously developed a regression-based bulk-motion subtraction (BMS) algorithm using a prototype swept-source optical coherence tomography angiography (OCTA) system. The algorithm estimates bulk motion velocity between consecutive B-scans and corrects for its effect on flow signal. Here, we aim to investigate its ability to improve the quantification of capillary density (CD) on two commercial OCT systems.

Methods : 6×6 mm macular OCTA scans were acquired by two spectral-domain systems (70-kHz Avanti/AngioVue and 68-kHz Cirrus/AngioPlex). The BMS algorithm was applied on each OCTA volume. Regression analysis of angiographic vs. reflectance signal of likely-avascular A-lines in B-frame segments was used to set an optimized reflectance-adjusted threshold for discriminating vascular v. nonvascular voxels. The capillary density (CD) was calculated from en face projections of the superficial vascular complex, excluding large vessels. No additional filtering step was applied on en face angiograms. The retinal signal strength (RSS) was calculated by averaging the logarithmic-scale OCT reflectance signal within the retinal slab, and its correlation with CD was investigated.

Results : Eight healthy eyes were scanned with each instrument – twice in the same session and once on a separate day. The BMS algorithm improved within-visit repeatability and between-visit reproducibility of CD compared to a fixed-threshold measurement algorithm (Table 1). Using the BMS algorithm, the CD results were less affected by RSS and the population variation was reduced. Motion-induced line artifacts were reduced by the BMS algorithm (Figure 1).

Conclusions : The regression-based BMS algorithm improved the reliability of perfusion quantification in OCTA on both FDA-cleared SD-OCT angiography systems. It may be generally useful for artifact reduction in OCTA despite differences in platform and flow signal generating algorithm.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

 

Figure 1. En face angiograms of the superficial vascular plexus binarized by fixed-thresholding and regression-based bulk motion subtraction algorithms. The binary angiograms are used to calculate vessel density as area percentage.

Figure 1. En face angiograms of the superficial vascular plexus binarized by fixed-thresholding and regression-based bulk motion subtraction algorithms. The binary angiograms are used to calculate vessel density as area percentage.

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