June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Compensation for reflectance variation in flow index quantification by optical coherence tomography angiography
Author Affiliations & Notes
  • Simon S. Gao
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • Yali Jia
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • Liang Liu
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • Hana L Takusagawa
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • John C Morrison
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • David Huang
    Ophthalmology, Oregon Health & Science University, Portland, Oregon, United States
  • Footnotes
    Commercial Relationships   Simon Gao, None; Yali Jia, Optovue (F), Optovue (P); Liang Liu, None; Hana Takusagawa, None; John Morrison, None; David Huang, Carl Zeiss Meditec (P), Optovue (F), Optovue (I), Optovue (P), Optovue (R)
  • Footnotes
    Support  This work was supported by NIH grants R01 EY023285, R01 EY024544, DP3 DK104397, P30 EY010572, and unrestricted departmental funding from Research to Prevent Blindness.
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 650. doi:
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    • Get Citation

      Simon S. Gao, Yali Jia, Liang Liu, Hana L Takusagawa, John C Morrison, David Huang; Compensation for reflectance variation in flow index quantification by optical coherence tomography angiography. Invest. Ophthalmol. Vis. Sci. 2017;58(8):650.

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

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Abstract

Purpose : To compensate for reflectance variation when quantifying flow index by optical coherence tomography angiography (OCTA).

Methods : Macular scans of healthy participants were taken using a spectral OCT system (Avanti). Participants received 2 or 3 OCTA scans covering a 3×3 mm area centered on the macula. The data was exported and analyzed with custom software. The SSADA algorithm was used to detect flow. Maximum flow projection of the inner retinal slab produced the en face angiogram. The reflectance of the maximum flow voxel was used to construct an en face vascular reflectance map. Larger vessels were identified by an automated algorithm that identified their high ratio of flow signal to outer retinal reflectance and separated from capillaries on the en face angiograms. Flow index was calculated by averaging the flow signal in the en face angiogram.

Results : Macular scans of healthy participants were taken using a spectral OCT system (Avanti). Participants received 2 or 3 OCTA scans covering a 3×3 mm area centered on the macula. The data was exported and analyzed with custom software. The SSADA algorithm was used to detect flow. Maximum flow projection of the inner retinal slab produced the en face angiogram. The reflectance of the maximum flow voxel was used to construct an en face vascular reflectance map. Larger vessels were identified by an automated algorithm that identified their high ratio of flow signal to outer retinal reflectance and separated from capillaries on the en face angiograms. Flow index was calculated by averaging the flow signal in the en face angiogram.

Conclusions : Compensating for reflectance variation improved the reliability of flow index quantification.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

Figure 1. (A) In a group of 13 healthy eyes which received 2 or 3 scans each, the flow index of the superficial retina, excluding the FAZ, was correlated to the signal strength index (SSI) of the scan. (B) The average decorrelation (flow signal) and average log reflectance of larger retinal vessels (red) and capillaries (blue) were correlated. Data were from en face images of the inner retina (ILM to OPL). (C) By scaling the decorrelation values based on reflectance according to the fits in panel B, the positive relationship between SSI and flow index was removed.

Figure 1. (A) In a group of 13 healthy eyes which received 2 or 3 scans each, the flow index of the superficial retina, excluding the FAZ, was correlated to the signal strength index (SSI) of the scan. (B) The average decorrelation (flow signal) and average log reflectance of larger retinal vessels (red) and capillaries (blue) were correlated. Data were from en face images of the inner retina (ILM to OPL). (C) By scaling the decorrelation values based on reflectance according to the fits in panel B, the positive relationship between SSI and flow index was removed.

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