August 2019
Volume 60, Issue 11
Open Access
ARVO Imaging in the Eye Conference Abstract  |   August 2019
Waveform analysis and vessel type identification in the retina with laser Doppler holography
Author Affiliations & Notes
  • Leo Puyo
    Institut Langevin, Paris, France
  • Michel Paques
    Centre d'investigation clinique des Quinze-Vingts, Paris, France
    Institut de la Vision, Paris, France
  • Mathias Fink
    Institut Langevin, Paris, France
  • Jose Sahel
    Centre d'investigation clinique des Quinze-Vingts, Paris, France
    Institut de la Vision, Paris, France
  • Michael Atlan
    Institut Langevin, Paris, France
  • Footnotes
    Commercial Relationships   Leo Puyo, None; Michel Paques, None; Mathias Fink, None; Jose Sahel, None; Michael Atlan, None
  • Footnotes
    Support  European Research Council
Investigative Ophthalmology & Visual Science August 2019, Vol.60, 018. doi:https://doi.org/
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    • Get Citation

      Leo Puyo, Michel Paques, Mathias Fink, Jose Sahel, Michael Atlan; Waveform analysis and vessel type identification in the retina with laser Doppler holography. Invest. Ophthalmol. Vis. Sci. 2019;60(11):018. doi: https://doi.org/.

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

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Abstract

Purpose : Laser Doppler holography (LDH) is a full-field blood flow imaging technique that was recently used in the human eye. The power Doppler signal measured in LDH involves several contributions such as blood flow but also ocular movements comprising fundus pulsations. We here investigate these different contributions through data processing in order to extract the retinal blood flow contribution.

Methods : This study was done in accordance with the Declaration of Helsinki and all subjects gave informed consent. We analyzed the reconstructed power Doppler waveforms using different Doppler frequency ranges. We used low frequency shifts to reveal slow ocular movements and high frequency shifts to reveal flow in vessels. Additionally, we transposed for LDH some metrics that were developed for functional Doppler ultrasound such as resistivity index that measures systolodiastolic variations in blood vessels.

Results : The segmentation of the power Doppler spectral density revealed that for frequency shifts from 1 to 4 kHz, the power Doppler signal is dominated by ocular fundus pulsations, while the frequency shifts for 10 to 37 kHz reveal the cardiac cycle waveform. The high frequency power Doppler signal is strongly correlated between all regions of the image, but subtracting the spatially averaged value allows to reveal waveforms typical of the probed structure (i.e. arteries or veins). Finally, we also found that calculating resistivity maps from these waveforms, we were able to propose a clear arteriovenous differentiation in the retina.

Conclusions : We have shown that the power Doppler signal as measured in LDH can be decomposed to measure the contributions of fundus pulsation and blood flow in retinal capillaries and large vessels. Moreover, the distinct waveforms of blood flow in arteries and veins allows for a robust differentiation of these vessels.

This abstract was presented at the 2019 ARVO Imaging in the Eye Conference, held in Vancouver, Canada, April 26-27, 2019.

 

Power Doppler throughout cardiac cycles measured in ROI (B) shown in Fig. 2. (a) Low frequency shifts (1-4 kHz). (b) High Frequency shifts (10-37 kHz).

Power Doppler throughout cardiac cycles measured in ROI (B) shown in Fig. 2. (a) Low frequency shifts (1-4 kHz). (b) High Frequency shifts (10-37 kHz).

 

Power Doppler measurements for high frequency shifts (10-37 kHz). (a) Power Doppler throughout cardiac cycle in a vein (V), an artery (A) and the background (B). (b) Associated power Doppler image with the ROIs drawn. (c) Power Doppler in the 3 same ROIs when subtracting average signal. (d) Coefficient of variation of the power Doppler leading to an arteriovenous differentiation.

Power Doppler measurements for high frequency shifts (10-37 kHz). (a) Power Doppler throughout cardiac cycle in a vein (V), an artery (A) and the background (B). (b) Associated power Doppler image with the ROIs drawn. (c) Power Doppler in the 3 same ROIs when subtracting average signal. (d) Coefficient of variation of the power Doppler leading to an arteriovenous differentiation.

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