September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Measuring organelle motility in RPE cells in the living human retina
Author Affiliations & Notes
  • Zhuolin Liu
    optometry school, Indiana University, Bloomington, Indiana, United States
  • Kazuhiro Kurokawa
    optometry school, Indiana University, Bloomington, Indiana, United States
  • Omer Pars Kocaoglu
    optometry school, Indiana University, Bloomington, Indiana, United States
  • Furu Zhang
    optometry school, Indiana University, Bloomington, Indiana, United States
  • Donald Thomas Miller
    optometry school, Indiana University, Bloomington, Indiana, United States
  • Footnotes
    Commercial Relationships   Zhuolin Liu, None; Kazuhiro Kurokawa, None; Omer Kocaoglu, None; Furu Zhang, None; Donald Miller, US #7,364,296 (P), US #8,979,266 (P)
  • Footnotes
    Support  NEI R01EY018339, P30EY019008
Investigative Ophthalmology & Visual Science September 2016, Vol.57, No Pagination Specified. doi:
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      Zhuolin Liu, Kazuhiro Kurokawa, Omer Pars Kocaoglu, Furu Zhang, Donald Thomas Miller; Measuring organelle motility in RPE cells in the living human retina. Invest. Ophthalmol. Vis. Sci. 2016;57(12):No Pagination Specified.

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

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Abstract

Purpose : The retinal pigment epithelium (RPE) plays a central role in supporting and maintaining photoreceptors. While dysfunction of the RPE underlies numerous retinal pathologies, biomarkers sensitive to RPE change are limited. In this study, we propose a new approach based on organelle motility that quantifies changes at the sub-cellular level. To do this, we take advantage of the interferometric nature of adaptive optics optical coherence tomography (AO–OCT) to measure motion–evoked changes in the scatter of light in individual RPE cells in the living human retina.

Methods : Two healthy subjects were imaged at 7° temporal retina using the Indiana AO–OCT imaging system. Three volume videos were acquired at 3 minute intervals with each containing 10 volumes (2.7 Hz volume rate). Volumes with unacceptable motion artifacts were removed. Remaining volumes were combined into a single, time-stamped video. Volumes of the video were registered in all three dimensions with subcellular accuracy to correct for motion artifacts. En face images were extracted of the following layers: RPE, inner segment/outer segment junction (IS/OS), cone outer segment tip (COST), and choriocapillaris (CC). The latter three were used as controls. The IS/OS and COST reflections are known to be relatively stable over the short time duration of the experiment (< 10 min). In contrast, the CC was dominated by white noise that fluctuated from one image to the next. To assess temporal dynamics, the cross-correlation was computed for the reflectance trace of individual RPE cells, as well as corresponding regions at IS/OS, COST, and CC. An ensemble cross-correlation was determined by averaging across all regions of the same layer. An exponential fit was applied to each to determine a time decay constant. The RPE cell mosaics (307 and 215 cells in the two subjects) were determined by Voronoi analysis [1].

Results : Temporal changes in the reflectance pattern inside individual RPE cells occurred on a faster time scale than those inside cones (IS/OS and COST). For the two subjects, average decay constant was 50.6 s and 45.3 s (RPE), 123.1 s and 143.7 s (IS/OS), and 137.2 s and 145.4 s (COST). As expected, choriocapillaris dominated by white noise had a decay constant of 0 s.

Conclusions : AO-OCT imaging permits measuring temporal dynamics inside RPE cells, the source of which we believe to be organelle motility.

[1] Liu, et al. IOVS 2015;56:ARVO E-Abstract 5883.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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