August 2019
Volume 60, Issue 11
Open Access
ARVO Imaging in the Eye Conference Abstract  |   August 2019
Drusen Dynamics using Optical Coherence Tomography (OCT)
Author Affiliations & Notes
  • Jeong W Pak
    Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States
  • Amitha Domalpally
    Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States
  • Yijun Huang
    EyeKor Inc, Madison, Wisconsin, United States
  • Dawn Myers
    Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States
  • Barbara Blodi
    Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States
  • Footnotes
    Commercial Relationships   Jeong Pak, None; Amitha Domalpally, None; Yijun Huang, EyeKor Inc (I); Dawn Myers, None; Barbara Blodi, None
  • Footnotes
    Support  Research to Prevent Blindness
Investigative Ophthalmology & Visual Science August 2019, Vol.60, PB0123. doi:
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      Jeong W Pak, Amitha Domalpally, Yijun Huang, Dawn Myers, Barbara Blodi; Drusen Dynamics using Optical Coherence Tomography (OCT). Invest. Ophthalmol. Vis. Sci. 2019;60(11):PB0123.

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

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Abstract

Purpose : Increase in drusen volume as measured by OCT may be a risk factor for end stage age-related macular degeneration (AMD). Change in overall drusen volume does not adequately capture the dynamic nature of drusen progression in an eye, with some drusen growing and others fading. We assessed these uneven regional changes in drusen volume on OCT as the disease progressed.

Methods : OCT was evaluated from 95 eyes with intermediate AMD at baseline and month 12. Segmentation of drusen was performed from top of the RPE layer to top of Bruch’s Membrane using semi-automated custom software to generate drusen volume in each of the 9 subfields of the OCT grid. Reproducibility was assessed by masked regrading of 50 eyes.

Results : The mean drusen volume at baseline was 1.02 mm3 (±0.17 mm3) and mean change at 12-month was 0.03 mm3 (±0.05 mm3). An increase in the mean drusen volume was seen in 72 eyes (75.8%), 15 (15.8%) showed a decrease and 8 (8.4%) showed no change over one year. In 59% of the AMD eyes, uniform change in drusen volume was observed across all subfields; 47% showed uniform increase and 12% uniform decrease in drusen volume across all subfields. In 40%, there was regional variation for change in subfields within the grid, such that within the same eye some subfields increased while others decreased. Intergrader agreement assessed using Bland Altman plots showed a mean difference of 0.02 mm3 (confidence limit -0.08, 0.02) between the two graders in drusen volume.

Conclusions : Drusen volume on OCT is a useful tool to measure change in drusen burden over time. Total volume is an insufficient metric to capture drusen progression. Mapping drusen volume by OCT subfield may provide a better understanding of the dynamic changes in AMD. Monitoring drusen dynamics may be an important outcome for clinical trials and future prevention therapy.

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

 

Figure 1 A heat map showing changes in drusen volume in individual subfields of the OCT grid. Warm colors (red) represent increase, cool colors (blue) represent decrease and no color represents no change. There is regional variability from subfield to subfield in drusen change.

Figure 1 A heat map showing changes in drusen volume in individual subfields of the OCT grid. Warm colors (red) represent increase, cool colors (blue) represent decrease and no color represents no change. There is regional variability from subfield to subfield in drusen change.

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