September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Quantitative mapping of retinal layer thickness and interface disruption by OCT enface imaging
Author Affiliations & Notes
  • Lakshmi Priya Rangaraju
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Michael Robert Tan
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Justin Wanek
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Norman P Blair
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Jennifer I Lim
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Mahnaz Shahidi
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Footnotes
    Commercial Relationships   Lakshmi Priya Rangaraju, None; Michael Tan, None; Justin Wanek, None; Norman Blair, None; Jennifer Lim, None; Mahnaz Shahidi, None
  • Footnotes
    Support  NIH DK104393 and EY001792, Research to Prevent Blindness
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5947. doi:
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    • Get Citation

      Lakshmi Priya Rangaraju, Michael Robert Tan, Justin Wanek, Norman P Blair, Jennifer I Lim, Mahnaz Shahidi; Quantitative mapping of retinal layer thickness and interface disruption by OCT enface imaging. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5947.

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

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Abstract

Purpose : To report a method for quantitative assessment of macular layer thickness and spatial extent of disruptions in layer interfaces due to diabetic retinopathy (DR).

Methods : High density spectral domain optical coherence tomography (SDOCT) imaging was performed in 12 DR subjects (age, 57 ± 11 years; 7 NPDR and 5 PDR) at 2 visits. Four of 12 subjects received anti-VEGF treatment between visits. An image segmentation software identified interfaces between retinal cell layers and generated enface thickness maps of nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCLIPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), and photoreceptor outer segment layer (OSL). Retinal layer interface disruption was defined as a visually indiscernable interface due to pathologies. Disruptions in the NFL/GCLIPL interface, GCLIPL/INL/OPL interfaces, or OPL/ONL/OSL interfaces were manually identified in SDOCT B-scans, and enface mapping of these regions was performed. Mean thickness (NFLT, GCLIPLT, INLT, OPLT, ONLT, OSLT) and areas of interface disruption (NFLd, INLd, ONLd) were calculated in 9 macular subfields. Data was analyzed using general linear model repeated measures.

Results : Mean time interval between visits was 163 ± 57 days. Mean number of anti-VEGF treatments was 3 (range: 0–10) and 4 (range: 0–14) at visit 1 and 2, respectively. Central subfield total retinal thickness was 303 ± 59 microns and 343 ± 90 microns at visit 1 and 2, respectively (P=0.08). Visual acuity (MAR) was 1.08 ± 0.29 and 1.27 ± 0.33 at visit 1 and 2, respectively (P = 0.2). In all macular subfields, NFLT, GCLIPLT, ONLT, OSLT and NFLd did not change significantly between visits (P ≥ 0.06). NFLT, GCLIPLT, ONLT, and OSLT varied significantly among macular subfields (P ≤ 0.01). INLT decreased over time in the perifoveal nasal subfield (P=0.009), while OPLT increased in the central subfield, all parafoveal subfields, and the perifoveal temporal subfield (P ≤ 0.02). INLd increased over time in the central subfield, and parafoveal nasal and temporal subfields (P ≤ 0.03) and ONLd increased in the central subfield (P=0.03).

Conclusions : Quantitative mapping of alterations in macular layer thickness and spatial extent of disruptions in layer interfaces is a promising tool for monitoring of diabetic macular changes.

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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