Fully automatic software for retinal thickness in eyes with diabetic macular edema from images acquired by cirrus and spectralis systems

Invest Ophthalmol Vis Sci. 2013 Nov 15;54(12):7595-602. doi: 10.1167/iovs.13-11762.

Abstract

Purpose: To determine whether a novel automatic segmentation program, the Duke Optical Coherence Tomography Retinal Analysis Program (DOCTRAP), can be applied to spectral-domain optical coherence tomography (SD-OCT) images obtained from different commercially available SD-OCT in eyes with diabetic macular edema (DME).

Methods: A novel segmentation framework was used to segment the retina, inner retinal pigment epithelium, and Bruch's membrane on images from eyes with DME acquired by one of two SD-OCT systems, Spectralis or Cirrus high definition (HD)-OCT. Thickness data obtained by the DOCTRAP software were compared with those produced by Spectralis and Cirrus. Measurement agreement and its dependence were assessed using intraclass correlation (ICC).

Results: A total of 40 SD-OCT scans from 20 subjects for each machine were included in the analysis. Spectralis: the mean thickness in the 1-mm central area determined by DOCTRAP and Spectralis was 463.8 ± 107.5 μm and 467.0 ± 108.1 μm, respectively (ICC, 0.999). There was also a high level agreement in surrounding areas (out to 3 mm). Cirrus: the mean thickness in the 1-mm central area was 440.8 ± 183.4 μm and 442.7 ± 182.4 μm by DOCTRAP and Cirrus, respectively (ICC, 0.999). The thickness agreement in surrounding areas (out to 3 mm) was more variable due to Cirrus segmentation errors in one subject (ICC, 0.734-0.999). After manual correction of the errors, there was a high level of thickness agreement in surrounding areas (ICC, 0.997-1.000).

Conclusions: The DOCTRAP may be useful to compare retinal thicknesses in eyes with DME across OCT platforms.

Keywords: diabetic macular edema (DME); segmentation; spectral-domain optical coherence tomography (SD-OCT).

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Diabetic Retinopathy / diagnosis*
  • Humans
  • Image Processing, Computer-Assisted / instrumentation*
  • Macular Edema / diagnosis*
  • Organ Size
  • Retina / pathology*
  • Retinal Photoreceptor Cell Inner Segment / pathology
  • Retinal Photoreceptor Cell Outer Segment / pathology
  • Retinal Pigment Epithelium / pathology
  • Software*
  • Tomography, Optical Coherence / instrumentation
  • Tomography, Optical Coherence / methods*