Platform-Independent Cirrus and Spectralis Thickness Measurements in Eyes with Diabetic Macular Edema Using Fully Automated Software.


Journal Article

We determine whether the automated segmentation software, Duke Optical Coherence Tomography Retinal Analysis Program (DOCTRAP), can measure, in a platform-independent manner, retinal thickness on Cirrus and Spectralis spectral domain optical coherence tomography (SD-OCT) images in eyes with diabetic macular edema (DME) under treatment in a clinical trial.Automatic segmentation software was used to segment the internal limiting membrane (ILM), inner retinal pigment epithelium (RPE), and Bruch's membrane (BM) in SD-OCT images acquired by Cirrus and Spectralis commercial systems, from the same eye, on the same day during a clinical interventional DME trial. Mean retinal thickness differences were compared across commercial and DOCTRAP platforms using intraclass correlation (ICC) and Bland-Altman plots.The mean 1 mm central subfield thickness difference (standard error [SE]) comparing segmentation of Spectralis images with DOCTRAP versus HEYEX was 0.7 (0.3) μm (0.2 pixels). The corresponding values comparing segmentation of Cirrus images with DOCTRAP versus Cirrus software was 2.2 (0.7) μm. The mean 1 mm central subfield thickness difference (SE) comparing segmentation of Cirrus and Spectralis scan pairs with DOCTRAP using BM as the outer retinal boundary was -2.3 (0.9) μm compared to 2.8 (0.9) μm with inner RPE as the outer boundary.DOCTRAP segmentation of Cirrus and Spectralis images produces validated thickness measurements that are very similar to each other, and very similar to the values generated by the corresponding commercial software in eyes with treated DME.This software enables automatic total retinal thickness measurements across two OCT platforms, a process that is impractical to perform manually.

Full Text

Duke Authors

Cited Authors

  • Willoughby, AS; Chiu, SJ; Silverman, RK; Farsiu, S; Bailey, C; Wiley, HE; Ferris, FL; Jaffe, GJ

Published Date

  • February 7, 2017

Published In

Volume / Issue

  • 6 / 1

Start / End Page

  • 9 -

PubMed ID

  • 28180033

Pubmed Central ID

  • 28180033

Electronic International Standard Serial Number (EISSN)

  • 2164-2591

International Standard Serial Number (ISSN)

  • 2164-2591

Digital Object Identifier (DOI)

  • 10.1167/tvst.6.1.9


  • eng