IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0087996.html
   My bibliography  Save this article

Repeatability and Reproducibility of Eight Macular Intra-Retinal Layer Thicknesses Determined by an Automated Segmentation Algorithm Using Two SD-OCT Instruments

Author

Listed:
  • Xinting Liu
  • Meixiao Shen
  • Shenghai Huang
  • Lin Leng
  • Dexi Zhu
  • Fan Lu

Abstract

Purpose: To evaluate the repeatability, reproducibility, and agreement of thickness profile measurements of eight intra-retinal layers determined by an automated algorithm applied to optical coherence tomography (OCT) images from two different instruments. Methods: Twenty normal subjects (12 males, 8 females; 24 to 32 years old) were enrolled. Imaging was performed with a custom built ultra-high resolution OCT instrument (UHR-OCT, ∼3 µm resolution) and a commercial RTVue100 OCT (∼5 µm resolution) instrument. An automated algorithm was developed to segment the macular retina into eight layers and quantitate the thickness of each layer. The right eye of each subject was imaged two times by the first examiner using each instrument to assess intra-observer repeatability and once by the second examiner to assess inter-observer reproducibility. The intraclass correlation coefficient (ICC) and coefficients of repeatability and reproducibility (COR) were analyzed to evaluate the reliability. Results: The ICCs for the intra-observer repeatability and inter-observer reproducibility of both SD-OCT instruments were greater than 0.945 for the total retina and all intra-retinal layers, except the photoreceptor inner segments, which ranged from 0.051 to 0.643, and the outer segments, which ranged from 0.709 to 0.959. The CORs were less than 6.73% for the total retina and all intra-retinal layers. The total retinal thickness measured by the UHR-OCT was significantly thinner than that measured by the RTVue100. However, the ICC for agreement of the thickness profiles between UHR-OCT and RTVue OCT were greater than 0.80 except for the inner segment and outer segment layers. Conclusions: Thickness measurements of the intra-retinal layers determined by the automated algorithm are reliable when applied to images acquired by the UHR-OCT and RTVue100 instruments.

Suggested Citation

  • Xinting Liu & Meixiao Shen & Shenghai Huang & Lin Leng & Dexi Zhu & Fan Lu, 2014. "Repeatability and Reproducibility of Eight Macular Intra-Retinal Layer Thicknesses Determined by an Automated Segmentation Algorithm Using Two SD-OCT Instruments," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
  • Handle: RePEc:plo:pone00:0087996
    DOI: 10.1371/journal.pone.0087996
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0087996
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0087996&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0087996?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0087996. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.