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Multicenter reliability of semiautomatic retinal layer segmentation using OCT

OBJECTIVE: To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. METHODS: Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Hei...

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Autores principales: Oberwahrenbrock, Timm, Traber, Ghislaine L., Lukas, Sebastian, Gabilondo, Iñigo, Nolan, Rachel, Songster, Christopher, Balk, Lisanne, Petzold, Axel, Paul, Friedemann, Villoslada, Pablo, Brandt, Alexander U., Green, Ari J., Schippling, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5852947/
https://www.ncbi.nlm.nih.gov/pubmed/29552598
http://dx.doi.org/10.1212/NXI.0000000000000449
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author Oberwahrenbrock, Timm
Traber, Ghislaine L.
Lukas, Sebastian
Gabilondo, Iñigo
Nolan, Rachel
Songster, Christopher
Balk, Lisanne
Petzold, Axel
Paul, Friedemann
Villoslada, Pablo
Brandt, Alexander U.
Green, Ari J.
Schippling, Sven
author_facet Oberwahrenbrock, Timm
Traber, Ghislaine L.
Lukas, Sebastian
Gabilondo, Iñigo
Nolan, Rachel
Songster, Christopher
Balk, Lisanne
Petzold, Axel
Paul, Friedemann
Villoslada, Pablo
Brandt, Alexander U.
Green, Ari J.
Schippling, Sven
author_sort Oberwahrenbrock, Timm
collection PubMed
description OBJECTIVE: To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. METHODS: Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Heidelberg Eye Explorer (v1.9.3.0) beta-software (Spectralis Viewing Module v6.0.0.7), followed by manual correction by 5 experienced operators from 5 different academic centers. The mean thicknesses within a 6-mm area around the fovea were computed for the retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer (OPL), and outer nuclear layer (ONL). Intraclass correlation coefficients (ICCs) were calculated for mean layer thickness values. Spatial distribution of ICC values for the segmented volume scans was investigated using heat maps. RESULTS: Agreement between raters was good (ICC > 0.84) for all retinal layers, particularly inner retinal layers showed excellent agreement across raters (ICC > 0.96). Spatial distribution of ICC showed highest values in the perimacular area, whereas the ICCs were poorer for the foveola and the more peripheral macular area. The automated segmentation of the OPL and ONL required the most correction and showed the least agreement, whereas differences were less prominent for the remaining layers. CONCLUSIONS: Automated segmentation with manual correction of macular OCT scans is highly reliable when performed by experienced raters and can thus be applied in multicenter settings. Reliability can be improved by restricting analysis to the perimacular area and compound segmentation of GCL and IPL.
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spelling pubmed-58529472018-03-16 Multicenter reliability of semiautomatic retinal layer segmentation using OCT Oberwahrenbrock, Timm Traber, Ghislaine L. Lukas, Sebastian Gabilondo, Iñigo Nolan, Rachel Songster, Christopher Balk, Lisanne Petzold, Axel Paul, Friedemann Villoslada, Pablo Brandt, Alexander U. Green, Ari J. Schippling, Sven Neurol Neuroimmunol Neuroinflamm Article OBJECTIVE: To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. METHODS: Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Heidelberg Eye Explorer (v1.9.3.0) beta-software (Spectralis Viewing Module v6.0.0.7), followed by manual correction by 5 experienced operators from 5 different academic centers. The mean thicknesses within a 6-mm area around the fovea were computed for the retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer (OPL), and outer nuclear layer (ONL). Intraclass correlation coefficients (ICCs) were calculated for mean layer thickness values. Spatial distribution of ICC values for the segmented volume scans was investigated using heat maps. RESULTS: Agreement between raters was good (ICC > 0.84) for all retinal layers, particularly inner retinal layers showed excellent agreement across raters (ICC > 0.96). Spatial distribution of ICC showed highest values in the perimacular area, whereas the ICCs were poorer for the foveola and the more peripheral macular area. The automated segmentation of the OPL and ONL required the most correction and showed the least agreement, whereas differences were less prominent for the remaining layers. CONCLUSIONS: Automated segmentation with manual correction of macular OCT scans is highly reliable when performed by experienced raters and can thus be applied in multicenter settings. Reliability can be improved by restricting analysis to the perimacular area and compound segmentation of GCL and IPL. Lippincott Williams & Wilkins 2018-03-13 /pmc/articles/PMC5852947/ /pubmed/29552598 http://dx.doi.org/10.1212/NXI.0000000000000449 Text en Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Article
Oberwahrenbrock, Timm
Traber, Ghislaine L.
Lukas, Sebastian
Gabilondo, Iñigo
Nolan, Rachel
Songster, Christopher
Balk, Lisanne
Petzold, Axel
Paul, Friedemann
Villoslada, Pablo
Brandt, Alexander U.
Green, Ari J.
Schippling, Sven
Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title_full Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title_fullStr Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title_full_unstemmed Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title_short Multicenter reliability of semiautomatic retinal layer segmentation using OCT
title_sort multicenter reliability of semiautomatic retinal layer segmentation using oct
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5852947/
https://www.ncbi.nlm.nih.gov/pubmed/29552598
http://dx.doi.org/10.1212/NXI.0000000000000449
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