4.6 Article

Multicenter reliability of semiautomatic retinal layer segmentation using OCT

Journal

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/NXI.0000000000000449

Keywords

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Funding

  1. Federal Ministry of Education and Research (BMBF)
  2. Santhera
  3. Carlos III Health Institute [JR/00008, PI/16/00005]
  4. Teva
  5. OCTiMS study
  6. Novartis
  7. NIH
  8. Biomedical Research Centre, based at Moorfields Eye Hospital
  9. NHS Foundation Trust
  10. UCL Institute of Ophthalmology
  11. Bayer
  12. Biogen
  13. Sanofi-Aventis/Genzyme
  14. Merck Serono
  15. Alexion
  16. Chugai
  17. MedImmune
  18. Shire
  19. German Research Council
  20. Werth Stiftung of the City of Cologne
  21. German Ministry of Education and Research
  22. Arthur Arnstein Stiftung Berlin
  23. EU FP7 Framework Program
  24. Arthur Arnstein Foundation Berlin
  25. Guthy Jackson Charitable Foundation
  26. US National Multiple Sclerosis Society
  27. Instituto de Salud Carlos III
  28. European Commission
  29. National MS Society
  30. Fundacion Maraton TV3
  31. GAEM Foundation
  32. Novartis Pharma OCTIMs
  33. Inception Sciences SRA
  34. NINDS
  35. NIA
  36. Sherak Foundation
  37. Hilton Foundation
  38. Sanofi-Genzyme
  39. University of Zurich
  40. Betty and David Koetser Foundation for Brain Research
  41. Swiss Multiple Sclerosis Society

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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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