Reproducibility of In-Vivo OCT Measured Three-Dimensional Human Lamina Cribrosa Microarchitecture
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Wang-2014-Reproducibility of I.pdf
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Author(s)
Wang, Bo
Nevins, Jessica E.
Nadler, Zach
Wollstein, Gadi
Ishikawa, Hiroshi
Bilonick, Richard A.
Kagemann, Larry
Sigal, Ian A.
Grulkowski, Ireneusz
Liu, Jonathan Jaoshin
Date Issued
April 2014
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Wang, Bo, Jessica E. Nevins, Zach Nadler, Gadi Wollstein, Hiroshi Ishikawa, Richard A. Bilonick, Larry Kagemann, et al. “Reproducibility of In-Vivo OCT Measured Three-Dimensional Human Lamina Cribrosa Microarchitecture.” Edited by Knut Stieger. PLoS ONE 9, no. 4 (April 18, 2014): e95526.
Version
Final published version
Abstract
Purpose
To determine the reproducibility of automated segmentation of the three-dimensional (3D) lamina cribrosa (LC) microarchitecture scanned in-vivo using optical coherence tomography (OCT).
Methods
Thirty-nine eyes (8 healthy, 19 glaucoma suspects and 12 glaucoma) from 49 subjects were scanned twice using swept-source (SS−) OCT in a 3.5×3.5×3.64 mm (400×400×896 pixels) volume centered on the optic nerve head, with the focus readjusted after each scan. The LC was automatically segmented and analyzed for microarchitectural parameters, including pore diameter, pore diameter standard deviation (SD), pore aspect ratio, pore area, beam thickness, beam thickness SD, and beam thickness to pore diameter ratio. Reproducibility of the parameters was assessed by computing the imprecision of the parameters between the scans.
Results
The automated segmentation demonstrated excellent reproducibility. All LC microarchitecture parameters had an imprecision of less or equal to 4.2%. There was little variability in imprecision with respect to diagnostic category, although the method tends to show higher imprecision amongst healthy subjects.
Conclusion
The proposed automated segmentation of the LC demonstrated high reproducibility for 3D LC parameters. This segmentation analysis tool will be useful for in-vivo studies of the LC.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0095526
