Original articleAutomated Segmentation Errors When Using Optical Coherence Tomography to Measure Retinal Nerve Fiber Layer Thickness in Glaucoma
Section snippets
Methods
We included data from participants enrolled in the ongoing Portland Progression Project11, 12, 13, 14 at Legacy Devers Eye Institute, Portland, Oregon. The Legacy Health Institutional Review Board approved this study. All participants provided their consent after they were informed about the risks and benefits of their participation. The study adhered to the tenets of the Declaration of Helsinki.
The Portland Progression Project includes participants with a diagnosis of glaucoma suspect or open
Results
This study included 3490 scans from 412 eyes (209 right and 203 left eyes) of 213 individuals. Four scans (0.1%) did not include complete measurements in clock hour 9 (temporal sector) and were not included in the evaluation of this sector or in the changes in glaucoma classification. Table 1 describes the participants. They were mostly white, 58% female, early glaucoma by mean deviation of their visual field, and a mean (±SD) age of 66.7 ± 10.9 years.
Discussion
OCT provides objective and repeatable measurements of optic nerve head structure and RNFL thickness.19, 20, 21, 22 However, variability in RNFL thickness measurements and failure of RNFL segmentation algorithms can lead to over- or underestimations of RNFL thickness.10 We were interested in the magnitude, associations, and locations of errors associated with automated segmentation of the RNFL when operators do not use manual refinement. In this study, we used manual refinement of the automated
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