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Berthold Pemp, Karl Kircher, Ursula Schmidt-Erfurth, Andreas Reitner; Reproducibility of a New Algorithm for Retinal Nerve Fiber Layer Thickness Measurement Using Spectral Domain OCT in Healthy Subjects. Invest. Ophthalmol. Vis. Sci. 2011;52(14):1022.
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© ARVO (1962-2015); The Authors (2016-present)
Alterations in retinal nerve fiber layer thickness (RNFLT) can be observed in various diseases of the optic nerve using optical coherence tomography (OCT). However, the detection of subtle changes over time is limited by image resolution and contrast as well as by the amount of speckle noise before layer segmentation. In the present study we evaluated short-term and day to day reproducibility of a new measurement algorithm with improved image quality using Spectralis spectral domain OCT and compared it to conventional measurements.
Twenty healthy subjects were included in this prospective cohort study. Peripapillary RNFLT was measured on four different days in forty eyes using Spectralis OCT. Conventional measurements with averaged 16 image frames were compared to a new algorithm using 100 frames. Short-term and day to day reproducibility was evaluated by the calculation of intraindividual coefficients of variation (CV) and intraclass correlation coefficients (ICC). In addition these values were compared to the reproducibility of averaged values from 7 repeated measurements per study day.
Short term reproducibility of single RNFLT measurements was significantly improved using the novel measurement algorithm of 100 frames (CV: 0.56 ± 0.42 % vs. 0.91 ± 0.54 %, p = 0.003, paired t-test). Day to day reproducibility was further improved by the use of averaged repeated measurements compared to single measurements (CV: 0.53 ± 0.43 % vs. 0.78 ± 0.56 %, p = 0.006). The ICC range was 0.96-0.99, also reflecting a very good day to day reproducibility. The best value was achieved using the novel algorithm of 100 frames.
Short term and day to day reproducibility of RNFLT measurements with spectral domain OCT can be improved by the increase of frames per measurement as well as by averaging values of repeated measurements per session. This allows a more accurate evaluation of RNFLT changes and reduces sample sizes necessary to detect small changes over time e.g. in neurodegenerative disease.
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