The comparison of manual vs automated disc margin delineation using spectral-domain optical coherence tomography

Abstract

Aims To examine the impact of manual vs automated disc margin delineation on optic nerve head (ONH) and retinal nerve fiber layer (RNFL) parameters using spectraldomain optical coherence tomography (SDOCT). Methods A prospective cohort study consisting of normal, glaucoma suspect (GS) and glaucoma patients who underwent ONH and RNFL measurements using SDOCT technology (RTVue; Optovue Inc.). The retinal pigment epithelium/Bruch's membrane (RPE/BM) complex end points were automatically determined first, and were manually redefined subsequently. Analysis of variance, coefficient of variation (COV), concordance correlation coefficient (CCC), and Bland-Altman plots were used for the analyses. Results Ninety-nine eyes of 50 subjects (age 68±10 years) consisting of 36 glaucoma, 56 GS, and 7 normal eyes were included. The RNFL thickness measurements were similar (P40.05) between the two methods of demarcation, except for the inferior-nasal sector (P ¼ 0.04). For the ONH measurements, the cup-to-disc (C/D) ratio and rim area showed significant differences between the two methods (Po0.001). COV/CCC values for the ONH parameters were as follows: cup area 17.6%/0.88; cup volume 7.4%/0.91; average C/D ratio 18.1%/0.78; rim area 25.3%/ 0.69; and rim volume 42.6%/0.71, respectively. CCC/COV values for the RNFL parameters were as follows: average 2.1%/0.98; inferiortemporal quadrant 8.1%/0.79; inferior-nasal quadrant INQ quadrant 12.6%/0.67; SNQ quadrant 7.8%/0.83; and STQ quadrant 7.8%/0.88, respectively. Conclusion An overall high agreement and moderate-substantial concordance was observed between the demarcation methods. Automated disc margin delineation of SDOCT can be used reliably in clinical practice.

Effect of Signal Intensity on Measurement of Ganglion Cell Complex and Retinal Nerve Fiber Layer Scans in Fourier-Domain Optical Coherence Tomography

“…In an ideal situation, it is preferable to have a large number of same-day repeat sessions on a single eye to evaluate the SSI effect. Additionally, factors other than signal intensity, such as cataract, vitreous floaters, or disc margin delineation algorithm failure, 29 may impact measurement values and lead to increased variability independent of SSI. It also is unknown to what extent measurement variability caused by extreme high and low SSI values affects OCT diagnostic classifications (i.e., green/yellow/red color code), which may complicate interpretation.…”

Artifact Rates for 2D Retinal Nerve Fiber Layer Thickness Versus 3D Neuroretinal Rim Thickness Using Spectral-Domain Optical Coherence Tomography

“… 21 , 31 On the other hand, 2D peripapillary RNFL thickness and 2D neuroretinal rim measurements generated along a flat reference plane (e.g., cup-to-disc ratio and rim area) on average undergo significant changes after correction of segmentation errors. 17 , 23 , 24 , 40 , 43 The need to manually fix errors or repeat scans in the clinic requires extra time and attention, and parameters derived from 3D volume scans appear to reduce this need.…”

Automated Segmentation of Optic Nerve Head Structures With Optical Coherence Tomography

“…10,16 Recent studies have examined the agreement between automated and manual segmentation in their derivation of disc margin-based measurements such as cup-disc ratio, with the assumption that the termination of the Bruch's membrane/retinal pigment epithelium complex represents the clinical disc margin. 19,20 While these studies have reported generally good agreement between the two methods, the clinically visible optic disc margin seldom corresponds to BMO, 6 making these studies challenging to interpret. In contrast, our evaluation of the automated segmentation algorithm compared automated and manual ILM and BMO segmentation in all of the same B-scan images.…”

“…Automated segmentation of the ILM and Bruch's membrane, including BMO, 10,16 is currently used in commercial SD-OCT devices. 17,18 To date, published studies have been limited to reporting the agreement between manual and automated segmentation methods primarily for deriving traditional indices such as cup-disc ratio and rim area, 10,16,19,20 with the assumption that BMO represents the disc margin. The aim of our study was to quantify and characterize the differences between an automated segmentation algorithm and manual methods to identify the ILM and BMO.…”