Effects of Circumpapillary Retinal Nerve Fiber Layer Segmentation Error Correction on Glaucoma Diagnosis in Myopic Eyes

Suwan, Yanin; Rettig, Samantha; Park, Sung Chul; Tantraworasin, Apichat; Geyman, Lawrence; Effert, keith; Silva, Luis; Jarukasetphorn, Ravivarn; Ritch, Robert

doi:10.1097/ijg.0000000000001054

Cited by 21 publications

(29 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, recent work 5 , 7 has argued that this metric does not perform well, and our results here are in agreement. There is also evidence that the cpRNFL thickness measured from circle b-scans, on which the ΔG metric is based, is affected by segmentation and alignment errors 14 – 18 and that reports based on this metric can miss local defects. 19 – 21 Our purpose here was to provide evidence that links these findings.…”

Section: Discussionmentioning

confidence: 99%

Reasons why OCT Global Circumpapillary Retinal Nerve Fiber Layer Thickness is a Poor Measure of Glaucomatous Progression

Eguia

Tsamis

Zemborain

et al. 2020

Trans. Vis. Sci. Tech.

Self Cite

View full text Add to dashboard Cite

Purpose To assess the effects of local defects, segmentation errors, and improper image alignment on the performance of the commonly used optical coherence tomography (OCT) measure of progression, that is the change in global (average) circumpapillary retinal nerve fiber layer (cpRNFL) thickness (ΔG). Methods One hundred fifty eyes suspected of, or with, early glaucoma had OCT circle and cube scans obtained using eye tracking on two occasions at least 1 year apart. Statistical progression was defined by fixed values of ΔG (3–8 um) and quantile regression. For a reference standard, four authors identified 30 eyes as “likely progressed,” and 61 eyes that “likely had not progressed” based on OCT reports from both baseline and follow-up tests. Results A ΔG criterion of 4 um had the best accuracy: 77%, with 5 false positive (8.2%) and 16 false negative (53%). A post hoc analysis of circular b-scans and OCT probability maps of these eyes indicated that segmentation errors and local progression accounted for most of these mistakes. Segmentation errors, although less common, were also present in true positives and true negatives. Conclusions Local defects and segmentation errors are the primary reasons for the poor performance of cpRNFL thickness G metric. Because these problems are difficult, if not impossible, to eliminate, the G metric should not be relied on in isolation for detecting glaucomatous progression. Translational Relevance Local defects and segmentation errors are easily identified by viewing OCT circumpapillary images, which should be part of the standard protocol for detecting glaucomatous progression.

show abstract

Section: Discussionmentioning

confidence: 99%

Reasons why OCT Global Circumpapillary Retinal Nerve Fiber Layer Thickness is a Poor Measure of Glaucomatous Progression

Eguia

Tsamis

Zemborain

et al. 2020

Trans. Vis. Sci. Tech.

Self Cite

View full text Add to dashboard Cite

show abstract

“… 13 – 22 This may be due to our broad inclusion of several different types of artifacts, as opposed to only segmentation errors, which were the focus of other papers. 15 , 17 , 19 , 20 …”

Section: Discussionmentioning

confidence: 99%

“… 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.…”

Section: Discussionmentioning

confidence: 99%

“… 5 – 12 However, its value is limited by a high rate of artifacts, with 7.1% to 58.5% of RNFL scans affected. 13 – 22 Studies show that these artifacts may cause clinically significant errors in measurement 17 , 23 , 24 and lead to false glaucoma classifications in as many as 39.0% of scans. 24 – 26 …”

Section: Introductionmentioning

confidence: 99%

“…[5][6][7][8][9][10][11][12] However, its value is limited by a high rate of artifacts, with 7.1% to 58.5% of RNFL scans affected. [13][14][15][16][17][18][19][20][21][22] Studies show that these artifacts may cause clinically significant errors in measurement 17,23,24 and lead to false glaucoma classifications in as many as 39.0% of scans. [24][25][26] The minimum distance band (MDB) quantifies three-dimensional (3D) neuroretinal rim tissue from a high-density SD-OCT optic nerve volume scan protocol using custom-designed research software.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Park

Tsikata

Lee

et al. 2020

Trans. Vis. Sci. Tech.

View full text Add to dashboard Cite

Purpose To compare the rates of clinically significant artifacts for two-dimensional peripapillary retinal nerve fiber layer (RNFL) thickness versus three-dimensional (3D) neuroretinal rim thickness using spectral-domain optical coherence tomography (SD-OCT). Methods Only one eye per patient was used for analysis of 120 glaucoma patients and 114 normal patients. For RNFL scans and optic nerve scans, 15 artifact types were calculated per B-scan and per eye. Neuroretinal rim tissue was quantified by the minimum distance band (MDB). Global MDB neuroretinal rim thicknesses were calculated before and after manual deletion of B-scans with artifacts and subsequent automated interpolation. A clinically significant artifact was defined as one requiring manual correction or repeat scanning. Results Among glaucomatous eyes, artifact rates per B-scan were significantly more common in RNFL scans (61.7%, 74 of 120) compared to B-scans in neuroretinal rim volume scans (20.9%, 1423 of 6820) (95% confidence interval [CI], 31.6–50.0; P < 0.0001). For clinically significant artifact rates per eye, optic nerve scans had significantly fewer artifacts (15.8% of glaucomatous eyes, 13.2% of normal eyes) compared to RNFL scans (61.7% of glaucomatous eyes, 25.4% of normal eyes) (glaucoma group: 95% CI, 34.1–57.5, P < 0.0001; normal group: 95% CI, 1.3–23.3, P = 0.03). Conclusions Compared to the most commonly used RNFL thickness scans, optic nerve volume scans less frequently require manual correction or repeat scanning to obtain accurate measurements. Translational Relevance This paper illustrates the potential for 3D OCT algorithms to improve in vivo imaging in glaucoma.

show abstract

Imaging in Myopic Glaucoma

Kim

2021

OCT Imaging in Glaucoma

View full text Add to dashboard Cite

Effects of Circumpapillary Retinal Nerve Fiber Layer Segmentation Error Correction on Glaucoma Diagnosis in Myopic Eyes

Abstract: A significant proportion of myopic eyes had RNFL segmentation errors in automated spectral-domain OCT analysis, decreasing glaucoma diagnostic capability of OCT RNFLT measurement.

Cited by 21 publications

References 15 publications

Reasons why OCT Global Circumpapillary Retinal Nerve Fiber Layer Thickness is a Poor Measure of Glaucomatous Progression

Reasons why OCT Global Circumpapillary Retinal Nerve Fiber Layer Thickness is a Poor Measure of Glaucomatous Progression

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

Imaging in Myopic Glaucoma

Contact Info

Product

Resources

About