Anatomical Features can Affect OCT Measures Used for Clinical Decisions and Clinical Trial Endpoints.

Purpose: To understand the association between anatomical parameters of healthy eyes and optical coherence tomography (OCT) circumpapillary retinal nerve fiber layer (cpRNFL) thickness measurements. Methods: OCT cpRNFL thickness was obtained from 396 healthy eyes in a commercial reference database (RDB). The temporal quadrant (TQ), superior quadrant (SQ), inferior quadrant (IQ), and global (G) cpRNFL thicknesses were analyzed. The commercial OCT devices code these values based on percentiles (red, <1%; yellow, ≥1% and <5%), after taking age and disc area into consideration. Four anatomical parameters were assessed: fovea-to-disc distance, an estimate of axial length, and the locations of the superior and the inferior peaks of the cpRNFL thickness curve. Pearson correlation values were obtained for the parameters and the thickness measures of each of the four cpRNFL regions, and t-tests were performed between the cpRNFL thicknesses coded as abnormal (red or yellow, <5%) versus normal (≥5%). Results: For each of the four anatomical parameters, the correlation with the thickness of one or more of the TQ, SQ, IQ, and G regions exceeded the correlation with age or disc area. All four parameters were significantly (P < 0.001) associated with the abnormal cpRNFL values. The significant parameters were not the same for the different regions; for example, a parameter could be negatively correlated for the TQ but positively correlated with the SQ or IQ. Conclusions: In addition to age and disc area, which are used for inferences in normative databases, four anatomical parameters are associated with cpRNFL thickness. Translational Relevance: Taking these additional anatomical parameters into consideration should aid diagnostic accuracy.

Understanding Patterns of Preserved Retinal Ganglion Cell Layer in Advanced Glaucoma as seen with OCT.

PRECIS: Using OCT, eyes with advanced glaucoma were found to have a wide range of patterns of damage that were consistent with the natural history of progression based upon a model of macular progression. PURPOSE: To understand the patterns of preserved retinal ganglion cells in eyes with advanced glaucoma using OCT and a model of progression of the central macula. METHODS: OCT GCL thickness was measured in 94 eyes with advanced glaucoma, defined as glaucomatous eyes with a 24-2 MD (mean deviation) worse than -12 dB. A commercial report supplied the GCL thickness in 6 sectors of the thick, donut-shaped GCL region around the fovea. For each eye, the 6 sectors were coded as green (within normal limits, WNL), yellow (≤5th, ≥1st percentile), or red (<1st percentile). RESULTS: In all 94 eyes, one or more of the 6 sectors of the donut were abnormal (red or yellow), while all 6 sectors were red in 52 (55%) of the eyes. On the other hand, 33 eyes had one or more sectors WNL (green). While the pattern of donut damage varied widely across these 33 eyes, 61 of the 66 hemiretinas were consistent with a temporal-to-nasal progression of damage within each hemiretina as predicted by our model. CONCLUSION: All eyes with advanced glaucoma had damage to the critically important central, donut-shaped GCL region. This region showed a wide range of patterns of damage, but these patterns were consistent with the natural history of progression based upon a model of macular progression. These results have implications for the clinical identification of macular progression, as well as for inclusion criteria for clinical trials seeking to preserve central macular function.

Glaucoma Detection Using Optical Coherence Tomography: Reviewing the Pitfalls of Comparison to Normative Data.

PRCIS: Optical coherence tomography is essential in managing glaucoma. This review describes various artifacts that originate from using a normative database to compare the individual's scans. This is a review paper regarding artifacts in optical coherence tomography imaging for glaucoma arising from using a normative database as a reference for healthy retinal nerve fiber layer and ganglion cell layer.

Improving glaucoma staging in clinical practice by combining the ICD-10 glaucoma severity classification system and optical coherence tomography.

OBJECTIVE: The International Classification of Disease, 10th revision (ICD-10) codes used for glaucoma severity classification are based on the 24-2 visual-field (VF) test. This study aim was to assess the added value of providing clinicians with optical coherence tomography (OCT) data, in addition to functional data, for glaucoma staging in clinical practice. EXPOSURE: Disease classification was determined for 54 glaucoma eyes, according to the principles of the ICD-10 guidelines. Eyes were independently graded in a masked fashion using the 24-2 VF test and 10-2 VF test, with and without OCT information. The reference standard (RS) for severity was determined using a previously published automated structure-function topographic agreement for glaucomatous damage using all available information. RESULTS: The RS classified eyes as mild, moderate and advanced in 3, 16 and 35 cases, respectively. Individual and combined 24-2 and 10-2 based gradings were significantly different from the RS (all P < 0.005), with Kappa agreements of 0.26, 0.45 and 0.42 respectively (P < 0.001). Classifications using OCT combined with either of the VF were not-significantly different from the RS (P > 0.3) with Kappa agreements of 0.56 and 0.57 respectively (P < 0.001). Combining 24-2 with OCT had less severity overestimations while 10-2 with OCT had fewer underestimations. CONCLUSION: Combining OCT and VF data provides better staging of glaucoma severity than VF data alone. The 24-2 and OCT combination seems most appropriate given the high concordance with the RS and less overestimation of severity. Incorporating structural information into disease stages allows clinicians to set more appropriate severity-based treatment targets for individual patients.

A Model of Progression to Help Identify Macular Damage Due to Glaucoma.

The central macula contains a thick donut shaped region of the ganglion cell layer (GCL) that surrounds the fovea. This region, which is about 12 degrees (3.5 mm) in diameter, is essential for everyday functions such as driving, reading, and face recognition. Here, we describe a model of progression of glaucomatous damage to this GCL donut. This model is based upon assumptions supported by the literature, and it predicts the patterns of glaucomatous damage to the GCL donut, as seen with optical coherence tomography (OCT). After describing the assumptions and predictions of this model, we test the model against data from our laboratory, as well as from the literature. Finally, three uses of the model are illustrated. One, it provides an aid to help clinicians focus on the essential central macula and to alert them to look for other, non-glaucomatous causes, when the GCL damage does not fit the pattern predicted by the model. Second, the patterns of progression predicted by the model suggest alternative end points for clinical trials. Finally, the model provides a heuristic for future research concerning the anatomic basis of glaucomatous damage.

Toward a Real-world Optical Coherence Tomography Reference Database: Optometric Practices as a Source of Healthy Eyes.

SIGNIFICANCE: The reports from optical coherence tomography (OCT) instruments depend on a reference database (RDB) of healthy eyes. Although these RDBs tend to be relatively small, they are time consuming and expensive to obtain. A larger RDB should improve our ability to screen for diseases such as glaucoma. PURPOSE: To explore the feasibility of developing a large RDB from OCT scans obtained by optometrists as part of their pre-test gathering of information, we tested the hypothesis that these scans are of sufficient quality for an RDB and contain a relatively low base rate of glaucoma and other pathologies (OPs). METHODS: Optical coherence tomography widefield (12 × 9 mm) scans from 400 eyes of 400 patients were randomly selected from a data set of more than 49,000 scans obtained from four optometry sites. Based on a commercial OCT report and a previously validated reading center method, two OCT graders categorized eyes as unacceptable to use for RDB, healthy (H), optic neuropathy consistent with glaucoma (ON-G), glaucoma suspect, or OPs. RESULTS: Overall, 29 (7.25%) of the eyes were graded unacceptable. Of the remaining 371 eyes, 352 (94.9%) were graded H. Although, for one site, 7.4% of the eligible eyes were graded ON-G, the average for the other three sites was 1.4%. Adjustments of the reading center criteria resulted in exclusion of more than half of these ON-G and OP eyes. CONCLUSIONS: The OCT scans obtained from optometry practices as part of their pre-test regimen are of sufficient quality for an RDB and contain a relatively low base rate of glaucoma and OPs. With the suggested exclusion criteria, the scans from optometry practices that are primarily involved in refraction and medical screening services should yield a large, real-world RDB with improved specificity and a base rate of glaucoma and/or OPs comparable with existing RDB.

Progression of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry.

Purpose: Performance comparison of optical coherence tomography (OCT) and visual field (VF) summary metrics for detecting glaucomatous progression. Methods: Thirty healthy control eyes (mean deviation [MD], -1.25 ± 2.03; pattern standard deviation [PSD] , 1.78 ± 0.77) and 91 patient eyes comprised of 54 glaucoma patients and 37 glaucoma suspects (MD, -1.58 ± 1.96; PSD, 2.82 ± 1.92) with a follow-up of at least 1 year formed a group to evaluate progression with event analyses (P-Event). A subset of eyes with an additional criterion of a minimum of four tests was used for trend analyses (P-Trend) (30 healthy controls and 73 patients). For P-Event analysis, test-retest variability thresholds (lower 5th percentile) were estimated with repeat tests within a 4-month period. A P-Event eye was considered a "progressor" if the difference between follow-up and baseline tests exceeded the variability thresholds. For the P-Trend analysis, rates of change were calculated based on least-squares regression. Negative rates with significant (P < 0.05) values were considered progressing. For a reference standard, 17 patient eyes were classified as definitely progressing based on clear evidence of structural and corresponding functional progression. Results: Isolated OCT and VF summary metrics were either inadequately sensitive or not too specific. Combinations of OCT-OCT and OCT-VF metrics markedly improved specificity to nearly 100%. A novel combination of OCT metrics (circumpapillary retinal nerve fiber layer and ganglion cell layer) showed high precision, with 13 of the 15 statistical progressors confirmed as true positives. Conclusions: Although relying solely on metrics is not recommended for clinical purposes, in situations requiring very high specificity and precision, combinations of OCT-OCT metrics can be used. Translational Relevance: All available OCT and VF metrics can miss eyes with progressive glaucomatous damage and/or can falsely identify progression in stable eyes.

The ICD-10 Glaucoma Severity Score Underestimates the Extent of Glaucomatous Optic Nerve Damage.

PURPOSE: To evaluate the International Classification of Disease, Tenth Revision (ICD-10) codes used for glaucoma severity classification, which are based on the location of visual field (VF) defects; given the known poor sensitivity of the 24-2 visual field test to early disease and macular damage, we hypothesized that the ICD-10 codes would not accurately reflect the extent of glaucomatous damage. DESIGN: Retrospective validity and reliability analysis. METHODS: We evaluated 80 eyes with glaucomatous optic neuropathy (GON). Masked reviewers assigned an ICD-10 severity grade based on 24-2 VF. Two additional masked examiners determined the presence of optical coherence tomography (OCT) structural damage in each hemifield and/or central 5 degrees to define an OCT-based equivalent ICD-10 classification. RESULTS: A total of 80 eyes with GON were classified as mild, moderate and advanced in 15, 23, and 42 cases, respectively, based on the 24-2 VF, and in 6, 7, and 67 cases, respectively, based on OCT. The OCT classifications were more severe in 29 of 80 cases (36%). In 33 cases (41.3%), macular damage detected by OCT was missed by the 24-2. In 4 of 80 cases (5%), the VF overestimated the severity, likely due to variability of the 24-2 test. CONCLUSIONS: The ICD-10 system relies solely on damage seen on the 24-2 and as provides a 24-2 functional score rather than a "glaucoma" severity score. OCT revealed wide variation of damage across grades, with a significant proportion of the eyes showing macular structural damage missed with the 24-2 VF. Adding OCT information to the ICD-10 system would help it to more accurately reflect the extent of glaucomatous damage.

Test of a Retinal Nerve Fiber Bundle Trajectory Model Using Eyes With Glaucomatous Optic Neuropathy.

Purpose: To test a model of retinal nerve fiber bundle trajectories that predicts the arcuate-shaped patterns seen on optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability/deviation maps (p-maps) in glaucomatous eyes. Methods: Thirty-one glaucomatous eyes from a database of 250 eyes had clear arcuate-shaped patterns on RNFL p-maps derived from an OCT cube scan. The borders of the arcuate patterns were extracted from the RNFL p-maps. Next, the trajectories from an arcuate model were compared against these borders via a normalized root-mean-square difference analysis. The model's parameter, ß, was varied, and the best-fitting, initial clock-hour position of the trajectory to the border was found for each ß. Finally, the regions, as determined by the arcuate border's best-fit, initial clock-hour positions, were compared against the abnormal regions on the circumpapillary retinal nerve fiber layer (cpRNFL) profile. Results: The arcuate model's mean ßSup and ßInf parameters minimized large differences between the trajectories and the arcuate borders on the RNFL p-maps. Furthermore, on average, 68% of the cpRNFL regions defined by the arcuate border's best-fit, initial clock-hour positions were abnormal (i.e., below the ≤5% threshold). Conclusions: The arcuate model performed well in predicting the borders of arcuate patterns seen on RNFL p-maps. It also predicted the associated abnormal regions of the cpRNFL thickness plots. Translational Relevance: This model should prove useful in helping clinicians understand topographical comparisons among different OCT representations and should improve structure-structure, as well as structure-function agreement analyses.

The OCT RNFL Probability Map and Artifacts Resembling Glaucomatous Damage.

Purpose: The purpose of this study was to improve the diagnostic ability of the optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability (p-) map by understanding the frequency and pattern of artifacts seen on the p-maps of healthy control (HC) eyes resembling glaucomatous damage. Methods: RNFL p-maps were generated from wide-field OCT cube scans of 2 groups of HC eyes, 200 from a commercial normative group (HC-norm) and 54 from a prospective study group, as well as from 62 patient eyes, which included 32 with early glaucoma (EG). These 32 EG eyes had 24-2 mean deviation (MD) better than -6 dB and perimetric glaucoma as defined by 24-2 and 10-2 criteria. For the HC groups, "glaucoma-like" arcuates were defined as any red region near the temporal half of the disc. Results: Seven percent of the 200 HC-norm and 11% of the 54 HC RNFL p-maps satisfied the definition of "glaucoma-like," as did all the patients' p-maps. The HC p-maps showed two general patterns of abnormal regions, "arcuate" and "temporal quadrant," and these patterns resembled those seen on some of the RNFL p-maps of the EG eyes. A "vertical midline" rule, which required the abnormal region to cross the vertical midline through the fovea, had a specificity of >99%, and a sensitivity of 75% for EG and 93% for moderate to advanced eyes. Conclusions: Glaucoma-like artifacts on RNFL p-maps are relatively common and can masquerade as arcuate and/or widespread/temporal damage. Translational Relevance: A vertical midline rule had excellent specificity. However, other OCT information is necessary to obtain high sensitivity, especially in eyes with early glaucoma.

Detection of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry.

Purpose: To evaluate the diagnostic performance of optical coherence tomography (OCT) and visual field (VF) summary statistics (metrics) that are available in OCT and VF reports. Methods: OCT disc and macular scans and 24-2 and 10-2 VFs were obtained from 56 healthy control (HC) eyes/participants and 61 eyes/patients with 24-2 mean deviation of better than -6 dB. All metrics were obtained from OCT radial, circle, and posterior pole cube scans and 24-2 and 10-2 VFs. Their diagnostic performances were evaluated, in isolation and in combinations. For specificity, the 56 HC eyes were used. For sensitivity, 40 of the 61 patient eyes were deemed likely glaucomatous based on an automated topographic method that evaluates structure-function (S-F) agreement. Any 1 of these 40 eyes not judged as abnormal by any given metric was considered a false negative. Results: All single OCT and VF metrics misclassified HCs as glaucomatous and missed likely glaucomatous eyes. The best performing single metric was the temporal inferior thickness of the 3.5-mm circle scan, with 96% specificity and 83% sensitivity. Combinations of OCT-OCT and OCT-VF metrics markedly improved specificity. A newly proposed metric that evaluates structure-structure (S-S) agreement at a hemifield level had the highest accuracy. This S-S metric had 98% specificity and 80% sensitivity. Conclusions: OCT and VF metrics, single or in combinations, have only moderate sensitivity for eyes with early glaucoma. Translational Relevance: OCT and VF metrics combinations evaluating S-S or S-F agreement can be highly specific, which is an important implication for clinical and research purposes.

The 24-2 Visual Field Guided Progression Analysis Can Miss the Progression of Glaucomatous Damage of the Macula Seen Using OCT.

PURPOSE: To better understand the efficacy of the 24-2 guided progression analysis (GPA) in the detection of progression in eyes with early glaucoma (i.e., 24-2 mean deviation [MD] better than -6 dB) by comparing 24-2 GPA with a reference standard (RS) based on a combination of OCT and 24-2 and 10-2 visual field (VF) information. DESIGN: Cross-sectional study. PARTICIPANTS: Ninety-nine eyes from 99 individuals, including 70 suspected or early glaucomatous eyes (24-2 MD better than -6 dB) and 29 healthy controls (HCs). METHODS: All the eyes had at least 4 OCT and VF test dates over a period that ranged from 12 to 59 months. The 24-2 VF tests included 2 baseline tests and at least 2 follow-up tests. The 2 baseline tests were performed within an average of 5.6 days (median, 7 days), and the last follow-up test was performed at least 1 year after the first baseline visit. MAIN OUTCOME MEASURES: A commercial 24-2 GPA software, with default settings, characterized the eyes as having "likely progression" (LP) or "possible progression" (PP); both were considered "progressing" for this analysis. For RS, 3 authors graded progression using strict criteria and a combination of a custom OCT progression report and commercial 24-2 and 10-2 GPA reports for the same test dates as GPA. RESULTS: The reference standard identified 10 (14%) of the 70 patient eyes and none of the HC eyes as having progression. The 24-2 guided progression analysis identified 13 of the 70 patient eyes as having progression (PP or LP). However, it correctly classified only 4 (40%) of the 10 RS progressors. All 6 of the RS progressors missed by the 24-2 GPA showed progression in the macula. In addition, the 24-2 GPA identified 2 of the 29 HC eyes as progressors and 9 patient eyes without progression based on the RS. CONCLUSIONS: In eyes with early glaucoma (i.e., 24-2 MD, > -6 dB) in this study, the 24-2 GPA missed progression seen using OCT and exhibited a relatively high rate of false positives. Furthermore, the region progressing typically included the macula. The results suggest that including OCT and/or 10-2 VFs should improve the detection of progression.

Distinguishing Healthy From Glaucomatous Eyes With Optical Coherence Tomography Global Circumpapillary Retinal Nerve Fiber Thickness in the Bottom 5th Percentile.

PRCIS: Two novel, quantitative metrics, and 1 traditional metric were able to distinguish between many, but not all healthy and glaucomatous eyes in the bottom 5th percentile of global circumpapillary retinal nerve fiber layer (cpRNFL) thickness. PURPOSE: To test the hypothesis that objective optical coherence tomography measures can distinguish between a healthy control with global cpRNFL thickness within the lower 5% of normal and a glaucoma patient with an equivalent cpRNFL thickness. PATIENTS AND METHODS: A total of 37 healthy eyes from over 700 normative eyes fell within the bottom 5th percentile in global cpRNFL thickness. The global cpRNFL thickness of 35 glaucomatous eyes from 188 patients fell within the same range. For the traditional methods, the global cpRNFL thickness percentile and the global ganglion cell layer (GCL) thickness percentile for the central ±8 degrees, were calculated for all 72 eyes. For the novel cpRNFL method, the normalized root mean square (RMS) difference between the cpRNFL thickness profile and the global thickness-matched normative thickness profile was calculated. For the superior-inferior (SI) GCL method, the normalized mean difference in superior and inferior GCL thickness was calculated for the central ±8 degrees. RESULTS: The best quantitative metric, the RMS cpRNFL method, had an accuracy of 90% compared with 81% for the SI GCL and 81% for the global GCL methods. As expected, the global cpRNFL had the worst accuracy, 72%. Similarly, the RMS cpRNFL method had an area under the curve of 0.93 compared with 0.83 and 0.84 for the SI GCL and global GCL methods, respectively. The global cpRNFL method had the worst area under the curve, 0.75. CONCLUSION: Quantitative metrics can distinguish between most of the healthy and glaucomatous eyes with low global cpRNFL thickness. However, even the most successful metric, RMS cpRNFL, missed some glaucomatous eyes.

Detecting glaucoma with only OCT: Implications for the clinic, research, screening, and AI development.

A method for detecting glaucoma based only on optical coherence tomography (OCT) is of potential value for routine clinical decisions, for inclusion criteria for research studies and trials, for large-scale clinical screening, as well as for the development of artificial intelligence (AI) decision models. Recent work suggests that the OCT probability (p-) maps, also known as deviation maps, can play a key role in an OCT-based method. However, artifacts seen on the p-maps of healthy control eyes can resemble patterns of damage due to glaucoma. We document in section 2 that these glaucoma-like artifacts are relatively common and are probably due to normal anatomical variations in healthy eyes. We also introduce a simple anatomical artifact model based upon known anatomical variations to help distinguish these artifacts from actual glaucomatous damage. In section 3, we apply this model to an OCT-based method for detecting glaucoma that starts with an examination of the retinal nerve fiber layer (RNFL) p-map. While this method requires a judgment by the clinician, sections 4 and 5 describe automated methods that do not. In section 4, the simple model helps explain the relatively poor performance of commonly employed summary statistics, including circumpapillary RNFL thickness. In section 5, the model helps account for the success of an AI deep learning model, which in turn validates our focus on the RNFL p-map. Finally, in section 6 we consider the implications of OCT-based methods for the clinic, research, screening, and the development of AI models.

Detecting Progression in Advanced Glaucoma: Are Optical Coherence Tomography Global Metrics Viable Measures?

SIGNIFICANCE: Optical coherence tomography (OCT) summary measures have been suggested as a way to detect progression in eyes with advanced glaucoma. Here, we show that these measures have serious flaws largely due to segmentation errors. However, inspection of the images and thickness maps can be clinically useful. PURPOSE: This study aimed to test the hypothesis that recently suggested global OCT measures for detecting progression in eyes with advanced progression are seriously affected by segmentation mistakes and other errors that limit their clinical utility. METHODS: Forty-five eyes of 38 patients with a 24-2 mean deviation worse than -12 dB had at least two spectral domain OCT sessions (0.8 to 4.4 years apart) with 3.5-mm circle scans of the disc and cube scans centered on the fovea. Average (global) circumpapillary retinal nerve fiber layer thickness, GcRNFL, and ganglion cell plus inner plexiform layer thickness, GGCLP, were obtained from the circle and cube scan, respectively. To evaluate progression, ΔGcRNFL was calculated for each eye as the GcRNFL value at time 2 minus the value at time 1, and ΔGGCLP was calculated in a similar manner. The b-scans of the six eyes with the highest and lowest ΔGcRNFL and ΔGGCLP values were examined for progression as well as segmentation, alignment, and centering errors. RESULTS: Progression was a major factor in only 7 of the 12 eyes with the most negative values of either ΔGcRNFL or ΔGGCLP, whereas segmentation played a role in 8 eyes and was the major factor in all 12 eyes with the largest positive values. In addition, alignment (one eye) and other (three eyes) errors played a secondary role in four of the six eyes with the most negative ΔGcRNFL values. CONCLUSIONS: For detecting the progression of advanced glaucoma, common summary metrics have serious flaws largely due to segmentation errors, which limit their utility in clinical and research settings.

A Topographic Comparison of OCT Minimum Rim Width (BMO-MRW) and Circumpapillary Retinal Nerve Fiber Layer (cRNFL) Thickness Measures in Eyes With or Suspected Glaucoma.

PRéCIS:: Bruch's membrane opening-minimum rim width (BMO-MRW) and circumpapillary retinal nerve fiber layer (cRNFL) thickness measures may be improved by comparing probability levels and accounting for blood vessel locations. PURPOSE: To understand the differences between 2 optical coherence tomography measures of glaucomatous damage: the BMO-MRW and cRNFL thickness. MATERIALS AND METHODS: Optical coherence tomography circle scans were obtained for an early glaucoma group (EG) of 88 eyes (88 patients) with 24-2 mean deviation better than -6.0 dB, and a broader group (BG) of 188 eyes (110 patients) with 24-2 mean deviation from -0.15 to -27.0 dB. On the basis of a commercial report, the cRNFL and BMO-MRW of each hemidisc was classified as abnormal if either of the 2 superior (inferior) sectors, temporal superior and nasal superior (temporal inferior and nasal inferior), was yellow or red (P<5%); and as normal if both were green (P≥5%). In addition, a post hoc analysis identified the reasons for disagreements on the basis of the presence (or absence) of glaucomatous damage at a hemidisc level (consensus of 4 experts). RESULTS: The BMO-MRW and cRNFL measures agreed in 81.9% (broader group) and 73.9% (EG) of the hemidiscs. In both groups, an abnormal-BMO-MRW/normal-cRNFL disagreement was as common as a normal-BMO-MRW/abnormal-cRNFL. Of the 46 EG hemidisc disagreements, the number of "mistakes" for BMO-MRW (28) was nonsignificantly higher than for cRNFL (18) (P=0.15). Primary causes for disagreement were as follows: borderline significance level, a local defect, and aberrant blood vessel location. CONCLUSIONS: Although BMO-MRW and cRNFL measures agreed in the majority of hemidiscs, they still disagreed in over 25% of the EG hemidiscs. These measures may be improved by comparing actual probability levels and accounting for blood vessel locations. However, both can miss information available on retinal ganglion cell/retinal nerve fiber layer probability maps.