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.

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.

Detecting Established Glaucoma Using OCT Alone: Utilizing an OCT Reading Center in a Real-World Clinical Setting.

Purpose: We evaluated the ability of an optical coherence tomography (OCT)-based reading center for glaucoma (ORG) to detect established glaucoma using OCT alone. Methods: This study included eyes from 70 consecutive patients with established glaucoma (i.e. moderate or severe glaucoma according to the International Classification of Diseases [ICD]-10 guidelines) and 20 consecutive healthy subjects, who had no evidence of glaucomatous optic neuropathy (GON) or visual field (VF) loss in either eye. Using a standardized ORG quality assessment, 33 eyes were excluded due to media opacity (12), poor image quality (13), or epiretinal membrane (8). Of the remaining 147 eyes, 86 had established glaucoma and 36 were from healthy controls (total n = 122). Based on the OCT report alone and applying a previously described evaluation method, the presence of GON in each eye was determined by two masked ORG graders. The main outcome measures were sensitivity and specificity for detection of eyes with established glaucoma. Results: Of the 86 eyes with established glaucoma (average mean deviation [MD] = -10.9 ± 7.7 dB, range = -0.5 to -31.5 dB), only one eye (MD = -0.46) was missed (sensitivity = 98.8%). However, the other eye of this patient was correctly classified as GON. Therefore, at a patient level, sensitivity was 100%. None of the 36 healthy eyes was classified as GON by the ORG (specificity = 100%). Conclusions: An OCT-based reading center is able to identify eyes with established glaucoma using OCT alone with high sensitivity and specificity. Translational Relevance: Our study validates the use of a systematic OCT-based approach for glaucoma detection in a real-world setting.

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.

Monitoring Lesion Area Progression in Stargardt Disease: A Comparison of En Face Optical Coherence Tomography and Fundus Autofluorescence.

Purpose: To compare longitudinal changes in en face spectral domain-optical coherence tomography (SD-OCT) measurements of ellipsoid zone (EZ) and retinal pigment epithelium (RPE) loss to changes in the hypoautofluorescent and hyperautofluorescent (AF) areas detected with short-wavelength (SW)-AF in ABCA4-associated retinopathy. Methods: SD-OCT volume scans were obtained from 20 patients (20 eyes) over 2.6 ± 1.2 years (range 1-5 years). The EZ, and RPE/Bruch's membrane boundaries were segmented, and en face slab images generated. SubRPE and EZ slab images were used to measure areas of atrophic RPE and EZ loss. These were compared to longitudinal measurements of the hypo- and abnormal AF (hypoAF and surrounding hyperAF) areas. Results: At baseline, the en face area of EZ loss was significantly larger than the subRPE atrophic area, and the abnormal AF area was significantly larger than the hypoAF area. The median rate of EZ loss was significantly greater than the rate of increase in the subRPE atrophic area (1.2 mm2/yr compared to 0.5 mm2/yr). The median rate of increase in the abnormal AF area was significantly greater than the increase in the hypoAF area (1.6 mm2/yr compared to 0.6 mm2/yr). Conclusions: En face SD-OCT can be used to quantify changes in RPE atrophy and photoreceptor integrity. It can be a complementary or alternative technique to SW-AF with the advantage of monitoring EZ loss. The SW-AF results emphasize the importance of measuring changes in the hypo- and abnormal AF areas. Translational Relevance: The findings are relevant to the selection of outcome measures for monitoring ABCA4-associated retinopathy.

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.

Comparison between the Recommendations of Glaucoma Specialists and OCT Report Specialists for Further Ophthalmic Evaluation in a Community-Based Screening Study.

PURPOSE: To compare glaucoma referral patterns between glaucoma and OCT report specialists and to determine what influence, if any, a designated OCT reading could have on a glaucoma specialist's judgments. DESIGN: Retrospective, exploratory study. SUBJECTS: We included 483 eyes (243 individuals) from high-risk New York City neighborhoods screened as part of a mobile van glaucoma screening study from July 2017 to October 2017. METHODS: All participants underwent comprehensive testing, including visual acuity, commercial OCT imaging, gonioscopy, intraocular pressure, frequency-doubling testing, and funduscopic assessment. Three glaucoma specialists independently evaluated all the collected data to determine whether a further glaucoma workup referral was recommended. Two OCT report specialists evaluated only the OCT image for each eye using the commercial report as well as a specialized, customized report. In phase II, the glaucoma specialists then re-evaluated a subset of these eyes, this time with an OCT report specialist's judgments made available. MAIN OUTCOME MEASURES: Comparison of glaucoma specialist referrals made by glaucoma specialists versus OCT report specialists. RESULTS: Intergrader agreement between glaucoma specialists was 60% (κ = 0.43) and between report specialists was 95% (κ = 0.77). There was an agreement between a single OCT report specialist and the consensus (2 of 3) of glaucoma specialists in 74% of eyes (κ= 0.32). Of the eyes studied, 25% were referred for further glaucoma evaluation by the glaucoma specialists alone and 1% were referred for further glaucoma workup by only the report specialist. With the addition of the report specialist's judgments, referral pattern changes varied by glaucoma specialist but overall agreement increased to 85% (κ = 0.53). CONCLUSIONS: There was a fair level of agreement regarding glaucoma referral recommendations between glaucoma specialists with access to comprehensive screening data and OCT report specialists with access to only OCT data. Overall agreement increased when the designated OCT evaluation was made available to the glaucoma specialists. These results may aid in the design of future large-scale glaucoma screening studies.

The Role of Intraocular Pressure and Systemic Hypertension in the Progression of Glaucomatous Damage to the Macula.

PRCIS: Macular structural and functional parameters were better correlated with pressure-dependent glaucomatous damage than conventional parameters. Self-reported systemic hypertension (HTN) was not associated with structural or functional progression in this cohort. PURPOSE: The aim was to examine the relationships between intraocular pressure (IOP), systemic HTN, and glaucoma progression using structural testing with optical coherence tomography (OCT) and functional testing with visual field (VF). PATIENTS AND METHODS: A total of 191 eyes of 119 patients enrolled in a prospective, longitudinal study (Structural and Functional Progression of Glaucomatous Damage to the Macula study) with a diagnosis of glaucoma were analyzed. Patients were tested with 10-2 and 24-2 VF and spectral-domain OCT obtained at 4 to 6 month intervals. IOP from each visit was collected. Self-reported diagnoses of HTN were reported in 72 eyes (37%) in the patients included. Linear mixed effects regression was used to test the relationship between summary statistics from VF and OCT and HTN diagnosis. The goodness-of-fit of relationships was assessed with Bayesian information criterion. RESULTS: Mean follow-up IOP was most associated with the following OCT parameters: global macula ganglion cell layer (GCL), inferior macula GCL, mean macular vulnerability zone GCL, and mean less vulnerable zone macula GCL, and with the following VF parameters: 10-2 PSD and 10-2 MD. There was no significant difference in rates of progression between HTN and non-HTN patients for any OCT or VF parameter. Models with the best goodness-of-fit for the relationship between HTN and progression were the same as those observed for IOP. CONCLUSION: Macular structural and functional parameters are more sensitive to IOP in terms of glaucomatous progression when compared with more conventional parameters. While HTN was not significantly associated with progression using any parameter, macular structural and functional parameters had a better goodness-of-fit to model progression and may be useful as endpoints.

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.

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.

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.

Rationale and Development of an OCT-Based Method for Detection of Glaucomatous Optic Neuropathy.

A specific, sensitive, and intersubjectively verifiable definition of disease for clinical care and research remains an important unmet need in the field of glaucoma. Using an iterative, consensus-building approach and employing pilot data, an optical coherence tomography (OCT)-based method to aid in the detection of glaucomatous optic neuropathy was sought to address this challenge. To maximize the chance of success, we utilized all available information from the OCT circle and cube scans, applied both quantitative and semiquantitative data analysis methods, and aimed to limit the use of perimetry to cases where it is absolutely necessary. The outcome of this approach was an OCT-based method for the diagnosis of glaucomatous optic neuropathy that did not require the use of perimetry for initial diagnosis. A decision tree was devised for testing and implementation in clinical practice and research that can be used by reading centers, researchers, and clinicians. While initial pilot data were encouraging, future testing and validation will be needed to establish its utility in clinical practice, as well as for research.

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.

Structure-function analysis for macular surgery in patients with coexisting glaucoma.

PURPOSE: To develop methods to assess the effects of epiretinal membranes (ERM) and macular holes (MH) coexisting with glaucoma on pre-operative retinal structure and function and evaluate post-operative outcomes. METHODS: Seven eyes of 7 patients with glaucoma, 6 with ERMs and 1 with MH, were enrolled; 4 underwent vitrectomy for ERM and one for MH. Visual fields (VFs) and optical coherence tomography (OCT) scans were obtained pre- and post-operatively. The 10-2VF deviation map was overlayed on ganglion cell and inner plexiform layer (GCL + IPL) and retinal nerve fiber layer (RNFL) deviation maps derived from OCT macula and disc cube scans. Optic nerve circle scans were obtained to assess RNFL thickness, and OCT b-scans associated with VF defects were compared pre- and post-operatively. RESULTS: Examination of pre-operative VFs and OCT scans showed the importance of determining the extent to which glaucomatous damage contributed to VF loss; verifying automated segmentation of the GCL + IPL and RNFL; and assessing foveal anatomy. Evaluation of post-operative structure-function outcomes required correction of magnification changes in OCT scans and repeated follow-up visits to clarify the origin of VF changes. CONCLUSIONS: Pre-operative comparisons of VFs and OCT scans may be beneficial in guiding surgical planning, and evaluating outcomes, in eyes with glaucoma undergoing macular surgery.

Identifying and understanding optical coherence tomography artifacts that may be confused with glaucoma / Identificando e compreendendo os artefatos de tomografia de coerência óptica que podem ser confundidos com o glaucoma

ABSTRACT Optical coherence tomography is often used for detection of glaucoma as well as to monitor progression. This paper reviews the most common types of artifacts on the optical coherence tomography report that may be confused with glaucomatous damage. We mainly focus on anatomy-related artifacts in which the retinal layer segmentation and thickness measurements are correct. In such cases, the probability maps (also known as deviation maps) show abnormal (red and yellow) regions, which may mislead the clinician to assume disease is present. This is due to the anatomic variability of the individual, and the normative database must be taken into account.

RESUMO A tomografia de coerência óptica é frequentemente usada para detectar glaucoma, bem como para monitorar a progressão. Este artigo analisa os tipos mais comuns de artefatos no relatório de tomografia de coerência óptica que podem ser confundidos com danos glaucomatosos. Nós nos concentramos principalmente nos artefatos relacionados à anatomia em que a segmentação da camada da retina e as medidas de espessura estão corretas. Nesses casos, os mapas de probabilidade (também conhecidos como mapas de desvio) mostram regiões anormais (vermelho e amarelo), o que pode induzir o clínico em erro ao supor que a doença está presente. Isto se deve à variabilidade anatômica do indivíduo, e o banco de dados normativo deve ser levado em conta.

Strategies to Improve Convolutional Neural Network Generalizability and Reference Standards for Glaucoma Detection From OCT Scans.

Purpose: To develop and evaluate methods to improve the generalizability of convolutional neural networks (CNNs) trained to detect glaucoma from optical coherence tomography retinal nerve fiber layer probability maps, as well as optical coherence tomography circumpapillary disc (circle) b-scans, and to explore impact of reference standard (RS) on CNN accuracy. Methods: CNNs previously optimized for glaucoma detection from retinal nerve fiber layer probability maps, and newly developed CNNs adapted for glaucoma detection from optical coherence tomography b-scans, were evaluated on an unseen dataset (i.e., data collected at a different site). Multiple techniques were used to enhance CNN generalizability, including augmenting the training dataset, using multimodal input, and training with confidently rated images. Model performance was evaluated with different RS. Results: Training with data augmentation and training on confident images enhanced the accuracy of the CNNs for glaucoma detection on a new dataset by 5% to 9%. CNN performance was optimal when a similar RS was used to establish labels both for the training and the testing sets. However, interestingly, the CNNs described here were robust to variation in the RS. Conclusions: CNN generalizability can be improved with data augmentation, multiple input image modalities, and training on images with confident ratings. CNNs trained and tested with the same RS achieved best accuracy, suggesting that choosing a thorough and consistent RS for training and testing improves generalization to new datasets. Translational Relevance: Strategies for enhancing CNN generalizability and for choosing optimal RS should be standard practice for CNNs before their deployment for glaucoma detection.