Global optical coherence tomography measures for detecting the progression of glaucoma have fundamental flaws

Progressive Macular Vessel Density Loss and Visual Field Progression in Open-angle Glaucoma Eyes with Central Visual Field Damage

PURPOSE

To investigate the association between the longitudinal changes in both macular vessel density (mVD) and macular ganglion cell-inner plexiform layer thickness (mGCIPLT) and visual field (VF) progression (including central VF progression) in open-angle glaucoma (OAG) patients with central visual field (CVF) damage at different glaucoma stages.

DESIGN

Retrospective longitudinal study.

PARTICIPANTS

This study enrolled 223 OAG eyes with CVF loss at baseline classified as early-to-moderate (133 eyes) or advanced (90 eyes) stage based on the VF mean deviation (MD) (-10 dB).

METHODS

Serial mVDs at parafoveal and perifoveal sectors and mGCIPLT measurements were obtained using OCT angiography and OCT during a mean follow-up of 3.5 years. Visual field progression was determined using both the event- and trend-based analyses during follow-up.

MAIN OUTCOME MEASURES

Linear mixed-effects models were used to compare the rates of change in each parameter between VF progressors and nonprogressors. Logistic regression analyses were performed to determine the risk factors for VF progression.

RESULTS

In early-to-moderate stage, progressors showed significantly faster rates of change in the mGCIPLT (-1.02 vs. -0.47 μm/year), parafoveal (-1.12 vs. -0.40%/year), and perifoveal mVDs (-0.83 vs. -0.44%/year) than nonprogressors (all P < 0.05). In advanced stage cases, only the rates of change in mVDs (parafoveal: -1.47 vs. -0.44%/year; perifoveal: -1.04 vs. -0.27%/year; all P < 0.05) showed significant differences between the groups. By multivariable logistic regression analyses, the faster rate of mVD loss was a predictor of VF progression regardless of glaucoma stage, while the rate of mGCIPLT loss was significantly associated with VF progression only in early-to-moderate stage cases.

CONCLUSIONS

Progressive mVD loss is significantly associated with VF progression (including central VF progression) in the OAG eyes with CVF loss regardless of the glaucoma stage.

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

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.

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.

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.

Prediction of visual field defects from macular optical coherence tomography in glaucoma using cluster analysis

Purpose

To assess the accuracy of cluster analysis‐based models in predicting visual field (VF) defects from macular ganglion cell‐inner plexiform layer (GCIPL) measurements in glaucomatous and healthy cohorts.

Methods

GCIPL measurements were extracted from posterior pole optical coherence tomography (OCT), from locations corresponding to central VF test grids. Models incorporating cluster analysis methods and corrections for age and fovea to optic disc tilt were developed from 493 healthy participants, and 5th and 1st percentile limits of GCIPL thickness were derived. These limits were compared with pointwise 5th and 1st percentile limits by calculating sensitivities and specificities in an additional 40 normal and 37 glaucomatous participants, as well as applying receiver operating characteristic (ROC) curve analyses to assess the accuracy of predicting VF results from co‐localised GCIPL measurements.

Results

Clustered models demonstrated globally low sensitivity, but high specificity in the glaucoma cohort (0.28–0.53 and 0.77–0.91, respectively), and high specificity in the healthy cohort (0.91–0.98). Clustered models showed similar sensitivities and superior specificities compared with pointwise methods (0.41–0.65 and 0.71–0.98, respectively). There were significant differences in accuracy between clusters, with relatively poor accuracy at peripheral macular locations (p < 0.0001 for all comparisons).

Conclusions

Cluster analysis‐based models incorporating age correction and holistic consideration of fovea to optic disc tilt demonstrated superior performance in predicting VF results to pointwise methods in both glaucomatous and healthy eyes. However, relatively low sensitivity and poorer performance at the peripheral macula indicate that OCT in isolation may be insufficient to predict visual function across the macula accurately. With modifications to criteria for abnormality, the concepts suggested by the described normative models may guide prioritisation of VF assessment requirements, with the potential to limit excessive VF testing.

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.

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.