Combining OCT and OCTA for Focal Structure-Function Modeling in Early Primary Open-Angle Glaucoma

Abilities of circumpapillary retinal nerve fiber layer thickness and vascular density to discriminate stages in primary open-angle glaucoma

PURPOSE

To clarify the abilities of circumpapillary retinal nerve fiber layer thickness (cpRNFLT) obtained by optical coherence tomography (OCT) and circumpapillary vessel density (cpVD) measured by OCT-angiography to distinguish different stages in primary open-angle glaucoma determined by 24-2 or 30-2 static visual field (VF) testing.

METHODS

This retrospective study includes 25 healthy normal eyes of 25 subjects and 87 primary open-angle glaucoma eyes of 87 patients. Areas under the receiver operating characteristic curves (AUROC) were evaluated for determining glaucoma stages using cpRNFLT and cpVD. The absolute errors of the estimated mean total deviation (mTD) using optimal models with cpRNFLT and cpVD were also compared.

RESULTS

The AUROCs for discriminating glaucomatous eyes from normal eyes was significantly higher for cpRNFLT than the respective AUROCs for cpVD (0.969 [95% CI 0.939 to 0.998] vs. 0.872 [95% CI 0.806 to 0.938], p = 0.006), whereas cpVD had significantly higher AUROC for discriminating severe glaucoma eyes from moderate glaucoma eyes than cpRNFLT (0.771 [95% CI 0.655 to 0.886] vs. 0.578 [95% CI 0.420 to 0.736], p = 0.022). The mean absolute error in estimating mTD using both cpRNFLT and cpVD was significantly less than the error using cpRNFLT alone (4.56 ± 3.76 dB vs. 5.39 ± 4.00 dB, p = 0.027).

CONCLUSION

Our results suggest that cpVD is better for follow-ups after moderate stage. The combination of cpRNFLT and cpVD may improve VF estimation compared to cpRNFLT alone.

Detection and agreement of event-based OCT and OCTA analysis for glaucoma progression

OBJECTIVE

To examine event-based glaucoma progression using optical coherence tomography (OCT) and OCT angiography (OCTA).

METHODS

In this retrospective study, glaucoma eyes with ≥2-year and 4-visits of OCT/OCTA imaging were included. Peripapillary capillary density (CD) and retinal nerve fibre layer thickness (RNFL) were obtained from 4.5 mm × 4.5 mm optic nerve head (ONH) scans. Event-based OCT/OCTA progression was defined as decreases in ONH measurements exceeding test-retest variability on ≥2 consecutive visits. Visual field (VF) progression was defined as significant VF mean deviation worsening rates on ≥2 consecutive visits. Inter-instrument agreement on progression detection was compared using kappa(κ) statistics.

RESULTS

Among 147 eyes (89 participants), OCTA and OCT identified 33(22%) and 25(17%) progressors, respectively. They showed slight agreement (κ = 0.06), with 7(5%) eyes categorized as progressors by both. When incorporating both instruments, the rate of progressors identified increased to 34%. Similar agreement was observed in diagnosis- and severity-stratified analyses (κ < 0.10). Compared to progressors identified only by OCT, progressors identified only by OCTA tended to have thinner baseline RNFL and worse baseline VF. VF progression was identified in 11(7%) eyes. OCT and VF showed fair agreement (κ = 0.26), with 6(4%) eyes categorized as progressors by both. OCTA and VF showed slight agreement (κ = 0.08), with 4(3%) eyes categorized as progressors by both.

CONCLUSIONS

OCT and OCTA showed limited agreement on event-based progression detection, with OCT showing better agreement with VF. Both OCT and OCTA detected more progressors than VF. OCT and OCTA may provide valuable, yet different and complementary, information about glaucoma progression.

Optical coherence tomography angiography in glaucoma

The use of optical coherence tomography angiography (OCTA) holds significant promise for optometrists in the diagnosis and management of glaucoma. It offers reliable differentiation of glaucomatous eyes from healthy ones and extends monitoring capabilities for advanced cases. OCTA represents a valuable addition to traditional assessment methods, particularly in complex cases. Glaucoma, a major cause of irreversible blindness, is traditionally diagnosed using structural and functional metrics. With growing interest, OCTA is being explored to diagnose, monitor, and manage glaucoma. This review focuses on the application of OCTA in glaucoma patients. A database search was carried out using Embase Elsevier (n = 664), PubMed (n = 574), and Cochrane Central Register of Controlled Trials (n = 19) on 15 August 2023. After deduplication and screening, 272 original papers were included in the narrative review. Inclusion criteria comprised English-language original studies on OCTA use in human glaucoma patients, with or without healthy controls. Exclusion criteria encompassed animal studies, in-vivo/in-vitro research, reviews, and congress abstracts. OCTA has good repeatability and reproducibility. OCTA metrics have good discriminatory power to differentiate glaucomatous eyes from healthy eyes and show strong associations with structural changes and visual field defects. OCTA can extend the monitoring of advanced glaucoma, addressing the 'floor effect' of traditional structural measurements. OCTA metrics can be affected by the choice of OCTA machine, post-image processing algorithms, systemic diseases, and ocular factors. Image artefacts can affect the accuracy of OCTA measurements, and proper scan quality evaluation is crucial to ensure reliable results. Additionally, artificial intelligence techniques offer promise for enhancing the diagnostic accuracy of OCTA by combining data from various retinal layers and regions. OCTA complements traditional methods in assessing glaucoma, especially in challenging cases, providing valuable insights for detection and management. Further research and clinical validation are needed to integrate OCTA into routine practice.

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements

PURPOSE

To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements.

DESIGN

Development and validation of a deep learning model.

METHODS

A total of 1051 10-2 VF OCTA pairs from healthy, glaucoma suspects, and glaucoma eyes were included. DL models were trained on en face macula VD images from OCTA to estimate 10-2 mean deviation (MD), pattern standard deviation (PSD), 68 total deviation (TD) and pattern deviation (PD) values and compared with a linear regression (LR) model with the same input. Accuracy of the models was evaluated by calculating the average mean absolute error (MAE) and the R2 (squared Pearson correlation coefficients) of the estimated and actual VF values.

RESULTS

DL models predicting 10-2 MD achieved R2 of 0.85 (95% confidence interval [CI], 74-0.92) for 10-2 MD and MAEs of 1.76 dB (95% CI, 1.39-2.17 dB) for MD. This was significantly better than mean linear estimates for 10-2 MD. The DL model outperformed the LR model for the estimation of pointwise TD values with an average MAE of 2.48 dB (95% CI, 1.99-3.02) and R2 of 0.69 (95% CI, 0.57-0.76) over all test points. The DL model outperformed the LR model for the estimation of all sectors.

CONCLUSIONS

DL models enable the estimation of VF loss from OCTA images with high accuracy. Applying DL to the OCTA images may enhance clinical decision making. It also may improve individualized patient care and risk stratification of patients who are at risk for central VF damage.

Neurovascular segregation of the retinal nerve fiber layer in glaucoma

The imaging data of one eye from 154 healthy and 143 glaucoma participants were acquired to evaluate the contributions of the neuronal and vascular components within the retinal nerve fiber layer (RNFL) for detecting glaucoma and modeling visual field loss through the use of optical coherence tomography (OCT) and OCT angiography. The neuronal and vascular components within the circumpapillary RNFL were independently evaluated. In healthy eyes, the neuronal component showed a stronger association with age (r = -0.52, p < 0.001) compared to measured RNFL thickness (r = -0.46, p < 0.001). Using the neuronal component alone improved detection of glaucoma (AUC: 0.890 ± 0.020) compared to measured RNFL thickness (AUC: 0.877 ± 0.021; χ2 = 5.54, p = 0.019). Inclusion of the capillary components with the sectoral neuronal component resulted in a significant improvement in glaucoma detection (AUC: 0.927 ± 0.015; χ2 = 15.34, p < 0.001). After adjusting for potential confounders, AUC increased to 0.952 ± 0.011. Results from modeling visual field loss in glaucoma eyes suggest that visual field losses associated with neuronal thinning were moderated in eyes with a larger capillary component. These findings suggest that segregation of the neurovascular components could help improve understanding of disease pathophysiology and affect disease management in glaucoma.

Influence of Refractive Error on Circumpapillary Structure-Function Versus Vessel Density-Function Relationships in Open Angle Glaucoma

PRCIS

In Japanese open angle glaucoma (OAG) eyes correlation of 30-degree visual field mean deviation (MD) and visual field index (VFI) with circumpapillary vessel density is systematically stronger than that with circumpapillary retinal nerve fiber layer thickness (RNFLT), and is preserved in myopia and high myopia.

PURPOSE

The purpose of this study was to investigate the influence of refractive error on the relationship between circumpapillary retinal nerve fiber layer thickness (cpRNFLT) and circumpapillary vessel density (cpVD), respectively, and global visual field parameters in Japanese open angle glaucoma (OAG) eyes.

MATERIAL AND METHODS

One eye of 81 Japanese OAG patients (spherical equivalent refractive error: +3.0 to -9.0 D) underwent 360-degree cpRNFLT and cpVD measurements with Cirrus HD 5000-AngioPlex optical coherence tomography and 30-2 Humphrey visual field testing for mean deviation (MD) and visual field index (VFI) within 1 month. Correlations were determined for the whole population and each refractive error subgroups, separately: emmetropia/hyperopia (n=24), mild (n=18), moderate (n=20), and high myopia (n=19).

RESULTS

For the total population, significant strong to very strong correlations were found between MD, VFI, and both cpRNFLT and cpVD, respectively, with consistently higher r -values for cpVD (highest r -values: 0.532 for cpRNFLT, P <0.001; 0.722 for cpVD, P <0.001). Of the refractive subgroups, statistically significant correlations between cpRNFLT and the visual field parameters were maintained only in the hyperopia/emmetropia and moderate myopia groups. In contrast, statistically significant, strong to very strong correlations between cpVD and both MD and VFI, always exceeding the corresponding r -values found for cpRNFLT were found in all refractive subgroups, with r -values ranging between 0.548 ( P =0.005) and 0.841 ( P <0.001).

CONCLUSIONS

Our results suggest that in Japanese OAG eyes the relationship of MD and VFI with cpVD is strong. It is systematically stronger than that with cpRNFLT and preserved in each conventional refractive error category including high myopia.

Combined Model of OCT Angiography and Structural OCT Parameters to Predict Paracentral Visual Field Loss in Primary Open-Angle Glaucoma

PURPOSE

To assess a model combining OCT angiography (OCTA) and OCT parameters to predict the severity of paracentral visual field (VF) loss in primary open-angle glaucoma (POAG).

DESIGN

Cross-sectional study.

PARTICIPANTS

Forty-four patients with POAG and 42 control subjects underwent OCTA and OCT imaging with a swept-source OCT device.

METHODS

The circumpapillary microvasculature was quantified for vessel density (cpVD) and flow (cpFlow) after delineation of Bruch's membrane opening and removal of large vessels. Retinal nerve fiber layer thickness (RNFLT) and Bruch's membrane opening-minimum rim width (BMO-MRW) were measured from structural OCT. Paracentral total deviation (PaTD) was defined as the average of the total deviation values within the central 10 degrees on Humphrey VF testing (24-2) for upper and lower hemifields. The OCT and OCTA parameters were measured in the affected hemisphere corresponding to the hemifield with lower PaTD for POAG patients. Models were created to predict affected PaTD based on RNFLT alone; RNFLT and BMO-MRW; OCTA alone; or RNFLT, BMO-MRW and OCTA parameters. The models were compared using coefficient of determination (r2) and Bayesian information criterion (BIC) score. Bayesian information criterion decrease of ≥6 indicates strong evidence for model improvement.

MAIN OUTCOME MEASURES

Performance of models containing OCT and OCTA parameters in predicting PaTD.

RESULTS

Patients with POAG and controls were similar in age and sex (65.9 ± 9.5 years and 38.4% male overall, P ≥ 0.56 for both). Average RNFLT, minimum RNFLT, average BMO-MRW, minimum BMO-MRW, cpVD, and cpFlow were all significantly lower (all P < 0.001) in the affected hemisphere in patients with POAG than in controls. In patients with POAG, the average mean deviation was -4.33 ± 3.25 dB; the PaTD of the affected hemifield averaged -4.55 ± 5.26 dB and correlated significantly with both OCTA and structural OCT parameters (r ≥ 0.43, P ≤ 0.004 for all). The model containing RNFLT, BMO-MRW, and OCTA parameters was superior in predicting affected PaTD (r2 = 0.47, BIC = 290.7), with higher r2 and lower BIC compared with all 3 other models.

CONCLUSIONS

A combined model of OCTA and structural OCT parameters can predict the severity of paracentral VF loss of the affected hemifield, supporting clinical utility of OCTA in patients with POAG with paracentral VF loss.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Heterogeneity of Ocular Hemodynamic Biomarkers among Open Angle Glaucoma Patients of African and European Descent

This study investigated the heterogeneity of ocular hemodynamic biomarkers in early open angle glaucoma (OAG) patients and healthy controls of African (AD) and European descent (ED). Sixty OAG patients (38 ED, 22 AD) and 65 healthy controls (47 ED, 18 AD) participated in a prospective, cross-sectional study assessing: intraocular pressure (IOP), blood pressure (BP), ocular perfusion pressure (OPP), visual field (VF) and vascular densities (VD) via optical coherence tomography angiography (OCTA). Comparisons between outcomes were adjusted for age, diabetes status and BP. VF, IOP, BP and OPP were not significantly different between OAG subgroups or controls. Multiple VD biomarkers were significantly lower in OAG patients of ED (p < 0.05) while central macular VD was lower in OAG patients of AD vs. OAG patients of ED (p = 0.024). Macular and parafoveal thickness were significantly lower in AD OAG patients compared to those of ED (p = 0.006-0.049). OAG patients of AD had a negative correlation between IOP and VF index (r = -0.86) while ED patients had a slightly positive relationship (r = 0.26); difference between groups (p < 0.001). Age-adjusted OCTA biomarkers exhibit significant variation in early OAG patients of AD and ED.

Combining Optical Coherence Tomography and Optical Coherence Tomography Angiography Longitudinal Data for the Detection of Visual Field Progression in Glaucoma

PURPOSE

To use longitudinal optical coherence tomography (OCT) and OCT angiography (OCTA) data to detect glaucomatous visual field (VF) progression with a supervised machine learning approach.

DESIGN

Prospective cohort study.

METHODS

One hundred ten eyes of patients with suspected glaucoma (33.6%) and patients with glaucoma (66.4%) with a minimum of 5 24-2 VF tests and 3 optic nerve head and macula images over an average follow-up duration of 4.1 years were included. VF progression was defined using a composite measure including either a "likely progression event" on Guided Progression Analysis, a statistically significant negative slope of VF mean deviation or VF index, or a positive pointwise linear regression event. Feature-based gradient boosting classifiers were developed using different subsets of baseline and longitudinal OCT and OCTA summary parameters. The area under the receiver operating characteristic curve (AUROC) was used to compare the classification performance of different models.

RESULTS

VF progression was detected in 28 eyes (25.5%). The model with combined baseline and longitudinal OCT and OCTA parameters at the global and hemifield levels had the best classification accuracy to detect VF progression (AUROC = 0.89). Models including combined OCT and OCTA parameters had higher classification accuracy compared with those with individual subsets of OCT or OCTA features alone. Including hemifield measurements significantly improved the models' classification accuracy compared with using global measurements alone. Including longitudinal rates of change of OCT and OCTA parameters (AUROCs = 0.80-0.89) considerably increased the classification accuracy of the models with baseline measurements alone (AUROCs = 0.60-0.63).

CONCLUSIONS

Longitudinal OCTA measurements complement OCT-derived structural metrics for the evaluation of functional VF loss in patients with glaucoma.

Applications of Artificial Intelligence and Deep Learning in Glaucoma

Diagnosis and detection of progression of glaucoma remains challenging. Artificial intelligence-based tools have the potential to improve and standardize the assessment of glaucoma but development of these algorithms is difficult given the multimodal and variable nature of the diagnosis. Currently, most algorithms are focused on a single imaging modality, specifically screening and diagnosis based on fundus photos or optical coherence tomography images. Use of anterior segment optical coherence tomography and goniophotographs is limited. The majority of algorithms designed for disease progression prediction are based on visual fields. No studies in our literature search assessed the use of artificial intelligence for treatment response prediction and no studies conducted prospective testing of their algorithms. Additional challenges to the development of artificial intelligence-based tools include scarcity of data and a lack of consensus in diagnostic criteria. Although research in the use of artificial intelligence for glaucoma is promising, additional work is needed to develop clinically usable tools.

Multipressure Dial Goggle Effects on Circumpapillary Structure and Microvasculature in Glaucoma Patients

PURPOSE

To evaluate the effects of pressure changes induced by a multipressure dial (MPD) on circumpapillary retinal nerve fiber layer (RNFL) and capillary density (CD) measurements in patients with glaucoma using OCT angiography (OCTA).

DESIGN

Prospective interventional study.

PARTICIPANTS

Twenty-four patients with primary open-angle glaucoma.

METHODS

One eye of each patient underwent negative pressure application with the MPD. The MPD alters intraocular pressure (IOP) relative to atmospheric pressure by generating a negative pressure vacuum within a goggle chamber that is placed over the eye. Each participant underwent serial high density OCTA imaging (AngioVue) of the optic nerve head at different negative pressure increments of -5 mmHg, starting from 0 mmHg, ending at -20 mmHg, and then returning to baseline. Images were acquired after 2 minutes of sustained negative pressure at each target pressure to allow for stabilization of the retinal structures and microvasculature. The RNFL thickness and CD measurements were automatically calculated using the native AngioVue software, and then exported for analysis.

MAIN OUTCOME MEASURES

The influence of different levels of negative pressure on circumpapillary RNFL thickness and CD measurements, assessed by a linear mixed-effects model with repeated measures.

RESULTS

The mean (± SD) age was 71.0 years (± 7.8 years), the baseline IOP was 17.5 mmHg (± 3.6 mmHg), and there was a mean 24-2 mean deviation of -2.80 dB (± 2.55 dB). Serial circumpapillary CD measurements showed a statistically significant dose-dependent increase from baseline, without negative pressure application, to the maximum negative pressure application of -20 mmHg (difference, 2.27%; P = 0.010). Capillary density measurements then decreased symmetrically when lowering the negative pressure to baseline. Circumpapillary CD measurements at target negative pressures of -10 mmHg, -15 mmHg, and -20 mmHg were significantly higher than the baseline measurements (all P values < 0.05). Circumpapillary RNFL thickness remained the same throughout different levels of negative pressure.

CONCLUSIONS

Circumpapillary CD measurements showed a dose-dependent increase with the induction of negative pressure, while RNFL thickness measurements remained unchanged.

Retinal Oxygen Extraction in Patients with Primary Open-Angle Glaucoma

Objective: To compare total retinal oxygen extraction between patients with primary open-angle glaucoma (POAG) and healthy control subjects. Design: A prospective, single-center, cross-sectional, case−control study performed at the Medical University of Vienna. Subjects: Forty patients with POAG and 40 age- and sex-matched control subjects. Methods: Total retinal blood flow was measured using Doppler optical coherence tomography (OCT). Retinal arterial and venous oxygen saturation was measured using reflectance spectroscopy. From these parameters, oxygen content in the retinal arterial and venous circulation as well as total retinal oxygen extraction were calculated. Results: Total retinal blood flow was lower in POAG (25.2 ± 6.7 µL/min) as compared to healthy control subjects (35.6 ± 8.3 µL/min, p < 0.001). Retinal arterial oxygen content was not different between the two groups (0.18 ± 0.01 mL(O2)/mL in both groups, p < 0.761), but retinal venous oxygen content was higher in POAG (0.15 ± 0.01 mL(O2)/mL) than in healthy controls (0.14 ± 0.01 mL(O2)/mL p < 0.001). Accordingly, retinal oxygen extraction was reduced in POAG (0.8 ± 0.3 µL(O2)/min as compared to healthy controls: 1.4 ± 0.4 µL(O2)/min, p < 0.001). There was a significant association between total retinal blood flow and total retinal oxygen extraction with measures of structural and functional damage (p < 0.001 each). Conclusions: This study indicates that POAG is associated with a reduction in total retinal oxygen extraction linked to structural and functional damage of the disease. Since the technology is non-invasive, it allows for longitudinal studies investigating to which degree low retinal oxygen extraction is linked to the progression of the disease.

Comparison of machine learning approaches for structure-function modeling in glaucoma

To evaluate machine learning (ML) approaches for structure-function modeling to estimate visual field (VF) loss in glaucoma, models from different ML approaches were trained on optical coherence tomography thickness measurements to estimate global VF mean deviation (VF MD) and focal VF loss from 24-2 standard automated perimetry. The models were compared using mean absolute errors (MAEs). Baseline MAEs were obtained from the VF values and their means. Data of 832 eyes from 569 participants were included, with 537 Asian eyes for training, and 148 Asian and 111 Caucasian eyes set aside as the respective test sets. All ML models performed significantly better than baseline. Gradient-boosted trees (XGB) achieved the lowest MAE of 3.01 (95% CI: 2.57, 3.48) dB and 3.04 (95% CI: 2.59, 3.99) dB for VF MD estimation in the Asian and Caucasian test sets, although difference between models was not significant. In focal VF estimation, XGB achieved median MAEs of 4.44 [IQR 3.45-5.17] dB and 3.87 [IQR 3.64-4.22] dB across the 24-2 VF for the Asian and Caucasian test sets and was comparable to VF estimates from support vector regression (SVR) models. VF estimates from both XGB and SVR were significantly better than the other models. These results show that XGB and SVR could potentially be used for both global and focal structure-function modeling in glaucoma.