Association Between Structure-function Characteristics and Visual Field Outcomes in Glaucoma Subjects With Intraocular Pressure Reduction After Trabeculectomy

Predicting glaucoma progression using deep learning framework guided by generative algorithm

Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomography (OCT) can be used to visualize glaucomatous optic nerve and retinal damage, while functional visual field (VF) tests can be used to measure the extent of vision loss. However, VF testing is patient-dependent and highly inconsistent, making it difficult to track glaucoma progression. In this work, we developed a multimodal deep learning model comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network, for glaucoma progression prediction. We used OCT images, VF values, demographic and clinical data of 86 glaucoma patients with five visits over 12 months. The proposed method was used to predict VF changes 12 months after the first visit by combining past multimodal inputs with synthesized future images generated using generative adversarial network (GAN). The patients were classified into two classes based on their VF mean deviation (MD) decline: slow progressors (< 3 dB) and fast progressors (> 3 dB). We showed that our generative model-based novel approach can achieve the best AUC of 0.83 for predicting the progression 6 months earlier. Further, the use of synthetic future images enabled the model to accurately predict the vision loss even earlier (9 months earlier) with an AUC of 0.81, compared to using only structural (AUC = 0.68) or only functional measures (AUC = 0.72). This study provides valuable insights into the potential of using synthetic follow-up OCT images for early detection of glaucoma progression.

Endpoints for clinical trials in ophthalmology

With the identification of novel targets, the number of interventional clinical trials in ophthalmology has increased. Visual acuity has for a long time been considered the gold standard endpoint for clinical trials, but in the recent years it became evident that other endpoints are required for many indications including geographic atrophy and inherited retinal disease. In glaucoma the currently available drugs were approved based on their IOP lowering capacity. Some recent findings do, however, indicate that at the same level of IOP reduction, not all drugs have the same effect on visual field progression. For neuroprotection trials in glaucoma, novel surrogate endpoints are required, which may either include functional or structural parameters or a combination of both. A number of potential surrogate endpoints for ophthalmology clinical trials have been identified, but their validation is complicated and requires solid scientific evidence. In this article we summarize candidates for clinical endpoints in ophthalmology with a focus on retinal disease and glaucoma. Functional and structural biomarkers, as well as quality of life measures are discussed, and their potential to serve as endpoints in pivotal trials is critically evaluated.

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

Purpose

To investigate modeling of the focal visual field (VF) loss by combining structural measurements and vascular measurements in eyes with early primary open-angle glaucoma (POAG).

Methods

In this cross-sectional study, subjects with early glaucoma (VF mean deviation, ≥−6 dB) underwent optical coherence tomography (OCT) imaging, optical coherence tomography angiography (OCTA) imaging, and Humphrey 24-2 VF tests. Capillary perfusion densities (CPDs) were calculated after the removal of large vessels in the OCTA images. Focal associations between VF losses at the individual VF test locations, circumpapillary retinal nerve fiber layer (RNFL) thickness measurements from OCT, and CPDs were determined using nerve fiber trajectory tracings. Linear mixed models were used to model focal VF losses at each VF test location.

Results

Ninety-seven eyes with early POAG (VF mean deviation, −2.47 ± 1.64 dB) of 71 subjects were included. Focal VF modeling using a combined RNFL–CPD approach resulted in a median adjusted R² value of 0.30 (interquartile range [IQR], 0.13–0.55), whereas the RNFL-only and CPD-only approaches resulted in median values of 0.22 (IQR, 0.10–0.51) and 0.26 (IQR, 0.10–0.52), respectively. Seventeen VF locations with the combined approach had an adjusted R² value greater than 0.50. Likelihood testing at each VF test location showed that the combined approach performed significantly better at the superior nasal VF regions of the eyes compared with the univariate approaches.

Conclusions

Modeling of focal VF losses showed improvements when structural thickness and vascular parameters were included in tandem. Evaluation of VF defects in early glaucoma may benefit from considering both RNFL and OCTA characteristics.

Focal Structure-Function Relationships in Primary Open-Angle Glaucoma Using OCT and OCT-A Measurements

Purpose

To evaluate the focal structure-function associations among visual field (VF) loss, optical coherence tomography angiography (OCT-A) vascular measurements, and optical coherence tomography (OCT) structural measurements in glaucoma.

Methods

In this cross-sectional study, subjects underwent standard automated perimetry, OCT-based nerve fiber thickness measurements, and OCT-A imaging. Mappings of focal VF test locations with OCT and OCT-A measurements were defined using anatomically adjusted nerve fiber trajectories and were studied using multivariate mixed-effects analysis. Segmented regression analysis was used to determine the presence of breakpoints in the structure-function associations.

Results

The study included 119 eyes from 86 Chinese subjects with primary open-angle glaucoma (POAG). VF mean deviation was significantly associated with global capillary perfusion density (β = 0.13 ± 0.08) and global retinal nerve fiber layer thickness (β = 0.09 ± 0.02). Focal capillary density (FCD) was significantly associated with VF losses at 34 VF test locations (66.7% of 24-2 VF), with 24 of the 34 locations being within 20° of retinal eccentricity. Focal nerve layer (FNL) thickness was significantly associated with 16 VF test locations (31.4% of 24-2 VF; eight locations within 20° eccentricity). For VF test locations in the central 10° VF, VF losses below the breakpoint were significantly associated with FCD (slope, 0.89 ± 0.12, P < 0.001), but not with FNL thickness (slope, 0.57 ± 0.39, P = 0.15).

Conclusions

Focal capillary densities were significantly associated with a wider range of visual field losses and in a larger proportion of the visual field compared to nerve fiber thickness.