Improving Personalized Structure to Function Mapping From Optic Nerve Head to Visual Field

Understanding and identifying visual field progression

Detecting deterioration of visual field sensitivity measurements is important for the diagnosis and management of glaucoma. This review surveys the current methods for assessing progression that are implemented in clinical devices, which have been used in clinical trials, alongside more recent advances proposed in the literature. Advice is also offered to clinicians on what they can do to improve the collection of perimetric data to help analytical progression methods more accurately predict change. This advice includes a discussion of how frequently visual field testing should be undertaken, with a view towards future developments, such as digital healthcare outside the standard clinical setting and more personalised approaches to perimetry.

Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning

Purpose

To assess the performance of a perimetric strategy using structure-function predictions from a deep learning (DL) model.

Methods

Visual field test-retest data from 146 eyes (75 patients) with glaucoma with (median [5th-95th percentile]) 10 [7, 10] tests per eye were used. Structure-function predictions were generated with a previously described DL model using cicumpapillary optical coherence tomography (OCT) scans. Structurally informed prior distributions were built grouping the observed measured sensitivities for each predicted value and recalculated for each subject with a leave-one-out approach. A zippy estimation by sequential testing (ZEST) strategy was used for the simulations (1000 per eye). Ground-truth sensitivities for each eye were the medians of the test-retest values. Two variations of ZEST were compared in terms of speed (average total number of presentations [NP] per eye) and accuracy (average mean absolute error [MAE] per eye), using either a combination of normal and abnormal thresholds (ZEST) or the calculated structural distributions (S-ZEST) as prior information. Two additional versions of these strategies employing spatial correlations were tested.

Results

S-ZEST was significantly faster, with a mean average NP of 213.87 (SD = 28.18), than ZEST, with a mean average NP of 255.65 (SD = 50.27) (P < 0.001). The average MAE was smaller for S-ZEST (1.98; SD = 2.37) than ZEST (2.43; SD = 2.69) (P < 0.001). Spatial correlations further improved both strategies (P < 0.001), but the differences between ZEST and S-ZEST remained significant (P < 0.001).

Conclusions

DL structure-function predictions can significantly improve perimetric tests.

Translational Relevance

DL structure-function predictions from clinically available OCT scans can improve perimetry in glaucoma patients.

Structure-function assessment in glaucoma based on perimetric sensitivity and en face optical coherence tomography images of retinal nerve fiber bundles

Many studies have assessed structure-function relations in glaucoma, but most without topographical comparison across the central 30°. We present a method for assessing structure-function relations with en face images of retinal nerve fiber layer (RNFL) bundles allowing topographical comparison across much of this retinal area. Forty-four patients with glaucoma (median age 61 years) were recruited and tested with Optical Coherence Tomography (OCT) and perimetry. Six rectangular volume scans were gathered, and then montaged to provide en face views of the RNFL bundles. We calculated the proportion of locations showing a perimetric defect that also showed an en face RNFL defect; and the proportion of locations falling on an RNFL defect that also showed a perimetric defect. A perimetric defect for a location was defined as a total deviation (TD) value equal to or deeper than -4 dB. We found that the median (IQR) number of locations with abnormal RNFL bundle reflectance that also had abnormal TD was 78% (60%) and for locations with abnormal TD that also had abnormal RNFL bundle reflectance was 75% (44%). We demonstrated a potential approach for structure-function assessment in glaucoma by presenting a topographic reflectance map, confirming results of previous studies and including larger retinal regions.

Concordance of Objectively Detected Retinal Nerve Fiber Bundle Defects in En Face OCT Images with Conventional Structural and Functional Changes in Glaucoma

PURPOSE

To assess how objectively detected defects in retinal nerve fiber bundle (RNFB) reflectance on en face OCT images relate to circumpapillary retinal nerve fiber layer thickness (cpRNFLT) and visual field defects.

DESIGN

Cross-sectional study.

PARTICIPANTS

Sixteen participants with early glaucoma and 29 age-matched healthy controls, of whom 22 had usable en face images for the establishment of normative levels of RNFB reflectance.

METHODS

All the participants underwent cpRNFLT scans, visual field examination, and wide-field OCT. En face reflectivity was assessed objectively using the Summary of Multiple Anatomically Adjusted Slabs method. En face defects were deemed concordant with cpRNFLT when they had at least 1 cpRNFLT point with P < 0.01, within ± 15° of the predicted insertion on the optic disc. Visual fields were examined using custom suprathreshold perimetry and SITA Standard 24-2. For each visual field location, the corresponding reflectance was deemed abnormal if any en face superpixel within ± 1° was abnormal. The overall, positive, and negative agreements were measured in each participant.

MAIN OUTCOME MEASURES

Proportion of concordant defects between en face reflectance analysis and cpRNFLT (%) as well as overall, positive, and negative agreements between en face reflectance analysis and visual field results.

RESULTS

Most en face abnormalities had concordant cpRNFLT defects in the mapped sector (median proportion concordant, 0.85; interquartile range, 0.74-0.95). In eyes with glaucoma, a median of 8.1% (range, 2.4%-23.7%) and 14.9% (range, 3.5%-29.1%) locations showed corresponding en face and visual field defects using 24-2 and custom perimetry, respectively. Both the perimetric strategies had moderate-to-good raw agreement with en face analysis (0.66-0.68), with stronger agreement on normal findings than on defects (0.77-0.78 and 0.4-0.44).

CONCLUSIONS

Objectively extracted reflectance defects showed strong concordance with conventional cpRNFLT damage and good agreement with perimetry, which could be enhanced by further minimization of image artifacts.

Development and validation of the Iris Glare, Appearance, and Photophobia questionnaire for patients with iris defects

PURPOSE

To validate the Iris Glare, Appearance, and Photophobia (Iris GAP) questionnaire, a new symptom-based and appearance-based quality-of-life measure for patients with iris defects.

SETTING

Single tertiary glaucoma clinic in Toronto, Ontario, Canada.

DESIGN

Prospective cohort study.

METHODS

Patients with varying degrees of iris defects were enrolled. Patients completed the Iris GAP questionnaire and the glare and driving subscales of the Refractive Status and Vision Profile (RSVP) questionnaire. Test-retest reliability, defined by Cronbach α and intraclass correlation coefficients (ICCs), was evaluated with repeat testing 2 weeks later.

RESULTS

The study included 73 patients with iris defects, 68 controls with no iris defects, 77 patients with peripheral iridotomies (PIs) or transillumination defects (TIDs), and 22 patientswith surgically repaired irides (n = 22). Iris GAP scores ranged from 0 to 32 with a 97% completion rate. Iris GAP had high test-retest reliability (Cronbach α = 0.866, ICC = 0.953, P < .0005). Iris GAP scores were reliably distinguishable between patients with iris defects, repaired iris defects, and PIs and TIDs and controls (1-way analysis of variance, P < .0005). In pairwise comparisons, the major defect group had statistically significant higher scores than any of the other groups ( P < .005 for each). The control and repaired groups had the lowest scores, whereas the PI/TID group had intermediate scores. 9 patients underwent iris repair between tests and had a mean difference of 8.2 ± 6.2 points between their preoperative and postoperative scores ( P = .004). Iris GAP scores positively correlated with RSVP scores ( R2 = 0.73).

CONCLUSIONS

Iris GAP can reliably evaluate symptomatology and patient-reported appearance in patients with iris defects.

Radial and Tangential Retinal Magnifications as Functions of Visual Field Angle Across Spherical, Oblate, and Prolate Retinal Profiles

Purpose

To provide a tool for calculating radial and tangential retinal magnifications as functions of field angle and retinal shape and to articulate patterns of magnification across the retina for monocular and binocular combinations of prolate-, oblate-, and spherical-shaped retinas.

Methods

Formulae were derived to calculate radial and tangential retinal magnifications (mm/deg) from field angle (degrees), retinal asphericity (unitless conic constant), retinal vertex radius of curvature (mm), and nodal point position (mm). Monocular retinal magnifications were determined for eyes with prolate, spherical, and oblate retinas as functions of field angle. Bilateral differences in magnifications were examined for combinations of those eyes.

Results

Retinal shape substantially affects magnification profiles even for eyes with the same axial length. Greatest magnification changes across a retina and between eyes, as well as greatest increase in radial-tangential differences (distortion), occur with prolate retinas. Binocular magnification differences were smallest for oblate retinas. Nodal points anterior to the vertex center of curvature and oblate asphericity both cause field-dependent reductions in magnification relative to the fovea (barrel distortion), whereas nodal points posterior to vertex center of curvature and prolate asphericity cause the opposite (pincushion distortion). Retinal magnification differences due to eye shape are much greater than aniseikonia thresholds and chromatic differences in magnification. A spreadsheet tool implements the magnification calculations.

Conclusions

Local retinal magnifications as functions of field angle have substantial effects on objective applications (imaging retinal anatomy) and subjective experiences (aniseikonia) and quantify an ocular property that differs across eye shapes and refractive errors.

Translational Relevance

Methods are provided to customize the calculation of radial and tangential magnifications across the retina for individual eyes, which will bolster the multifactorial study of the effects of foveal and peripheral optics across eye shapes and refractive errors.

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, β, was varied, and the best-fitting, initial clock-hour position of the trajectory to the border was found for each β. 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 β_Sup and β_Inf 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.

Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and Optical Coherence Tomography Imaging

PURPOSE

To develop and validate a deep learning (DL) system for predicting each point on visual fields (VF) from disc and optical coherence tomography (OCT) imaging and derive a structure-function mapping.

DESIGN

Retrospective, cross-sectional database study PARTICIPANTS: 6437 patients undergoing routine care for glaucoma in three clinical sites in the UK.

METHODS

OCT and infrared reflectance (IR) optic disc imaging was paired with the closest VF within 7 days. Efficient-Net B2 was used to train two single modality DL models to predict each of the 52 sensitivity points on the 24-2 VF pattern. A policy DL model was designed and trained to fuse the two model predictions.

MAIN OUTCOME MEASURES

Pointwise Mean Absolute Error (PMAE) RESULTS: A total of 5078 imaging to VF pairs were used as a held-out test set to measure the final performance. The improvement in PMAE with the policy model was 0.485 [0.438, 0.533] dB compared to the IR image of the disc alone and 0.060 [0.047, 0.073] dB compared to the OCT alone. The improvement with the policy fusion model was statistically significant (p < 0.0001). Occlusion masking shows that the DL models learned the correct structure function mapping in a data-driven, feature agnostic fashion.

CONCLUSIONS

The multimodal, policy DL model performed the best; it provided explainable maps of its confidence in fusing data from single modalities and provides a pathway for probing the structure-function relationship in glaucoma.

Hierarchical Censored Bayesian Analysis of Visual Field Progression

Purpose

To develop a Bayesian model (BM) for visual field (VF) progression accounting for the hierarchical, censored and heteroskedastic nature of the data.

Methods

Three versions of a hierarchical BM were developed: a simple linear (Hi-linear); censored at 0 dB (Hi-censored); heteroskedastic censored (Hi-HSK). For the latter, we modeled the test variability according to VF sensitivity using a large test-retest cohort (1396 VFs, 146 eyes with glaucoma). We analyzed a large cohort of 44,371 VF tests from 3352 eyes from five glaucoma clinics. We quantified the bias in the estimated rate-of-progression, the detection of progression (Hit-rate [HR]), the median time-to-progression and the prediction error of future observations (mean absolute error [MAE]). HR and time-to-progression were compared at matched false-positive-rate (FPR), quantified using permutations of a separate test-retest cohort (360 tests, 30 eyes with glaucoma). BMs were compared to simple linear regression and Permutation-Analyses-of Pointwise-Linear-Regression. Differences in time-to-progression were tested using survival analysis.

Results

Censored models showed the smallest bias in the rate-of-progression. The three BMs performed very similarly in terms of HR and time-to-progression and always better than the other methods. The average reduction in time-to-progression was 37% with the BMs (P < 0.001) at 5% FPR. MAE for prediction was very similar among methods.

Conclusions

Bayesian hierarchical models improved the detection of VF progression. Accounting for censoring improves the precision of the estimates, but minimal effect is provided by accounting for heteroskedasticity.

Translational Relevance

These results are relevant for quantification of VF progression in practice and for clinical trials.

Increased Depth, Reduced Extent, and Sharpened Edges of Visual Field Defects Measured by Compass Fundus Perimeter Compared to Humphrey Field Analyzer

Purpose

The purpose of this study was to compare visual field results of the COMPASS fundus perimeter (CMP) and the Humphrey Field Analyzer (HFA) in the same eyes; to compare structure-function concordance between circumpapillary retinal nerve fiber layer (Cp-RNFL) profiles and the two perimetry results; and to evaluate whether differences between the two results reflect postulated advantages of real-time eye movement compensation during perimetry.

Methods

We retrospectively analyzed 24-2 visual field data measured with CMP and HFA together with Cp-RNFL optical coherence tomography (OCT) scan data from 95 eyes of 65 people with glaucoma. We defined visual field locations with total deviation (TD) less than −5 dB as defective. The CMP and HFA fields were compared on measures of: spatial extent (number of defective locations); depth (TD values); and sharpness of scotomata edges (maximum TD difference between defective locations and their neighbors). Structure-function concordance between Cp-RNFL profile and respective visual field was also compared.

Results

Compared to the HFA, scotomata measured by CMP were of reduced spatial extent (mean difference = −3.14 locations, p < 0.001), greater depth (median TD of CMP = −17 dB versus HFA = −13 dB, p = 0.029) and steeper edges (median of maximum TD difference of CMP = 10.6 dB versus HFA = 6 dB, p < 0.001). Structure-function concordance between Cp-RNFL profile and either visual field were comparable despite the reduced scotoma spatial extent measured by CMP.

Conclusions

Glaucomatous visual fields measured by CMP displayed characteristics consistent with expected effects of using real-time eye movement compensation technology compared to the widely used HFA.

Translational Relevance

Glaucomatous visual field defects measured by the CMP are more localized, deeper, and steeper than those of the HFA.