The effect of macular visual field test density on central structure-function concordance in glaucoma.

CLINICAL RELEVANCE: Central visual field (VF) testing often requires focussed high-density test grids. The critical number of test locations for maximising structure-function concordance in the macula is not known. PURPOSE: The aim of this work is to determine the impact of the number of test locations in the central VF on binarized structure-function concordance in glaucoma. METHODS: Humphrey Field Analyser (HFA) 10-2 test grid and Cirrus optical coherence tomography Ganglion Cell Analysis (GCA) results from one eye of 155 glaucoma patients were extracted. Following anatomical correction for retinal ganglion cell displacement, the pointwise results of the central 36 locations of the 10-2 pattern deviation map and their corresponding locations within the GCA deviation map were recorded. The number of test locations was systematically reduced from 36 (4 locations per step) and added from 1 (1 location per step) and binarized structure-function concordance (p < 0.05 for both) at each step was evaluated. Eleven test point subtraction and addition models were developed. Concordance rates (proportion) were plotted as a function of number of test locations, and were fitted using segmental nonlinear regression to identify the critical point of inflection at which concordance was maximised and discordance minimised. RESULTS: Subtractive and additive approaches returned two-way estimates of the critical number, with, on average 8-14 test locations being the range at which structure-function concordance was optimised in the present cohort across all models. A randomised approach to subtracting or adding test locations returned critical numbers that were similar to systematic and empirical models, suggesting that specific test location was not as critical in optimising structure-function concordance compared to the number of test locations. CONCLUSION: There is a potential critical number (8-14) in macular visual field testing where binarized structure-function concordance is optimised, providing a framework for guiding the development of integrated macular test locations in VF testing for glaucoma.

Which glaucoma patients benefit from 10-2 visual field testing? Proposing the functional vulnerability zone framework.

CLINICAL RELEVANCE: A method for determining 10-2 deployment in glaucoma with the goal of detecting additional visual field sensitivity for the purpose of functional monitoring is proposed. BACKGROUND: To provide a pilot method for determining when to deploy the 10-2 visual field (VF) test grid in glaucoma by characterising the 'functional vulnerability zone'. METHODS: The cross-sectional 24-2 (central 12 locations) and 10-2 VF results from 133 eyes of 133 glaucoma subjects were used to describe the central Hill of Vision using VF sensitivity. The 'volume' (defined using arbitrary units, A.U.) under the Hill was calculated. A greater A.U. on the 10-2 indicated a functional vulnerability zone (FVZ), signifying additional clinical dynamic range for potential future monitoring. The main outcome measures were calculated A.U. and 24-2 factors which were significantly related to A.U. differences between 24-2 and 10-2. RESULTS: Over 55% of patients had an FVZ (A.U. greater using 10-2). Several 24-2 features (worse mean deviation, worse central 24-2 mean defect, and a higher proportion of defective locations) were significant in the FVZ cohort compared to non-FVZ. 24-2 mean deviation levels at which 10-2 may be favoured were low at -3.16 to -3.62 dB. Specifically, 5 or more defective central 24-2 test locations were associated with an FVZ. Subjects exhibiting a less severe defect on the 10-2 were more likely to have an FVZ, indicating its potential for future VF monitoring. CONCLUSIONS: The authors propose several clinical markers, focussing on the 24-2, which can guide clinicians on when the 10-2 may have utility in glaucoma assessment. The authors provide a pilot reference spreadsheet for clinicians to visualise the likelihood of 10-2 utility in the context of an FVZ.

Visualising structural and functional characteristics distinguishing between newly diagnosed high-tension and low-tension glaucoma patients.

PURPOSE: To determine whether there are quantifiable structural or functional differences that can distinguish between high-tension glaucoma (HTG; intraocular pressure [IOP] > 21 mm Hg) and low-tension glaucoma (LTG; IOP ≤ 21 mm Hg) at diagnosis. METHOD: This was a retrospective, cross-sectional study. Clinical results of one eye from 90 newly diagnosed HTG and 319 newly diagnosed LTG patients (117 with very-low-tension glaucoma [vLTG; ≤15 mm Hg] and 202 with middling LTG [mLTG; >15 mm Hg, ≤21 mm Hg]) were extracted, which included relevant demographic covariates of glaucoma, quantitative optical coherence tomography (including the optic nerve head, retinal nerve fibre layer and ganglion cell-inner plexiform layer) measurements and standard automated perimetry global metrics. We used binary logistic regression analysis to identify statistically significant clinical parameters distinguishing between phenotypic groups for inclusion in principal component (PC) (factor) analysis (PCA). The separability between each centroid for each cohort was calculated using the Euclidean distance (d(x,y)). RESULTS: The binary logistic regression comparing HTG and all LTG identified eight statistically significant clinical parameters. Subsequent PCA results included three PCs with an eigenvalue >1. PCs 1 and 2 accounted for 21.2% and 20.2% of the model, respectively, with a d(x,y) = 0.468, indicating low separability between HTG and LTG. The analysis comparing vLTG, mLTG and HTG identified 15 significant clinical parameters, which were subsequently grouped into five PCs. PCs 1 and 2 accounted for 24.1% and 17.8%, respectively. The largest separation was observed between vLTG and HTG (d(x,y) = 0.581), followed by vLTG and mLTG (d(x,y) = 0.435) and lastly mLTG and HTG (d(x,y) = 0.210). CONCLUSION: Conventional quantitative structural or functional parameters could not distinguish between pressure-defined glaucoma phenotypes at the point of diagnosis and are therefore not contributory to separating cohorts. The overlap in findings highlights the heterogeneity of the primary open-angle glaucoma clinical presentations among pressure-defined groups at the cohort level.