Comparison of 10-2 and 24-2C Test Grids for Identifying Central Visual Field Defects in Glaucoma and Suspect Patients

Purpose The purpose of this study was to compare concordance between ganglion cell-inner plexiform layer (GCIPL) data from the Cirrus optical coherence tomographer (OCT) Ganglion Cell Analysis (GCA) and visual fields (VFs), with and without Drasdo displacement. Methods From 296 open-angle glaucoma participants, GCIPL deviation and raw thickness data were extracted over locations per the 10-2 VF test grid, with and without application of Drasdo displacement, with global and eccentricity-dependent sensitivities and specificities calculated for both. With OCT and VF data classified as within or outside normative limits, pattern deviation values were compared using paired t -tests and Spearman correlations. Regression models were applied to pattern deviation values as a function of GCIPL thickness, and differences in model performance with and without displacement were compared using extra sums-of-squares F tests. Results There were small but significant improvements in global specificity without displacement (0.58–0.59 with displacement and 0.61 without displacement), without notable differences in sensitivity (0.77–0.78 with displacement and 0.76–0.78 without displacement). At abnormal VF locations and without displacement, a higher proportion of correct OCT classifications ( P = 0.0008) and significant correlation with worsening pattern deviation values were observed ( r = 0.50, P = 0.002). Regression models indicated significantly steeper slopes with Drasdo displacement centrally ( P = 0.002–0.04). Conclusions With GCA deviation maps, small improvements in structure-function concordance were observed without displacement, which are unlikely to be clinically meaningful. Using GCIPL thickness data, significantly better structure-function concordance was observed centrally with Drasdo displacement. Translational Relevance Applying Drasdo displacement on probability-based reports is unlikely to alter clinical impressions of structure-function concordance, but applying displacement with GCIPL thickness data may improve detection of structure-function concordance.

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“…Participants were consecutively recruited from patients meeting these criteria, with data from 128 participants included in a previous study. 5 …”

Section: Methodsmentioning

confidence: 99%

Clinical Evaluations of Macular Structure-Function Concordance With and Without Drasdo Displacement

Tong

Phu

Alonso‐Caneiro

et al. 2022

Trans. Vis. Sci. Tech.

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“…Similarly, we focussed on using quantitative data from clinician‐facing outputs from the Humphrey Field Analyzer and Cirrus optical coherence tomography, which again limits our generalisability to the outputs from these devices only. For instance, we used a 24‐2 visual field grid for our visual field quantitative metrics, which may miss some central defects that might be detected when using the 10‐2 or 24‐2C protocols 66–68 . As described in the literature, there may be qualitative, morphological differences between pressure‐defined phenotypes, which are not conducive to the analysis method used in the present study that might benefit from archetypal analysis examining patterns of loss, both structurally and functionally 69,70 …”

Section: Discussionmentioning

confidence: 99%

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

Rafla

Khuu

Kashyap

et al. 2023

Ophthalmic Physiologic Optic

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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.

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“…Patients’ visual field (perimetry) was assessed for each eye (with corrective lenses if necessary) using a 24-2C (SITA-Faster) test grids on the Humphrey Field Analyzer (Carl Zeiss Meditec, Dublin, CA) which incorporates a selection of 10 distributed test points derived from the 10-2 into the 24-2 grid so that both the central and peripheral visual fields can be tested. It should be noted that the 24-2C test grid can identify the presence of a central visual field defect on similar global indices [e.g., mean deviation (MD)] to the 10-2 grid, the 10-2 grid providing a detailed description of the visual field defect (Phu & Kalloniatis, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Impact of glaucoma on the spatial frequency processing of scenes in central vision

et al. 2023

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Glaucoma is an eye disease characterized by a progressive vision loss usually starting in peripheral vision. However, a deficit for scene categorization is observed even in the preserved central vision of patients with glaucoma. We assessed the processing and integration of spatial frequencies in the central vision of patients with glaucoma during scene categorization, considering the severity of the disease, in comparison to age-matched controls. In the first session, participants had to categorize scenes filtered in low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs) as a natural or an artificial scene. Results showed that the processing of spatial frequencies was impaired only for patients with severe glaucoma, in particular for HFS scenes. In the light of proactive models of visual perception, we investigated how LSF could guide the processing of HSF in a second session. We presented hybrid scenes (combining LSF and HSF from two scenes belonging to the same or different semantic category). Participants had to categorize the scene filtered in HSF while ignoring the scene filtered in LSF. Surprisingly, results showed that the semantic influence of LSF on HSF was greater for patients with early glaucoma than controls, and then disappeared for the severe cases. This study shows that a progressive destruction of retinal ganglion cells affects the spatial frequency processing in central vision. This deficit may, however, be compensated by increased reliance on predictive mechanisms at early stages of the disease which would however decline in more severe cases.

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Comparison of 10-2 and 24-2C Test Grids for Identifying Central Visual Field Defects in Glaucoma and Suspect Patients

Cited by 22 publications

References 62 publications

Clinical Evaluations of Macular Structure-Function Concordance With and Without Drasdo Displacement

Clinical Evaluations of Macular Structure-Function Concordance With and Without Drasdo Displacement

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

Impact of glaucoma on the spatial frequency processing of scenes in central vision

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