Clinical model assisting with the collaborative care of glaucoma patients and suspects

Jamous, Khalid F; Kalloniatis, Michael; Hennessy, Michael; Agar, Ashish; Hayen, Andrew; Zangerl, Barbara

doi:10.1111/ceo.12466

Cited by 65 publications

(98 citation statements)

References 50 publications

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“…These included but were not limited to age-related macular degeneration, retinal dystrophies, optic neuropathies, and glaucoma as well as those identified as glaucoma suspects. Glaucoma suspects were defined in previous work, 38 which, in brief, included any subject with a clinical finding suspicious with regard to glaucoma on fundus appearance, imaging results, or visual fields. All eyes encompassed in this study met the following inclusion criteria: availability of a good-quality Spectralis OCT (imaging quality score > 15 dB) scan, visual acuity (VA) better than 20/25 (logMAR < 0.1) for all those under the age of 60 or better than 20/32 (logMAR < 0.2) for those older than 60, and spherical equivalent of less than ±6 diopters and astigmatism of less than 3 diopters.…”

Section: Methodsmentioning

confidence: 99%

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

Yoshioka

Zangerl

Nivison‐Smith

et al. 2017

Invest. Ophthalmol. Vis. Sci.

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109

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PurposeTo characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease.MethodsSingle eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort.ResultsPattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm).ConclusionsPattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease.

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Section: Methodsmentioning

confidence: 99%

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

Yoshioka

Zangerl

Nivison‐Smith

et al. 2017

Invest. Ophthalmol. Vis. Sci.

Self Cite

109

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“…Subjects fell into two groups: 13 patients with optic nerve disease and 42 control subjects without eye disease. For all participants, a full ocular examination was undertaken as outlined in previous studies . All participants were experienced with visual field testing, were fully corrected for their refractive error and their results were reliable (as per HFA manufacturer criteria: except for Goldmann V).…”

Section: Methodsmentioning

confidence: 99%

Equating spatial summation in visual field testing reveals greater loss in optic nerve disease

Kalloniatis

Khuu

2016

Ophthalmic Physiologic Optic

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“…These were defined as at least two of the following: (1) retinal changes characteristics of glaucoma were present on fundoscopy; (2) retinal changes characteristic of glaucoma were present on OCT imaging; or (3) patients exhibited visual field defect consistent with these structural findings. 8,35 If deemed appropriate by the ophthalmologist, the patient was referred for further comprehensive clinical consultation with a glaucoma specialist (KM) and included in the glaucomatous group if a final diagnosis of glaucoma was established. All glaucomatous subjects in this study were initiated on topical antiglaucoma medication following the consultation and their pretreatment IOPs were recorded.…”

Section: Study Participantsmentioning

confidence: 99%

Consistency of Structure-Function Correlation Between Spatially Scaled Visual Field Stimuli and In Vivo OCT Ganglion Cell Counts

Yoshioka

Zangerl

Phu

et al. 2018

Invest. Ophthalmol. Vis. Sci.

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PURPOSE. To investigate the effect of stimulus size and disease status on the structure-function relationship within the central retina, we correlated the differential light sensitivity (DLS) with Goldmann stimulus size I to V (GI-V) and optical coherence tomography (OCT) derived in vivo ganglion cell count per stimulus area (GCc) within the macular area in normal subjects and patients with early glaucoma.METHODS. Humphrey Field Analyzer 10-2 visual field data with GI through V and Spectralis OCT macular ganglion cell layer (GCL) thickness measurements were collected from normal and early glaucoma cohorts including 25 subjects each. GCc was calculated from GCL thickness data and correlated with DLSs for different stimulus sizes.RESULTS. Correlation coefficients attained with smaller stimulus size were higher compared to larger stimulus sizes in both normal (GI-GII: R 2 ¼ 0.41-0.43, GIII-GV: R 2 ¼ 0.16-0.41) and diseased cohorts (GI-GII: R 2 ¼ 0.33-0.41, GIII-GV: R 2 ¼ 0.19-0.36). Quadratic regression curves for combined GI to V data demonstrated high correlation (R 2 = 0.82-0.90) and differed less than 1 dB of visual sensitivity within the GCc range between cohorts. The established structure-function relationship was compatible with a histologically derived model correlation spanning the range predicted by stimulus sizes GI to GIII.CONCLUSIONS. Stimulus sizes within critical spatial summation area (GI-II) improved structurefunction correlations in the central visual field. The structure-function relationship was identical in both normal and diseased cohort when GI to GV data were combined. Congruency of GI and GII structure-function correlation with those previously derived with GIII from more peripheral locations further suggests that the structure-function relationship is governed by the number of ganglion cell per stimulus area.

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Clinical model assisting with the collaborative care of glaucoma patients and suspects

Cited by 65 publications

References 50 publications

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

Equating spatial summation in visual field testing reveals greater loss in optic nerve disease

Consistency of Structure-Function Correlation Between Spatially Scaled Visual Field Stimuli and In Vivo OCT Ganglion Cell Counts

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