Literature DB >> 27760271

Spatial Interpolation Enables Normative Data Comparison in Gaze-Contingent Microperimetry.

Jonathan Denniss1, Andrew T Astle1.   

Abstract

PURPOSE: To demonstrate methods that enable visual field sensitivities to be compared with normative data without restriction to a fixed test pattern.
METHODS: Healthy participants (n = 60, age 19-50) undertook microperimetry (MAIA-2) using 237 spatially dense locations up to 13° eccentricity. Surfaces were fit to the mean, variance, and 5th percentile sensitivities. Goodness-of-fit was assessed by refitting the surfaces 1000 times to the dataset and comparing estimated and measured sensitivities at 50 randomly excluded locations. A leave-one-out method was used to compare individual data with the 5th percentile surface. We also considered cases with unknown fovea location by adding error sampled from the distribution of relative fovea-optic disc positions to the test locations and comparing shifted data to the fixed surface.
RESULTS: Root mean square (RMS) difference between estimated and measured sensitivities were less than 0.5 dB and less than 1.0 dB for the mean and 5th percentile surfaces, respectively. Root mean square differences were greater for the variance surface, median 1.4 dB, range 0.8 to 2.7 dB. Across all participants 3.9% (interquartile range, 1.8-8.9%) of sensitivities fell beneath the 5th percentile surface, close to the expected 5%. Positional error added to the test grid altered the number of locations falling beneath the 5th percentile surface by less than 1.3% in 95% of participants.
CONCLUSIONS: Spatial interpolation of normative data enables comparison of sensitivity measurements from varied visual field locations. Conventional indices and probability maps familiar from standard automated perimetry can be produced. These methods may enhance the clinical use of microperimetry, especially in cases of nonfoveal fixation.

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Year:  2016        PMID: 27760271     DOI: 10.1167/iovs.16-20222

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  4 in total

1.  Central visual field sensitivity data from microperimetry with spatially dense sampling.

Authors:  Andrew T Astle; Iram Ali; Jonathan Denniss
Journal:  Data Brief       Date:  2016-08-04

2.  Microperimetry in Age-Related Macular Degeneration: An Evidence-Base for Pattern Deviation Probability Analysis in Microperimetry.

Authors:  Nicola K Cassels; John M Wild; Tom H Margrain; Chris Blyth; Victor Chong; Jennifer H Acton
Journal:  Transl Vis Sci Technol       Date:  2019-12-31       Impact factor: 3.283

3.  Microperimetry Hill of Vision and Volumetric Measures of Retinal Sensitivity.

Authors:  Amandeep Singh Josan; Thomas M W Buckley; Laura J Wood; Jasleen K Jolly; Jasmina Cehajic-Kapetanovic; Robert E MacLaren
Journal:  Transl Vis Sci Technol       Date:  2021-06-01       Impact factor: 3.283

4.  Interpreting MAIA Microperimetry Using Age- and Retinal Loci-Specific Reference Thresholds.

Authors:  Jason Charng; Paul G Sanfilippo; Mary S Attia; Monika Dolliver; Sukanya Arunachalam; Avenell L Chew; Evan N Wong; David A Mackey; Fred K Chen
Journal:  Transl Vis Sci Technol       Date:  2020-06-18       Impact factor: 3.283

  4 in total

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