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dc.contributor.authorDenniss, Jonathan*
dc.contributor.authorAstle, A.T.*
dc.date.accessioned2017-01-09T16:45:10Z
dc.date.available2017-01-09T16:45:10Z
dc.date.issued2016-10
dc.identifier.citationDenniss J and Astle AT (2016) Spatial Interpolation Enables Normative Data Comparison in Gaze-Contingent Microperimetry. Investigative Ophthalmology and Visual Science. 57: 5449-5456.en_US
dc.identifier.urihttp://hdl.handle.net/10454/11082
dc.descriptionyesen_US
dc.description.abstractPurpose: 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.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttp://dx.doi.org/10.1167/iovs.16-20222en_US
dc.rights© 2016 The Authors. Published by ARVO. This work is licensed under a Creative Commons Attribution 4.0 International License.en_US
dc.subjectMicroperimetry; Fundus perimetry; Gaze-contingent; Normative database; Age-Related Macular Degeneration (AMD); Spatial Interpolationen_US
dc.titleSpatial Interpolation Enables Normative Data Comparison in Gaze-Contingent Microperimetryen_US
dc.status.refereedyesen_US
dc.date.Accepted2016-09-09
dc.typeArticleen_US
dc.type.versionPublished versionen_US
refterms.dateFOA2018-07-27T01:47:20Z


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