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Optimal image sample size for corneal nerve morphometry

Vagenas, Dimitrios, Pritchard, Nicola, Edwards, Katie, Shahidi, Ayda M., Sampson, Geoff, Russell, Anthony, Malik, Rayaz A., & Efron, Nathan (2012) Optimal image sample size for corneal nerve morphometry. Optometry and Vision Science, 89(5), pp. 812-817.

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Abstract

Purpose Arbitrary numbers of corneal confocal microscopy images have been used for analysis of corneal subbasal nerve parameters under the implicit assumption that these are a representative sample of the central corneal nerve plexus. The purpose of this study is to present a technique for quantifying the number of random central corneal images required to achieve an acceptable level of accuracy in the measurement of corneal nerve fiber length and branch density.

Methods Every possible combination of 2 to 16 images (where 16 was deemed the true mean) of the central corneal subbasal nerve plexus, not overlapping by more than 20%, were assessed for nerve fiber length and branch density in 20 subjects with type 2 diabetes and varying degrees of functional nerve deficit. Mean ratios were calculated to allow comparisons between and within subjects.

Results In assessing nerve branch density, eight randomly chosen images not overlapping by more than 20% produced an average that was within 30% of the true mean 95% of the time. A similar sampling strategy of five images was 13% within the true mean 80% of the time for corneal nerve fiber length.

Conclusions The “sample combination analysis” presented here can be used to determine the sample size required for a desired level of accuracy of quantification of corneal subbasal nerve parameters. This technique may have applications in other biological sampling studies.

Impact and interest:

11 citations in Scopus
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12 citations in Web of Science®

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ID Code: 54153
Item Type: Journal Article
Keywords: corneal confocal microscopy, sampling methodology, corneal nerves, daibetes
DOI: 10.1097/OPX.0b013e31824ee8c9
ISSN: 1040-5488
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Biostatistics (010402)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > OPTOMETRY AND OPHTHALMOLOGY (111300)
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Deposited On: 15 Oct 2012 11:28
Last Modified: 13 Jun 2013 01:13

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