Literature DB >> 22670074

Low limit for effective signal strength in the Stratus OCT in imperative low signal strength cases.

Man Mook Ha1, Joon Mo Kim, Hyun Joong Kim, Ki Ho Park, Martha Kim, Chul Young Choi.   

Abstract

PURPOSE: To determine the lowest limit of signal strength that is still effective for accurate analysis of optic coherence tomography (OCT) values, we investigated the reproducibility of OCT scans by signal strength (SS).
METHODS: A total of 668 subjects were scanned for measurements of retinal nerve fiber layer (RNFL) thickness using the Stratus OCT twice on the same day. The variability of overall RNFL thickness parameters obtained at different SS was analyzed and compared by repeated-measures of ANOVA and Spearman's correlation coefficient. Values of the intraclass correlation coefficient (ICC) and variability (standard deviation) of RNFL thickness were obtained. The false positive ratio was analyzed.
RESULTS: When SS was 3, the variability of RNFL thickness was significantly different (low ICC, high variability) in comparison to when SS was 4 or greater. Significant negative correlations were observed between variability in RNFL thickness and signal strength. The difference of variability of average RNFL thickness between SS 4 (4.94 µm) and SS 6 (4.41 µm) was 0.53 µm.
CONCLUSIONS: Clinically, the difference of variability of average RNFL thickness between SS 4 and SS 6 was quite small. High SS is important, however, when signal strength is low due to uncorrectable factors in patients in need of OCT for glaucoma and retinal disease. Our results suggest that SS 4 is the lowest acceptable limit of signal strength for obtaining reproducible scanning images.

Entities:  

Keywords:  Glaucoma; Optic coherence tomography; Retinal nerve fiber layer; Signal strength; Variability

Mesh:

Year:  2012        PMID: 22670074      PMCID: PMC3364429          DOI: 10.3341/kjo.2012.26.3.182

Source DB:  PubMed          Journal:  Korean J Ophthalmol        ISSN: 1011-8942


  27 in total

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  4 in total

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Journal:  Neuroophthalmology       Date:  2019-10-29

3.  Deep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets.

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Journal:  Transl Vis Sci Technol       Date:  2022-05-02       Impact factor: 3.048

4.  Reproducibility of peripapillary retinal nerve fiber layer thickness measured by spectral domain optical coherence tomography in pseudophakic eyes.

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Journal:  Korean J Ophthalmol       Date:  2014-03-14
  4 in total

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