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文章基本信息

  • 标题:Comparison of Reliability in Diabetic Macular Edema Estimates between Two Image Analysis Algorithms
  • 本地全文:下载
  • 作者:Gye, Hyo Jung ; Bae, Jeong Hun ; Song, Su Jeong
  • 期刊名称:Journal of the Korean Ophthalmological Society
  • 印刷版ISSN:0378-6471
  • 出版年度:2016
  • 卷号:57
  • 期号:5
  • 页码:772-778
  • DOI:10.3341/jkos.2016.57.5.772
  • 语种:Korean
  • 出版社:The Korean Ophthalmological Society
  • 摘要:Purpose

    To evaluate segmentation reliability in diabetic macular edema (DME) estimates between a Cirrus™ HD-OCT image analysis algorithm and an Iowa reference algorithm, which are an automatic segmentation software.

    Methods

    Thirty eyes from 23 patients diagnosed with DME were included and underwent spectral-domain optical coherence scans (Cirrus™ HD-OCT). Central foveal thickness (CFT) and ganglion cell layer-inner plexiform layer segmentation data were compared with those produced by the Cirrus™ HD-OCT segmentation algorithm and Iowa reference algorithm. Measurement agreement was assessed using intraclass correlation (ICC) and segmentation errors were confirmed by 2 ophthalmologists.

    Results

    The mean CFT in the 1-mm central area determined by the manufacturer-supplied Cirrus software and Iowa reference algorithm was 512.07 ± 182.35 µm and 476.53 ± 32.36 µm, respectively ( p < 0.05). The mean paired difference was 35.53 ± 92.46 µm (ICC, 0.929). Segmentation errors were demonstrated in eyes with a CFT less than 400 µm, specifically for 45% of scans obtained by the Cirrus algorithm and 9% from the Iowa algorithm; in eyes with a CFT equal to or higher than 400 µm, the error rates were 95% and 42%, respectively.

    Conclusions

    CFT measurement in eyes with diabetic macular edema using the Cirrus algorithm and Iowa algorithm showed relatively high degrees of agreement and significant correlation. In eyes with a CFT equal to or higher than 400 µm, the Iowa algorithm showed higher reliability in retinal segmentation than the Cirrus algorithm.

  • 关键词:Central foveal thickness; Diabetic macular edema; Optical coherence tomography; Reliability; Segmentation algorithm
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