Comparison of Reliability in Diabetic Macular Edema Estimates between Two Image Analysis Algorithms
Journal of the Korean Ophthalmological Society
;
: 772-778, 2016.
Article
in Korean
| WPRIM
| ID: wpr-160939
ABSTRACT
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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Retinaldehyde
/
Iowa
/
Macular Edema
/
Ganglion Cysts
/
Tomography, Optical Coherence
Limits:
Humans
Country/Region as subject:
North America
Language:
Korean
Journal:
Journal of the Korean Ophthalmological Society
Year:
2016
Type:
Article
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