J Korean Ophthalmol Soc.  2016 May;57(5):772-778. 10.3341/jkos.2016.57.5.772.

Comparison of Reliability in Diabetic Macular Edema Estimates between Two Image Analysis Algorithms

• Gye HJ
• Bae JH
• Song SJ

• KMID: 2212720
• DOI: http://doi.org/10.3341/jkos.2016.57.5.772

Abstract

PURPOSE
To evaluate segmentation reliability in diabetic macular edema (DME) estimates between a Cirrusâ„¢ 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 (Cirrusâ„¢ HD-OCT). Central foveal thickness (CFT) and ganglion cell layer-inner plexiform layer segmentation data were compared with those produced by the Cirrusâ„¢ 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.

Keyword

Central foveal thickness; Diabetic macular edema; Optical coherence tomography; Reliability; Segmentation algorithm

MeSH Terms

Ganglion Cysts
Humans
Iowa
Macular Edema*
Retinaldehyde
Tomography, Optical Coherence
Retinaldehyde

Figure

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  Figure 1. Representative automatic segmentation results for a normal eye. (A) Cirrus™ High definition optical coherence tomography (HD-OCT) segmentation of the ganglion cell layer (GCL) + inner plexiform layer (IPL) between the purple line and the yellow line. (B) Iowa algorithm segmentation of the GCL + IPL between the second surface (orange) and the third surface (yellow).

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  Figure 2. Automatic segmentation results for eyes with diabetic macular edema. (A, B) An eye with central foveal thickness (CFT) < 400 μm. (C, D) An eye with CFT < 400 μm. (A, C) Iowa reference algorithm segmentation image. (B, D) Cirrus segmentation image. (A, B) show the correct segmentation results for the two algorithms, while (C, D) show incorrect segmentation results for the Cirrus segmentation image.

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  Figure 3. Bland-Altman plot for the Cirrus versus Iowa algorithm. The solid line indicates the average mean difference, whereas dotted lines delineate 95% confidence intervals.

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  Figure 4. Scatterplots of central foveal thickness obtained with the Cirrus software algorithm and the Iowa reference algorithm (Pearson correlation β = 0.868, p < 0.001).

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  Figure 5. Proportion of segmentation errors obtained with the Cirrus software algorithm and Iowa reference algorithm. CFT = central foveal thickness.

Reference

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