**Purpose.**:
To evaluate the intersession repeatability of retinal thickness measurements in patients with diabetic macular edema (DME) using the Heidelberg Spectralis optical coherence tomography (OCT) algorithm and a publicly available, three-dimensional graph search-based multilayer OCT segmentation algorithm, the Iowa Reference Algorithm.

**Methods.**:
Thirty eyes from 21 patients diagnosed with clinically significant DME were included and underwent consecutive, registered macula-centered spectral-domain optical coherence scans (Heidelberg Spectralis). The OCT scans were segmented into separate surfaces, and the average thickness between internal limiting membrane and outer retinal pigment epithelium complex surfaces was determined using the Iowa Reference Algorithm. Variability between paired scans was analyzed and compared with the retinal thickness obtained from the manufacturer-supplied Spectralis software.

**Results.**:
The coefficient of repeatability (variation) for central macular thickness using the Iowa Reference Algorithm was 5.26 μm (0.62% [95% confidence interval (CI), 0.43–0.71]), while for the Spectralis algorithm this was 6.84 μm (0.81% [95% CI, 0.55–0.92]). When the central 3 mm was analyzed, the coefficient of repeatability (variation) was 2.46 μm (0.31% [95% CI, 0.23–0.38]) for the Iowa Reference Algorithm and 4.23 μm (0.53% [95% CI, 0.39–0.65]) for the Spectralis software.

**Conclusions.**:
The Iowa Reference Algorithm and the Spectralis software provide excellent reproducibility between serial scans in patients with clinically significant DME. The publicly available Iowa Reference Algorithm may have lower between-measurement variation than the manufacturer-supplied Spectralis software for the central 3 mm subfield. These findings have significant implications for the management of patients with DME.

^{ 1,2 }Initially, time-domain OCT using Stratus OCT (Carl Zeiss Meditec, Inc., Dublin, CA) was used clinically to evaluate patients with DME.

^{ 3 }This has largely been supplanted by spectral-domain OCT technology (SD-OCT), which allows for faster scans and higher resolution. One of the most commonly used SD-OCT devices, Spectralis OCT (Heidelberg Spectralis; Heidelberg Engineering, Heidelberg, Germany), has a scan rate of 40,000 axial scans per second and an axial resolution of 5 μm.

^{ 4,5 }possibly related to active eye tracking as well as the ability to register subsequent images, as is now standard on most devices. Only two studies, however, have addressed the reproducibility of SD-OCT in patients with DME.

^{ 6,7 }Reproducibility in DME could potentially be lower than in normal eyes because macular edema may distort the retinal layers and segmentation by OCT, which has been a reported finding induced by subretinal fluid from neovascular age-related macular degeneration.

^{ 8,9 }Clinical OCT devices are equipped with manufacturer-specific segmentation algorithms that identify the retinal layers in the acquired OCT volumes. Thus, reproducibility potentially depends not only on the OCT imaging hardware, but also on the algorithm, both of which can be affected by macular edema.

^{ 5,6,10 }

^{ 11–13 }available in the public domain at http://www.biomed-imaging.uiowa.edu/downloads, has previously been developed and validated on OCT volumes from all clinically used OCT devices, including Spectralis. This allowed us to study the question whether the segmentation algorithm has a differential impact on reproducibility of DME quantification. The purpose of this pilot study was to compare the reproducibility of the manufacturer-supplied algorithm for Spectralis OCT volumes and the reproducibility of the Iowa Reference Algorithm on the same Spectralis OCT volumes for patients with DME.

*.vol*format.

^{ 14 }was obtained from the manufacturer-supplied Spectralis software. The Spectralis software seems to determine average retinal thickness as the distance between the inner limiting membrane and the signal from the outer border of the RPE in two dimensions, though the algorithms have not been published. The average thickness of the central 1 and 3 mm subfields was determined using the Iowa Reference Algorithm by segmenting four surfaces in the same OCT volumes: the internal limiting membrane, external limiting membrane, inner/outer segment (IS/OS) junction, and the outer surface of the retinal pigment epithelium (RPE) complex (Fig. 1).

^{ 13,15 }Mean subfield retinal thickness was obtained by averaging the distance between internal limiting membrane and RPE complex for all A-scans in each central subfield. No correction of segmentation errors was performed.

**Figure 1**

**Figure 1**

*t*-test. The coefficient of repeatability was calculated as 1.96 times the standard deviation between subfield thicknesses, and the coefficient of variation was calculated as standard deviation divided by the mean. The 95% confidence intervals (95% CI) and comparisons of the coefficient of variation were analyzed using the log transformation method.

^{ 16 }Bland–Altman plots were calculated to further compare the two algorithms.

^{ 17 }To examine if increased macular thickness had an influence on repeatability of measurements, the coefficients of repeatability and variation were compared between eyes with a retinal thickness higher than 400 μm and eyes with a retinal thickness less than 400 μm. This threshold of 400 μm was chosen because it was roughly the average of the central macular thickness in our patient population.

*P*= 0.85). See the Table. Comparing the CMT between the two algorithms revealed a coefficient of repeatability of 25.02 μm and a coefficient of variation of 2.96% (95% CI, 2.29–3.86). The average central 3 mm thickness was 407.23 μm (95% CI, 265.90–548.56 μm) for the Iowa Reference Algorithm and 405.02 μm (95% CI, 274.12–535.91 μm) for the Heidelberg Spectralis algorithm, also a nonsignificant difference (

*P*= 0.902). Comparing the central 3 mm thickness between the two algorithms gave a coefficient of repeatability of 15.73 μm and a coefficient of variation of 1.86% (95% CI, 1.24–2.08).

**Table**

**Table**

Mean Macular Thickness, μm (95% CI) | Coefficient of Variation, % (95% CI) | Coefficient of Repeatability, μm | |

Iowa Reference Algorithm, central 1 mm | 435.60 (186.60–684.59) | 0.62 (0.43–0.71) | 5.26 |

Spectralis software, central 1 mm | 429.15 (180.31–677.99) | 0.81 (0.55–0.92) | 6.84 |

Iowa Reference Algorithm, central 3 mm | 407.23 (265.90–548.56) | 0.31 (0.23–0.38) | 2.46 |

Spectralis software, central 3 mm | 405.02 (274.12–535.91) | 0.53 (0.39–0.65) | 4.23 |

Iowa Reference Algorithm, central 1 mm > 400 μm | 534.81 (336.65–732.98) | 0.64 (0.43–0.71) | 6.70 |

Iowa Reference Algorithm, central 1 mm < 400 μm | 336.38 (246.25–426.50) | 0.49 (0.47–0.79) | 3.25 |

Spectralis software, central 1 mm > 400 μm | 529.80 (339.98–719.62) | 0.87 (0.66–1.11) | 9.0 |

Spectralis software, central 1 mm < 400 μm | 328.50 (234.45–422.55) | 0.55 (0.40–0.67) | 3.56 |

**Figure 2**

**Figure 2**

**Figure 3**

**Figure 3**

^{ 3,7 }The coefficient of variation of the CMT was lower for both the Iowa algorithm (0.62%) and the Spectralis algorithm (0.81%) than the coefficient of variation previously found by Forooghian et al. for both Cirrus OCT (2.42%) and Stratus OCT (2.63%).

^{ 7 }Wolf-Schnurrbusch et al. showed that Spectralis OCT had a lower coefficient of variation when compared to other OCT devices in normal eyes.

^{ 5 }

^{ 5 }The Iowa Reference Algorithm can analyze the OCT volumes from all major SD-OCT devices. Potentially the measured differences that have been found between retinal layer thickness in different SD-OCT devices are related to the manufacturer-specific algorithms used in these devices.

^{ 5–7,10,18 }Because our results show that the layer segmentation algorithm affects the between-measurement variability, a publicly available published algorithm such as the Iowa Reference Algorithm has the potential to eliminate cross-device variability.

**E.H. Sohn**, None;

**J.J. Chen**, None;

**K. Lee**, None;

**M. Niemeijer**, None;

**M. Sonka**, P;

**M.D. Abràmoff**, P

*. 1995; 113: 1019–1029. [CrossRef] [PubMed]*

*Arch Ophthalmol**. 1998; 105: 360–370. [CrossRef] [PubMed]*

*Ophthalmology**. 2007; 114: 1520–1525. [CrossRef] [PubMed]*

*Ophthalmology**. 2008; 49: 5386–5391. [CrossRef] [PubMed]*

*Invest Ophthalmol Vis Sci**. 2009; 50: 3432–3437. [CrossRef] [PubMed]*

*Invest Ophthalmol Vis Sci**. 2011; 31: 48–55. [CrossRef] [PubMed]*

*Retina**. 2008; 49: 4290–4296. [CrossRef] [PubMed]*

*Invest Ophthalmol Vis Sci**. 2008; 49: 1084–1088. [CrossRef] [PubMed]*

*Invest Ophthalmol Vis Sci**. 2010; 51: 4788–4791. [CrossRef] [PubMed]*

*Invest Ophthalmol Vis Sci**. 2009; 147: 267–275, e2. [CrossRef] [PubMed]*

*Am J Ophthalmol**. 2010; 29: 159–168. [CrossRef] [PubMed]*

*IEEE Trans Med Imaging**. 2008; 27: 1495–1505. [CrossRef] [PubMed]*

*IEEE Trans Med Imaging**. 2009; 28: 1436–1447. [CrossRef] [PubMed]*

*IEEE Trans Med Imaging**. 1985; 103: 1796–1806. [CrossRef] [PubMed]*

*Arch Ophthalmol**. 2010; 29: 2023–2037. [CrossRef] [PubMed]*

*IEEE Trans Med Imaging**. 1996; 313: 106. [CrossRef] [PubMed]*

*BMJ**. 1986; 1: 307–310. [CrossRef] [PubMed]*

*Lancet**. 2008; 39: S43–S49. [PubMed]*

*Ophthalmic Surg Lasers Imaging*