Repeatability and reproducibility of automatic segmentation of retinal layers in healthy subjects using Spectralis optical coherence tomography

Çetinkaya, Ersan; Duman, Rahmi; Sabaner, Mehmet Cem

doi:10.5935/0004-2749.20170092

Cited by 9 publications

(6 citation statements)

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“…Spectralis is one of the commercially available SD-OCT machines that is commonly used in clinical practice. The machine contains a software algorithm that enables a fast acquisitional cross-sectional retinal scan and generates a highly reproducible automated retinal thickness measurement for total and segmented individual retinal layers [14, 16, 17]. In Spectralis, the retinal thickness values were presented as either the ETDRS (covering a central 10-degree area) or posterior pole (covering a central 24-degree area) analysis formats.…”

Section: Discussionmentioning

confidence: 99%

Reference Database of Inner Retinal Layer Thickness and Thickness Asymmetry in Healthy Thai Adults as Measured by the Spectralis Spectral-Domain Optical Coherence Tomography

et al. 2022

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Purpose: To determine a reference database of the thickness and intraocular thickness asymmetry of total retina, retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and inner plexiform layer (IPL) in healthy Thai subjects measured by the Spectralis spectral-domain optical coherence tomography Methods: This cross-sectional study recruited the healthy subjects age ≥18 years, having spherical refraction within ±6 diopters and cylindrical refraction ±3 diopters, from a hospital’s personnel and the people accompanying patients visiting the ophthalmology department. If the eligibility criteria were met for both eyes, only 1 eye of each subject was randomly selected for an analysis. Macular images were obtained using posterior pole thickness scan protocol over a 24x24 degree area at the center of the fovea. The automated retinal thickness segmentation values of total retina and three inner retinal layers were calculated for the mean and the mean intraocular thickness difference between superior and inferior retinal hemispheres. The influence of age, gender, and axial length on thickness and thickness asymmetry of individualized retinal layer were evaluated. Results: Two hundred and fifty-two subjects were included in study with a mean (SD) age of 46.7 (15.8) years and 120 (47.6%) were males. According to the Early Treatment Diabetic Retinopathy Study map, the inner ring area was the thickest location of the total retina (range; 326.0 to 341.5 µm), ganglion cell layer (range; 47.7 to 52.7 µm), and inner plexiform layer (range; 39.9 to 42.1 µm); whereas the thickest location of RNFL was at the outer ring area (range; 18.8 to 47.5 µm). For posterior pole intraocular thickness asymmetry, the greatest mean ± SD difference was observed for total retina (9.0 ± 2.2 µm), followed by RNFL (9.9 ± 3.2 µm), and GCL (2.7 ± 0.6 µm) and the lowest mean difference was noted for IPL (2.4 ± 0.5 µm). The thickness and thickness asymmetry of each retinal layer were variably influenced by age, gender, and axial length; however, these factors had a minimal influence on the thickness asymmetry maps of GCL and RNFL. Conclusion: The reference database of the macular thickness and thickness asymmetry from this study would be beneficial in determining physiologic variations of the OCT parameters in the healthy Thai population.

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Section: Discussionmentioning

confidence: 99%

Reference Database of Inner Retinal Layer Thickness and Thickness Asymmetry in Healthy Thai Adults as Measured by the Spectralis Spectral-Domain Optical Coherence Tomography

et al. 2022

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“…However, this inaccuracy can be significantly reduced by postsegmentation inspection and refinement by a trained operator [42,43]. Regarding individual macular layer thickness measurements, Spectralis segmentation software has proven high repeatability and reproducibility for all layers in all nine ETDRS areas [7,44]. Nevertheless, its accuracy may be significantly affected by image quality or marked anatomical distortion [7,45].…”

Section: Table 1 Demographic and Clinical Characteristics Of The Patients By Groupmentioning

confidence: 99%

Neurodegeneration in systemic lupus erythematosus: layer by layer retinal study using optical coherence tomography

et al. 2020

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Background Systemic lupus erythematosus (SLE) is a chronic, autoimmune and multisystemic disease. Recent studies with functional and structural magnetic resonance imaging and cognitive tests report an unexpectedly high frequency of central nervous system involvement, even in patients with asymptomatic SLE. The purpose of this study was to identify early signs of retinal neurodegeneration by comparing the thickness of the peripapillary retinal nerve fiber layer (pRNFL) and all macular layers between patients with SLE without ophthalmologic manifestations and healthy controls. The effect of disease duration and systemic comorbidities was also studied. Methods Cross-sectional study, in which all participants underwent a complete ophthalmologic evaluation including retinal segmentation analysis with spectral domain-optical coherence tomography. Patients with SLE also received a detailed autoimmune disease specialist evaluation to assess the disease activity state and systemic involvement. For pRNFL thickness, the global and six peripapillary sectors were determined. Each macular layer thickness was determined in the nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. A multiple linear regression analysis was performed to control for the effect of potential demographic, ophthalmic and systemic confounders. A second multivariable analysis, including patients with SLE only, was performed to assess the effect of disease-specific variables on the outcome measures. Results Sixty-eight eyes of 68 patients with SLE and 50 eyes of 50 healthy controls were considered. The pRNFL was significantly thinner in the SLE group globally (p = 0.026) and in the temporal superior (p = 0.007) and temporal (p = 0.037) sectors. In patients with SLE, chronic medication for hypercholesterolemia, hypertension and anticoagulants were associated with a significant thinning of the pRNFL. Patients with SLE presented significant thinning in the photoreceptor layer in five ETDRS areas (p < 0.05). Shorter disease duration was associated with greater photoreceptor thinning in all ETDRS subfields. Neuropsychiatric SLE, higher disease activity and cardiovascular risk factors were associated with a thinner photoreceptor layer. No differences were observed in overall retinal thickness or the remaining macular layers. Conclusion Patients with SLE present early signs of retinal neurodegeneration, as evidenced by a reduction in the photoreceptor layer and pRNFL. These signs are more pronounced in patients with higher cardiovascular risk burden or neuropsychiatric involvement.

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“…To the best of our knowledge, our study is the first to analyze the HEYEX software for macular sublayer segmentation in NDD. Cetinkaya et al25 found excellent agreement with repeated measurements using the Spectralis HEYEX software on healthy participants for all individual retinal sublayer thickness values. Heussen et al26 compared automated software with manual correction in healthy participants, and found that manual correction of inner and outer retinal boundary errors yields mean differences of less than 6 μm, which is similar to the axial resolution of SD-OCT devices.…”

Section: Discussionmentioning

confidence: 81%

Validation of Optical Coherence Tomography Retinal Segmentation in Neurodegenerative Disease

Wong

Cheng

Mandelcorn

et al. 2019

Trans. Vis. Sci. Tech.

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PurposeThis study assessed agreement between an automated spectral-domain optical coherence tomography (SD-OCT) retinal segmentation software and manually corrected segmentation to validate its use in a prospective clinical study of neurodegenerative diseases (NDD).MethodsThe sample comprised 30 subjects with NDD, including vascular cognitive impairment, frontotemporal dementia, Parkinson's disease, and Alzheimer's disease. Macular SD-OCT scans were acquired and segmented using Heidelberg Spectralis. For the central foveal B scan of each eye, eight segmentation lines were examined to determine the proportion of each line that the software erroneously delineated. Errors in four lines were manually corrected in all B scans spanning a 6-mm circle centered on the foveola. Mean volume and thickness measurements for four retinal layers (total retina, retinal nerve fiber layer [RNFL], inner retinal layers, and outer retinal layers) were obtained before and after correction.ResultsThe outer plexiform layer line had one of the lowest mean error ratios (2%), while RNFL had the highest (23%). Agreement between automated software and trained observer was excellent (ICC > 0.98) for retinal thickness and volume of all layers. Mean volume differences between software and observers for the four layers ranged from −0.003 to 0.006 mm3. Mean thickness differences ranged from −1.855 to 1.859 μm.ConclusionsDespite occasional small errors in software-generated retinal sublayer segmentation, agreement was excellent between software-derived and observer-corrected mean volume and thickness sublayer measurements.Translational RelevanceAutomated SD-OCT segmentation software generates valid measurements of retinal layer volume and thickness in NDD subjects, thereby avoiding the need to manually correct nonobvious delineation errors.

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Repeatability and reproducibility of automatic segmentation of retinal layers in healthy subjects using Spectralis optical coherence tomography

Abstract: It is possible to obtain cross-sections from the same location using the device's follow-up mode, making it virtually impossible to distinguish between repeated measurements taken with the device by different examiners.

Cited by 9 publications

References 0 publications

Reference Database of Inner Retinal Layer Thickness and Thickness Asymmetry in Healthy Thai Adults as Measured by the Spectralis Spectral-Domain Optical Coherence Tomography

Reference Database of Inner Retinal Layer Thickness and Thickness Asymmetry in Healthy Thai Adults as Measured by the Spectralis Spectral-Domain Optical Coherence Tomography

Neurodegeneration in systemic lupus erythematosus: layer by layer retinal study using optical coherence tomography

Validation of Optical Coherence Tomography Retinal Segmentation in Neurodegenerative Disease

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