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The Repeatability of Retinal Layer Thickness Measurements with Spectral-Domain Optical Coherence Tomography in Normal Eyes
摘要： Purpose: To evaluate the repeatability of retinal layer thickness measurements in normal eyes imaged using spectral domain optical coherence tomography (SD-OCT). Methods: Sixty-eight eyes of 34 healthy subjects were enrolled in this study. Imaging was performed 4 times using 9 × 9 mm macular scans with SD-OCT (RS 3000 Advance HD OCT, NIDEK, Gamagori, Japan) at the same visit by an experienced examiner. After automatic retinal segmentation (layering) in 5 layers, the thickness of each layer was calculated. Macular thickness of 9 Early Treatment of Diabetic Retinopathy Study (ETDRS)–like regions was obtained. Repeatability for each of the 9 subfield areas was calculated by their repeatability coefficients and intraclass correlation coefficients (ICCs). Results: There was no significant difference in average retinal thickness and each retinal layer thickness between all measurements acquired by the experienced examiner. The ICCs of retinal layer thickness ranged from 0.826 to 0.847 for the ganglion cell layer + inner plexiform layer, inner nuclear layer + outer plexiform layer and outer nuclear layer + external limiting membrane in the fovea. The ICCs were greater than 0.909 for the other intra-retinal layers in all 9 ETDRS subfield thickness between all measurement pairs. Conclusions: Excellent repeatability was observed for SD-OCT retinal segmented layer thickness measurements in healthy subjects.
关键词： Repeatability,Spectral domain optical coherence tomography,Retinal layer thickness,Automated segmentation,Intraclass correlation coefficients
更新于2025-09-10 09:29:36
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Simplified, automated methods for assessing pixel intensities of fluorescently-tagged drugs in cells
摘要： Assessing the cytoplasmic uptake of fluorescently-tagged drugs in heterogeneous cell types currently involves time-consuming manual segmentation of confocal microscopy images. We developed a set of methods that incorporate map algebra techniques to facilitate and expedite image segmentation, particularly of the parenchyma of intermediate cells in the stria vascularis of the inner ear. Map algebra is used to apply a convolution kernel to pixel neighborhoods to create a masking image to select pixels in the original image for further operations. Here, we describe the utility of integrated intensity-based, percentile-based, and local autocorrelation-based methods to automate segmentation of images into putative morphological regions for pixel intensity analysis. Integrated intensity-based methods are variants of watershed segmentation tools that determine morphological boundaries from rates of change in integrated pixel intensity. Percentile- and local autocorrelation-based methods evolved out of the process of developing map algebra- and integrated intensity-based tools. We identified several simplifications that are surprisingly effective for image segmentation and pixel intensity analysis. These methods were empirically validated on three levels: first, the algorithms were developed based on iterations of inspected results; second, algorithms were tested for various types of robustness; and third, developed algorithms were validated against results from manually-segmented images. We conclude the key to automated segmentation is supervision of output data.
关键词： pixel intensity analysis,map algebra,fluorescently-tagged drugs,confocal microscopy,automated segmentation
更新于2025-09-10 09:29:36
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Does the Location of Bruch's Membrane Opening Change Over Time? Longitudinal Analysis Using San Diego Automated Layer Segmentation Algorithm (SALSA)
摘要： PURPOSE. We determined if the Bruch’s membrane opening (BMO) location changes over time in healthy eyes and eyes with progressing glaucoma, and validated an automated segmentation algorithm for identifying the BMO in Cirrus high-definition coherence tomography (HD-OCT) images. METHODS. We followed 95 eyes (35 progressing glaucoma and 60 healthy) for an average of 3.7 6 1.1 years. A stable group of 50 eyes had repeated tests over a short period. In each B-scan of the stable group, the BMO points were delineated manually and automatically to assess the reproducibility of both segmentation methods. Moreover, the BMO location variation over time was assessed longitudinally on the aligned images in 3D space point by point in x, y, and z directions. RESULTS. Mean visual field mean deviation at baseline of the progressing glaucoma group was (cid:2)7.7 dB. Mixed-effects models revealed small nonsignificant changes in BMO location over time for all directions in healthy eyes (the smallest P value was 0.39) and in the progressing glaucoma eyes (the smallest P value was 0.30). In the stable group, the overall intervisit–intraclass correlation coefficient (ICC) and coefficient of variation (CV) were 98.4% and 2.1%, for the respectively, automated algorithm for the manual segmentation and 98.1% and 1.9%, respectively, CONCLUSIONS. Bruch’s membrane opening location was stable in normal and progressing glaucoma eyes with follow-up between 3 and 4 years indicating that it can be used as reference point in monitoring glaucoma progression. The BMO location estimation with Cirrus HD-OCT using manual and automated segmentation showed excellent reproducibility.
关键词： BMO location variation,glaucoma,automated segmentation,reference plane
更新于2025-09-04 15:30:14
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Automated Analysis of Vitreous Inflammation Using Spectral-Domain Optical Coherence Tomography
摘要： Purpose: To develop an automated method for quantifying vitreous signal intensity on optical coherence tomography (OCT), with particular application for use in the assessment of vitreous inflammation. Methods: This retrospective, observational case-control series comprised 30 patients (30 eyes), with vitreous haze secondary to intermediate, posterior, or panuveitis; 12 patients (12 eyes) with uveitis without evidence of vitreous haze; and 18 patients (18 eyes) without intraocular inflammation or vitreoretinal disease. The presence and severity of vitreous haze was classified according to the National Eye Institute system; other inflammatory indices and clinical parameters were also documented. Spectral-domain OCT images were analyzed using custom VITreous ANalysis software (termed ‘VITAN’), which is fully automated and avoids the need for manual segmentation. Results: VITAN performed accurate segmentation in all scans. Automated measurements of the vitreous:retinal pigment epithelium (RPE) signal ratio showed a moderate correlation with clinical vitreous haze scores (r ? 0.585, P , 0.001), comparable to that reported using manual segmentation in our previous study (r ? 0.566, P ? 0.0001). The novel parameter of vitreous:RPE textural ratio showed a marginally stronger correlation (r ? 0.604, P , 0.001) with clinical vitreous haze scores than the Vitreous:RPE signal ratio. Conclusions: The custom OCT image analysis software (VITAN) allows rapid and automated measurement of vitreous parameters, that is comparable to our previously reported vitreous:RPE index, and correlates with clinically measured disease activity. Such OCT-based indices may provide the much needed objective markers of vitreous activity, which may be used in both clinical assessment, and as outcome measures in clinical trials for intermediate, posterior, and panuveitis.
关键词： optical coherence tomography,vitreous inflammation,uveitis automated segmentation
更新于2025-09-04 15:30:14