Dataset Information

Diagnostic Capability of Three-Dimensional Macular Parameters for Glaucoma Using Optical Coherence Tomography Volume Scans.

ABSTRACT: Purpose:To compare the diagnostic capability of three-dimensional (3D) macular parameters against traditional two-dimensional (2D) retinal nerve fiber layer (RNFL) thickness using spectral domain optical coherence tomography. To determine if manual correction and interpolation of B-scans improve the ability of 3D macular parameters to diagnose glaucoma. Methods:A total of 101 open angle glaucoma patients (29 with early glaucoma) and 57 healthy subjects had peripapillary 2D RNFL thickness and 3D macular volume scans. Four parameters were calculated for six different-sized annuli: total macular thickness (M-thickness), total macular volume (M-volume), ganglion cell complex (GCC) thickness, and GCC volume of the innermost 3 macular layers (retinal nerve fiber layer + ganglion cell layer + inner plexiform layer). All macular parameters were calculated with and without correction and interpolation of frames with artifacts. The areas under the receiver operating characteristic curves (AUROC) were calculated for all the parameters. Results:The 3D macular parameter with the best diagnostic performance was GCC-volume-34, with an inner diameter of 3 mm and an outer of 4 mm. The AUROC for RNFL thickness and GCC-volume-34 were statistically similar for all regions (global: RNFL thickness 0.956, GCC-volume-34 0.939, P value = 0.3827), except for the temporal GCC-volume-34, which was significantly better than temporal RNFL thickness (P value = 0.0067). Correction of artifacts did not significantly change the AUROC of macular parameters (P values between 0.8452 and 1.0000). Conclusions:The diagnostic performance of best macular parameters (GCC-volume-34 and GCC-thickness-34) were similar to or better than 2D RNFL thickness. Manual correction of artifacts with data interpolation is unnecessary in the clinical setting.

SUBMITTER: Verticchio Vercellin AC

PROVIDER: S-EPMC6188465 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Diagnostic Capability of Three-Dimensional Macular Parameters for Glaucoma Using Optical Coherence Tomography Volume Scans.

Verticchio Vercellin Alice C AC Jassim Firas F Poon Linda Yi-Chieh LY Tsikata Edem E Braaf Boy B Shah Sneha S Ben-David Geulah G Shieh Eric E Lee Ramon R Simavli Huseyin H Que Christian J CJ Papadogeorgou Georgia G Guo Rong R Vakoc Benjamin J BJ Bouma Brett E BE de Boer Johannes F JF Chen Teresa C TC

Investigative ophthalmology & visual science 20181001 12

<h4>Purpose</h4>To compare the diagnostic capability of three-dimensional (3D) macular parameters against traditional two-dimensional (2D) retinal nerve fiber layer (RNFL) thickness using spectral domain optical coherence tomography. To determine if manual correction and interpolation of B-scans improve the ability of 3D macular parameters to diagnose glaucoma.<h4>Methods</h4>A total of 101 open angle glaucoma patients (29 with early glaucoma) and 57 healthy subjects had peripapillary 2D RNFL th ...[more]

PMID: 30326067

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Project description:Importance:Whether optical coherence tomography angiography (OCT-A) outperforms OCT to detect glaucoma remains inconclusive. Objective:To compare (1) the diagnostic performance for detection of glaucoma and (2) the structure-function association between inner macular vessel density and inner macular thickness. Design, Setting, and Participants:This cross-sectional study included 115 patients with glaucoma and 35 healthy individuals for measurements of retinal thickness and retinal vessel density, segmented between the anterior boundary of internal limiting membrane and the posterior boundary of the inner plexiform layer, over the 3 × 3-mm2 macula using swept-source OCT. All participants were Chinese. Visual sensitivity corresponding to the 3 × 3-mm2 macular region was expressed in unlogged 1/lambert for investigation of the structure-function associations. Diagnostic performance was evaluated with area under the receiver operating characteristic curves (AUCs). The study was conducted between January 12, 2016, and December 12, 2016. Main Outcomes and Measures:Area under the receiver operating characteristic curve and R2 analysis. Results:Of the 115 patients with glaucoma, 42 (36.5%) were women (mean [SD] age, 53.5 [13.4] years); of the 35 individuals with healthy eyes, 25 (71.4%) were women (age, 60.6 [5.9] years). Inner macular vessel density and thickness were 4.3% (95% CI, 2.4%-6.1%) and 21.1 μm (95% CI, 17.4-24.9 μm) smaller, respectively, in eyes with glaucoma compared with healthy eyes. The AUC of mean inner macular thickness for glaucoma detection was greater than that of mean inner macular vessel density (difference, 0.17; 95% CI, 0.01-0.31; P = .03). At 90% specificity, the sensitivity of mean inner macular thicknesses for detection of glaucoma was greater than that of mean inner macular vessel densities (difference, 29.2%; 95% CI, 11.5%-64.6%; P = .02). The strength of the structure-function association was stronger for mean inner macular thickness than mean inner macular vessel density in the linear (difference in R2 = 0.38; 95% CI, 0.22-0.54; P < .001) and nonlinear (difference in R2 = 0.36; 95% CI, 0.21-0.51; P < .001) regression models. Conclusions and Relevance:In this study, OCT measurement of inner macular thickness shows a higher diagnostic performance to detect glaucoma and a stronger structure-function association than the currently used OCT-A measurement of inner macular vessel density. These findings may suggest that OCT-A of the macula has a limited role in the diagnostic evaluation of glaucoma.

Project description:PURPOSE:To detect macular perfusion defects in glaucoma using projection-resolved optical coherence tomography (OCT) angiography. DESIGN:Prospective observation study. PARTICIPANTS:A total of 30 perimetric glaucoma and 30 age-matched normal participants were included. METHODS:One eye of each participant was imaged using 6×6-mm macular OCT angiography (OCTA) scan pattern by 70-kHz 840-nm spectral-domain OCT. Flow signal was calculated by the split-spectrum amplitude-decorrelation angiography algorithm. A projection-resolved OCTA (PR-OCTA) algorithm was used to remove flow projection artifacts. Four en face OCTA slabs were analyzed: the superficial vascular complex (SVC), intermediate capillary plexus (ICP), deep capillary plexus (DCP), and all-plexus retina (SVC + ICP + DCP). The vessel density (VD), defined as the percentage area occupied by flow pixels, was calculated from en face OCTA. A novel algorithm was used to adjust the vessel density to compensate for local variations in OCT signal strength. MAIN OUTCOME MEASURES:Macular retinal VD, ganglion cell complex (GCC) thickness, and visual field (VF) sensitivity. RESULTS:Focal capillary dropout could be visualized in the SVC, but not the ICP and DVP, in glaucomatous eyes. In the glaucoma group, the SVC and all-plexus retinal VD (mean ± standard deviation: 47.2%±7.1% and 73.5%±6.6%) were lower than in the normal group (60.5%±4.0% and 83.2%±4.2%, both P < 0.001, t test). The ICP and DCP VD were not significantly lower in the glaucoma group. Among the overall macular VD parameters, the SVC VD had the best diagnostic accuracy as measured by the area under the receiver operating characteristic curve (AROC). The accuracy was even better when the worse hemisphere (inferior or superior) was used, achieving an AROC of 0.983 and a sensitivity of 96.7% at a specificity of 95%. Among the glaucoma participants, the hemispheric SVC VD values were highly correlated with the corresponding GCC thickness and VF sensitivity (P < 0.003). The reflectance compensation step in VD calculation significantly improved repeatability, normal population variation, and correlation with VF and GCC thickness. CONCLUSIONS:On the basis of PR-OCTA, glaucoma preferentially affects perfusion in the SVC in the macula more than the deeper plexuses. Reflectance-compensated SVC VD measurement by PR-OCTA detected glaucoma with high accuracy and could be useful in the clinical evaluation of glaucoma.

Project description:ImportanceConventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.ObjectiveTo develop a segmentation-free deep learning (DL) algorithm for assessment of glaucomatous damage using the entire circle B-scan image from SD-OCT.Design, setting, and participantsThis cross-sectional study at a single institution used data from SD-OCT images of eyes with glaucoma (perimetric and preperimetric) and normal eyes. The data set was randomly split at the patient level into a training (50%), validation (20%), and test data set (30%). Data were collected from March 2008 to April 2019, and analysis began April 2018.ExposuresA convolutional neural network was trained to discriminate glaucomatous from normal eyes using the SD-OCT circle B-scan without segmentation lines.Main outcomes and measuresThe ability to discriminate glaucoma from healthy eyes was evaluated by comparing the area under the receiver operating characteristic curve and sensitivity at 80% or 95% specificity for the DL algorithm's predicted probability of glaucoma vs conventional RNFL thickness parameters given by SD-OCT software. The performance was also assessed in preperimetric glaucoma, as well as by visual field severity using Hodapp-Parrish-Anderson criteria.ResultsA total of 20 806 SD-OCT images from 1154 eyes of 635 individuals (612 [53%] with glaucoma and 542 normal eyes [47%]) were included. The mean (SD) age at SD-OCT scan was 70.8 (10.4) years in individuals with glaucoma and 55.8 (14.1) years in controls. There were 187 women (53.3%) in the glaucoma group and 165 (59.8%) in the control group. Of 612 eyes with glaucoma, 432 (70.4%) had perimetric and 180 (29.6%) had preperimetric glaucoma. The DL algorithm had a significantly higher area under the receiver operating characteristic curve than global RNFL thickness (0.96 vs 0.87; difference = 0.08 [95% CI, 0.04-0.12]) and each RNFL thickness sector for discriminating between glaucoma and controls (all P < .001). At 95% specificity, the DL algorithm (81%; 95% CI, 64%-97%) was more sensitive than global RNFL thickness (67%; 95% CI, 58%-76%). The areas under the receiver operating characteristic curve were also significantly greater for the DL algorithm compared with RNFL thickness at each stage of disease, especially preperimetric and mild perimetric glaucoma.Conclusions and relevanceA segmentation-free DL algorithm performed better than conventional RNFL thickness parameters for diagnosing glaucomatous damage on OCT scans, especially in early disease. Future studies should investigate how such an approach contributes to diagnostic decisions when combined with other relevant clinical information, such as risk factors and perimetry results.

Dataset Information

Diagnostic Capability of Three-Dimensional Macular Parameters for Glaucoma Using Optical Coherence Tomography Volume Scans.

Publications

Diagnostic Capability of Three-Dimensional Macular Parameters for Glaucoma Using Optical Coherence Tomography Volume Scans.

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