Vertical Macular Asymmetry Measures Derived From SD-OCT for Detection of Early Glaucoma.
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ABSTRACT:
SUBMITTER: Sharifipour F
PROVIDER: S-EPMC5555252 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Purpose:The purpose of this study was to compare rates of change of various macular thickness measures and evaluate the influence of baseline damage on macular rates of change. Methods:One hundred twelve eyes (112 patients) with ? 2 years of follow-up and ? 5 macular optical coherence tomography (OCT) images and 10-2 visual field (VF) tests were included. OCT measures of interests were full macular thickness (FMT), ganglion cell complex (GCC), ganglion cell/inner plexiform layer (GCIPL), ganglion cell layer (GCL), and outer retinal layer (ORL) thickness in 3° × 3° superpixels. Rates of change were estimated with linear regression and normalized by dividing rates by the average normative superpixel thickness. We compared rates of change and proportion of significantly worsening superpixels (detection rate) and improving superpixels (false discovery rate [FDR]) among macular measures as a function of baseline thickness and 10-2 VF status. Results:Median (interquartile range [IQR]) baseline VF mean deviation, follow-up time, and number of VFs/OCTs were -7.6 dB (-11.8 to -3.8 dB), 4.5 years (4.0-5.0 years), and 9 (8-10), respectively. Normalized FMT and GCC rates of change were faster and detection rates were higher than GCIPL and GCL (P < 0.001), but FMT had lower FDR than GCC (P = 0.02); faster FMT rates were partially explained by ORL rates of change. GCC detection rates were less likely than GCIPL and GCL rates to decrease with diminishing baseline thickness or worse VF damage. In eyes with 10-2 VF worsening, GCC and GCL demonstrated the fastest rates of change. Conclusions:GCC measurements are most likely to detect structural worsening along the spectrum of glaucoma severity. Although FMT rates of change are least influenced by baseline thickness, they partially reflect likely age-related ORL changes. Translational Relevance:GCC thickness measurements seem to be the optimal macular outcome measure for detection of glaucoma deterioration.
| S-EPMC7414740 | biostudies-literature
Project description:Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisition, signal attenuation, multi-frame averaging, and vignetting, making it difficult to correct the data in a fundamental way. This paper presents a method for inhomogeneity correction by acting to reduce the variability of intensities within each layer. In particular, the N3 algorithm, which is popular in neuroimage analysis, is adapted to work for OCT data. N3 works by sharpening the intensity histogram, which reduces the variation of intensities within different classes. To apply it here, the data are first converted to a standardized space called macular flat space (MFS). MFS allows the intensities within each layer to be more easily normalized by removing the natural curvature of the retina. N3 is then run on the MFS data using a modified smoothing model, which improves the efficiency of the original algorithm. We show that our method more accurately corrects gain fields on synthetic OCT data when compared to running N3 on non-flattened data. It also reduces the overall variability of the intensities within each layer, without sacrificing contrast between layers, and improves the performance of registration between OCT images.
| S-EPMC6311386 | biostudies-literature
Project description:PurposeTo quantitatively investigate the macular retinal light reflection characteristic using optical property indices derived from spectral-domain optical coherence tomography (SD-OCT) scans with depth attenuation compensation for pituitary adenoma.MethodsThis study included 38 patients (mean age 44.66 ± 13.77 years old) with diagnosis of pituitary adenoma and 43 age-matched controls. All SD-OCT scans were light attenuation compensated by a depth-resolved model. Attenuation coefficient, the corrected intensity, and the retinal layer thickness were deduced for macular retinal nerve fiber layer (RNFL) and ganglion cell layer combined with inner plexiform layer (GCIPL), as well as comparing between patients and controls by statistical methods.ResultsAttenuation coefficients of RNFL and GCIPL among patients were significantly lower compared to the controls with P values equal to or less than 0.001. The mean values of the corrected optical intensity were decreased in the patients without universally significant differences. Significant decreases in thickness existing in the RNFL of patients, especially in the superonasal (SN) quadrant and inferonasal (IN) quadrant (decrease ratio = 9.64% and 13.02%, both with P < 0.001). The thickness of RNFL was significantly associated with the attenuation coefficient (standardized beta = 0.335, P=0.002). The performances of attenuation coefficient were better than the corrected optical intensity and the thickness (the values of the areas under the receiver operating characteristic curves = 0.751 and 0.758, both with P < 0.001) in discriminating pituitary adenoma patients from controls.ConclusionsThe retinal light reflection characteristics were debilitated in patients with pituitary adenoma. The potential of attenuation coefficients of RNFL and GCIPL in distinguishing patients with pituitary adenoma from controls was validated by the comparison of the derived optical property indices.
| S-EPMC7658689 | biostudies-literature
Project description:PurposeTo test the hypothesis that newly developed shape measures using optical coherence tomography (OCT) macular volume scans can discriminate patients with perimetric glaucoma from healthy subjects.MethodsOCT structural measures defining macular topography and volume were recently developed based on cubic Bézier curves. We exported macular volume scans from 135 eyes with glaucoma (133 patients) and 155 healthy eyes (85 subjects) and estimated global and quadrant-based measures. The best subset of measures to predict glaucoma was explored with a gradient boost model (GBM) with subsequent logistic regression. Accuracy and area under receiver operating curves (AUC) were the primary metrics. In addition, we separately investigated model performance in 66 eyes with mild glaucoma (mean deviation ≥ -6 dB).ResultsAverage (±SD) 24-2 mean deviation was -8.2 (±6.1) dB in eyes with glaucoma. The main predictive measures for glaucoma were temporal inferior rim height, nasal inferior pit volume, and temporal inferior pit depth. Lower values for these measures predicted higher risk of glaucoma. Sensitivity, specificity, and AUC for discriminating between healthy and glaucoma eyes were 81.5% (95% CI = 76.6-91.9%), 89.7% (95% CI = 78.7-94.2%), and 0.915 (95% CI = 0.882-0.948), respectively. Corresponding metrics for mild glaucoma were 84.8% (95% CI = 72.1%-95.5%), 85.8% (95% CI = 87.1%-97.4%), and 0.913 (95% CI = 0.867-0.958), respectively.ConclusionsNovel macular shape biomarkers detect early glaucoma with clinically relevant performance. Such biomarkers do not depend on intraretinal segmentation accuracy and may be helpful in eyes with suboptimal macular segmentation.Translational relevanceMacular shape biomarkers provide valuable information for detection of early glaucoma and may provide additional information beyond thickness measurements.
| S-EPMC9344219 | biostudies-literature
Project description:To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies.Six hundred ninety macular SD-OCT image volumes (6.0 × 6.0 × 2.3 mm(3)) were obtained from one eyes of 690 subjects (74.6 ± 9.7 [mean ± SD] years, 37.8% of males) randomly selected from the population-based Rotterdam Study. The dataset consisted of 420 OCT volumes with successful automated retinal nerve fiber layer (RNFL) segmentations obtained from our previously reported graph-based segmentation method and 270 volumes with failed segmentations. To evaluate the reliability of the layer segmentations, we have developed a new metric, segmentability index SI, which is obtained from a random forest regressor based on 12 features using OCT voxel intensities, edge-based costs, and on-surface costs. The SI was compared with well-known quality indices, quality index (QI), and maximum tissue contrast index (mTCI), using receiver operating characteristic (ROC) analysis.The 95% confidence interval (CI) and the area under the curve (AUC) for the QI are 0.621 to 0.805 with AUC 0.713, for the mTCI 0.673 to 0.838 with AUC 0.756, and for the SI 0.784 to 0.920 with AUC 0.852. The SI AUC is significantly larger than either the QI or mTCI AUC (P < 0.01).The segmentability index SI is well suited to identify SD-OCT scans for which successful automated intraretinal layer segmentations can be expected.Interpreting the quantification of SD-OCT images requires the underlying segmentation to be reliable, but standard SD-OCT quality metrics do not predict which segmentations are reliable and which are not. The segmentability index SI presented in this study does allow reliable segmentations to be identified, which is important for more accurate layer thickness analyses in research and population studies.
| S-EPMC4824284 | biostudies-other
Project description:PurposeTo investigate variation and determinants of macular layers, peripapillary retinal nerve fiber layer (pRNFL) and Bruch's membrane opening-minimum rim width (BMO-MRW) in the general population.MethodsIn 1306 participants, we performed spectral domain optical coherence tomography (SD-OCT) scans of the macula, pRNFL, and BMO-MRW, and assessed their determinants using multivariable regression. Intraindividual interocular differences were analyzed using Spearman's rank correlation analysis.ResultsParticipant age ranged from 30 to 95 years (mean ± standard deviation, 56.1 ± 13.9) and 56% were women. Interocular correlation ranged from 0.63 to 0.93. Differences increased with age and were larger in persons with glaucoma or prior stroke. pRNFL and BMO-MRW decreased with increasing age. Except for RNFL, volumes of various inner macular layers and the outer nuclear layer (ONL) decreased with increasing age, more negative spherical equivalent (SE), and were lower in women compared to men. For some layers, age effects amplified over the life course. History of stroke was associated with smaller volumes of various layers, without reaching statistical significance. We found no association of further systemic parameters with any SD-OCT parameter.ConclusionsWe provide large-scale normative data from a Caucasian general population for various SD-OCT measures. Interocular variability increased with age and specific pathology. Factors, such as age, sex, refraction, and a history of stroke, were associated with various retinal assessments.Translational relevanceIn clinical routine, our findings should be considered on a per eye basis when interpreting SD-OCT volumes, pRNFL, or BMO-MRW to avoid confounded results.
| S-EPMC6549562 | biostudies-literature
Project description:BACKGROUND:To evaluate the diagnostic ability of macular ganglion cell asymmetry to diagnose preperimetric glaucoma (PPG), using Cirrus spectral domain optical coherence tomography (OCT). METHODS:This prospective study included 67 eyes of 67 patients with PPG and 67 eyes of 67 age- and refractive error-matched controls. We measured circumpapillary RNFL (cpRNFL) thickness, macular ganglion cell-inner plexiform layer (GCIPL) thickness and optic nerve head (ONH) parameters using OCT. Macular ganglion cell asymmetries were expressed as absolute difference and ratios between inferior hemisphere and superior hemisphere, inferotemporal (IT) and superotemporal (ST), IT and superonasal (SN), IT and inferonasal (IN), ST and IN as well as temporal and nasal. An asymmetry index was assigned by taking the absolute value of log10 of the ratio. The area under the receiver operating characteristics curve (AUROC), partial AUROC (pAUROC)???specificities 90 and 95%, cutoff values and sensitivities at specificities 90 and 95% was analyzed. RESULTS:Parameters with largest AUROCs were IT GCIPL thickness (0.784), average RNFL thickness (0.767), and average C/D (0.746). For macular asymmetry parameters, log IT/SN index had the largest AUROC (0.734), followed by log IT/IN index (0.725), and absolute difference of IT-SN GCIPL thickness (0.715). Performance was comparable between the best measures of asymmetry analysis (log IT/SN index) and those of cpRNFL, GCIPL, and ONH parameters (all P?>?0.05). The IT/SN asymmetry index not only had the largest pAUROC based on the pAUROCs ?90 and 95% specificity (0.044 and 0.019) but also had the highest diagnostic sensitivity at 90 and 95% specificities (52.2 and 46.3%). CONCLUSIONS:GCIPL asymmetry measurements have diagnostic ability comparable to cpRNFL, GCIPL, and ONH analysis for PPG. The best macular ganglion cell asymmetry parameter was IT/SN asymmetry index, which could be a new parameter to detect early structural changes in PPG.
| S-EPMC6325869 | biostudies-other
Project description:Disruption of external limiting membrane (ELM) integrity on spectral-domain optical coherence tomography (SD-OCT) is associated with lower visual acuity outcomes in patients suffering from diabetic macular edema (DME). However, no automated methods to detect ELM and/or determine its integrity from SD-OCT exist.Sixteen subjects diagnosed with clinically significant DME (CSME) were included and underwent macula-centered SD-OCT (512 × 19 × 496 voxels). Sixteen subjects without retinal thickening and normal acuity were also scanned (200 × 200 × 1024 voxels). Automated quantification of ELM disruption was achieved as follows. First, 11 surfaces were automatically segmented using our standard 3-D graph-search approach, and the subvolume between surface 6 and 11 containing the ELM region was flattened based on the segmented retinal pigment epithelium (RPE) layer. A second, edge-based graph-search surface-detection method segmented the ELM region in close proximity "above" the RPE, and each ELM A-scan was classified as disrupted or nondisrupted based on six texture features in the vicinity of the ELM surface. The vessel silhouettes were considered in the disruption classification process to avoid false detections of ELM disruption.In subjects with CSME, large areas of disrupted ELM were present. In normal subjects, ELM was largely intact. The mean and 95% confidence interval (CI) of the detected disruption area volume for normal and CSME subjects were mean(normal) = 0.00087 mm(3) and CI(normal) = (0.00074, 0.00100), and mean(CSME) = 0.00461 mm(3) and CI(CSME) = (0.00347, 0.00576) mm(3), respectively.In this preliminary study, we were able to show that automated quantification of ELM disruption is feasible and can differentiate continuous ELM in normal subjects from disrupted ELM in subjects with CSME. We have started determining the relationships of quantitative ELM disruption markers to visual outcome in patients undergoing treatment for CSME.
| S-EPMC3517271 | biostudies-other
Project description:The purpose of this study was to measure central macular thickness in an unprecedented number of cynomolgus monkeys. Macular thickness was measured with Heidelberg spectral-domain OCT in 320 eyes of healthy and treatment-naïve cynomolgus monkeys (80 males and 80 females). The macula was successfully measured in all 320 eyes. Macular thickness was not significantly different between the sexes. The mean central macular thickness was 244 μm (+/- 21 μm). Macular thicknesses in the quadrants were 327 +/-17 μm (temporal inner), 339 +/- 17 μm (inferior inner), 341 +/- 14 μm (superior inner), 341 +/-18 μm (nasal inner), and 299 +/- 20 μm (temporal outer), 320 +/- 16 μm (superior outer), 332 +/-23 μm (inferior outer), and 337 +/-18 μm (nasal outer). Highly significant differences between the nasal and temporal quadrants were detected. This study successfully demonstrated the feasibility of retinal thickness measurements in healthy cynomolgus monkeys. The present findings indicate that the macula is thicker in cynomolgus monkeys than in humans and provide important normative data for future studies.
| S-EPMC6779255 | biostudies-literature
Project description:PurposeTo assess the diagnostic utility of a new hemifield asymmetry analysis derived using pattern recognition contrast sensitivity isocontours (CSIs) within the Humphrey Field Analyzer (HFA) 24-2 visual field (VF) test grid. The performance of an optimal CSI-derived map was compared against a commercially available clustering method (Glaucoma Hemifield Test, GHT).MethodsFive hundred VF results of 116 healthy subjects were used to determine normative distribution limits for comparisons. Pattern recognition analysis was applied to HFA 24-2 sensitivity data to determine CSI theme maps delineating clusters for hemifield comparisons. Then, 1019 VF results from 228 glaucoma patients were assessed using different clustering methods to determine the true-positive rate. We also assessed additional 354 VF results of 145 healthy subjects to determine the false-positive rate.ResultsThe optimum clustering method was the CSI-derived seven-theme class map, which identified more glaucomatous VFs compared with the GHT map. The seven-class theme map also identified more cases compared with the five-, six-, and eight-class maps, suggesting no effect of number of clusters. Integrating information regarding the location of glaucomatous defects to the CSI clusters did not improve detection rate.ConclusionsA clustering map derived using CSIs improved detection of glaucomatous VFs compared with the currently available GHT. An optimized CSI-derived map may serve as an additional means to aid earlier detection of glaucoma.Translational relevancePattern recognition-derived theme maps provide a means for guiding test point selection for asymmetry analysis in glaucoma assessment.
| S-EPMC6126954 | biostudies-literature