Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images.
ABSTRACT: 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.
Project description:<h4>Objective</h4>To define quantitative indicators for the presence of intermediate age-related macular degeneration (AMD) via spectral-domain optical coherence tomography (SD-OCT) imaging of older adults.<h4>Design</h4>Evaluation of diagnostic test and technology.<h4>Participants and controls</h4>One eye from 115 elderly subjects without AMD and 269 subjects with intermediate AMD from the Age-Related Eye Disease Study 2 (AREDS2) Ancillary SD-OCT Study.<h4>Methods</h4>We semiautomatically delineated the retinal pigment epithelium (RPE) and RPE drusen complex (RPEDC, the axial distance from the apex of the drusen and RPE layer to Bruch's membrane) and total retina (TR, the axial distance between the inner limiting and Bruch's membranes) boundaries. We registered and averaged the thickness maps from control subjects to generate a map of "normal" non-AMD thickness. We considered RPEDC thicknesses larger or smaller than 3 standard deviations from the mean as abnormal, indicating drusen or geographic atrophy (GA), respectively. We measured TR volumes, RPEDC volumes, and abnormal RPEDC thickening and thinning volumes for each subject. By using different combinations of these 4 disease indicators, we designed 5 automated classifiers for the presence of AMD on the basis of the generalized linear model regression framework. We trained and evaluated the performance of these classifiers using the leave-one-out method.<h4>Main outcome measures</h4>The range and topographic distribution of the RPEDC and TR thicknesses in a 5-mm diameter cylinder centered at the fovea.<h4>Results</h4>The most efficient method for separating AMD and control eyes required all 4 disease indicators. The area under the curve (AUC) of the receiver operating characteristic (ROC) for this classifier was >0.99. Overall neurosensory retinal thickening in eyes with AMD versus control eyes in our study contrasts with previous smaller studies.<h4>Conclusions</h4>We identified and validated efficient biometrics to distinguish AMD from normal eyes by analyzing the topographic distribution of normal and abnormal RPEDC thicknesses across a large atlas of eyes. We created an online atlas to share the 38?400 SD-OCT images in this study, their corresponding segmentations, and quantitative measurements.
Project description:Spectral-domain optical coherence tomography (SD-OCT) represents a reliable tool for retinal layer volume and thickness measurement. The aim of this study was to evaluate retinal changes indicating neurodegenerative processes in patients with end-stage renal disease (ESRD) compared to healthy controls. This was a cross-sectional, single-center study comprising 32 ESRD patients and 38 controls. Sectoral retinal nerve fiber layer (RNFL) thickness and retinal layer volumes were obtained by SD-OCT. Age- and gender-adjusted retinal layer volumes such as total retinal volume (p?=?0.037), ganglion cell layer volume (GCL, p?=?0.003), ganglion cell layer - inner plexiform layer volume (GCL-IPL, p?=?0.005) and inner retinal layer volume (IRL, p?=?0.042) of the right eye were lower in ESRD patients. Inner plexiform layer volume of both eyes (IPL, right eye: p?=?0.017; left eye: 0.044) was reduced, as was RNFL thickness in the temporal superior sector (right eye: p?=?0.016). A subgroup analysis excluding patients with diabetes revealed that GCL (p?=?0.014) and GCL-IPL volume of the right eye (p?=?0.024) and temporal superior sector of the RNFL scan (p?=?0.021) in ESRD patients were still significantly thinner. We observed a decrease in several retinal layer volumes and temporal RNFL thickness indicative of retinal neurodegenerative processes in patients with ESRD.
Project description:In macular spectral domain optical coherence tomography (SD-OCT) volumes, detection of the foveal center is required for accurate and reproducible follow-up studies, structure function correlation, and measurement grid positioning. However, disease can cause severe obscuring or deformation of the fovea, thus presenting a major challenge in automated detection. We propose a fully automated fovea detection algorithm to extract the fovea position in SD-OCT volumes of eyes with exudative maculopathy. The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. Based on foveal type classification, the fovea position is computed based on retinal nerve fiber layer thickness. Mean absolute distance between system and clinical expert annotated fovea positions from a dataset comprised of 240 SD-OCT volumes was 162.3?µm in cystoid macular edema and 262?µm in nAMD. The presented method has cross-vendor functionality, while demonstrating accurate and reliable performance close to typical expert interobserver agreement. The automatically detected fovea positions may be used as landmarks for intra- and cross-patient registration and to create a joint reference frame for extraction of spatiotemporal features in "big data." Furthermore, reliable analyses of retinal thickness, as well as retinal structure function correlation, may be facilitated.
Project description:To correlate the thicknesses of focal regions of the macular ganglion cell layer with those of the peripapillary nerve fiber layer using spectral-domain optical coherence tomography (SD-OCT) in glaucoma subjects.Macula and optic nerve head SD-OCT volumes were obtained in 57 eyes of 57 subjects with open-angle glaucoma or glaucoma suspicion. Using a custom automated computer algorithm, the thickness of 66 macular ganglion cell layer regions and the thickness of 12 peripapillary nerve fiber layer regions were measured from registered SD-OCT volumes. The mean thickness of each ganglion cell layer region was correlated to the mean thickness of each peripapillary nerve fiber layer region across subjects. Each ganglion cell layer region was labeled with the peripapillary nerve fiber layer region with the highest correlation using a color-coded map.The resulting color-coded correlation map closely resembled the nerve fiber bundle (NFB) pattern of retinal ganglion cells. The mean r(2) value across all local macular-peripapillary correlations was 0.49 (± 0.11). When separately analyzing the 30 glaucoma subjects from the 27 glaucoma-suspect subjects, the mean r(2) value across all local macular-peripapillary correlations was significantly larger in the glaucoma group (0.56 ± 0.13 vs. 0.37 ± 0.11; P < 0.001).A two-dimensional (2-D) spatial NFB map of the retina can be developed using structure-structure relationships from SD-OCT. Such SD-OCT-based NFB maps may enhance glaucoma detection and contribute to monitoring change in the future.
Project description:To provide a comprehensive histopathological validation of cardiac magnetic resonance (CMR) and endocardial voltage mapping of acute and chronic atrial ablation injury.16 pigs underwent pre-ablation T2-weighted (T2W) and late gadolinium enhancement (LGE) CMR and high-density voltage mapping of the right atrium (RA) and both were repeated after intercaval linear radiofrequency ablation. Eight pigs were sacrificed following the procedure for pathological examination. A further eight pigs were recovered for 8 weeks, before chronic CMR, repeat RA voltage mapping and pathological examination. Signal intensity (SI) thresholds from 0 to 15 SD above a reference SI were used to segment the RA in CMR images and segmentations compared with real lesion volumes. The SI thresholds that best approximated histological volumes were 2.3 SD for LGE post-ablation, 14.5 SD for T2W post-ablation and 3.3 SD for LGE chronically. T2-weighted chronically always underestimated lesion volume. Acute histology showed transmural injury with coagulative necrosis. Chronic histology showed transmural fibrous scar. The mean voltage at the centre of the ablation line was 3.3 mV pre-ablation, 0.6 mV immediately post-ablation, and 0.3 mV chronically.This study presents the first histopathological validation of CMR and endocardial voltage mapping to define acute and chronic atrial ablation injury, including SI thresholds that best match histological lesion volumes. An understanding of these thresholds may allow a more informed assessment of the underlying atrial substrate immediately after ablation and before repeat catheter ablation for atrial arrhythmias.
Project description:PURPOSE:To determine optimal objective, machine-derived variables and variable combinations from Scheimpflug and spectral-domain (SD) OCT imaging to distinguish the clinically unaffected eye in patients with asymmetric keratoconus (AKC) from a normal control population. DESIGN:Retrospective case-control study. PARTICIPANTS:Thirty clinically unaffected eyes with no physical findings on slit-lamp examination, no definitive abnormalities on corneal imaging, and corrected distance acuity of 20/20 or better from 30 patients with highly AKC eyes and 60 eyes from 60 normal control patients who had undergone uneventful LASIK with at least 2 years of stable follow-up (controls). METHODS:Scheimpflug and SD OCT imaging were obtained in all eyes, and receiver operating characteristic (ROC) curves were generated to determine area under the curve (AUC), sensitivity, and specificity for each machine-derived variable and variable combination. MAIN OUTCOME MEASURES:Distinguishing AKC eyes from controls as determined by AUC, sensitivity, and specificity. RESULTS:No individual machine-derived metric from Scheimpflug or SD OCT technology yielded an AUC higher than 0.75. Combining 5 Scheimpflug metrics (index height decentration [IHD], index vertical asymmetry [IVA], pachymetry apex, inferior-superior value, and Ambrosio's Relational Thickness Maximum [ARTmax]) yielded the best Scheimpflug results (AUC 0.86, sensitivity 83%, specificity 83%). Combining 11 SD OCT thickness metrics (minimum-median, temporal outer, superior nasal outer, minimum, epithelium minimum-maximum, epithelial standard deviation, superior inner, superior outer, superior temporal outer, superior nasal inner, central) yielded the best SD OCT results (AUC 0.96, sensitivity 89%, specificity 89%). Combining 13 total Scheimpflug/SD OCT metrics yielded the best results overall (AUC 1.0, sensitivity 100%, specificity 100%). The most impactful variables in combined models included epithelial thickness variability and total focal corneal thickness variability from SD OCT and anterior curvature and topometric indices from Scheimpflug technology. No posterior corneal metrics were impactful in modeling. CONCLUSIONS:Individual machine-derived metrics from Scheimpflug and SD OCT imaging poorly distinguished normal eyes from minimally affected eyes from patients with highly AKC. Combined SD OCT metrics performed better than combined Scheimpflug metrics. Combining anterior curvature and asymmetry indices from Scheimpflug with regional total thickness and epithelial thickness variability metrics from SD OCT clearly distinguished the 2 populations. Posterior corneal indices were not useful in distinguishing populations.
Project description:To evaluate the diagnostic ability of macular ganglion cell and inner plexiform layer measurements in glaucoma, obtained using swept source (SS) and spectral domain (SD) optical coherence tomography (OCT) and to compare to circumpapillary retinal nerve fiber layer (cpRNFL) thickness measurements.The study included 106 glaucomatous eyes of 80 subjects and 41 eyes of 22 healthy subjects from the Diagnostic Innovations in Glaucoma Study. Macular ganglion cell and inner plexiform layer (mGCIPL), macular ganglion cell complex (mGCC) and cpRNFL thickness were assessed using SS-OCT and SD-OCT, and area under the receiver operating characteristic curves (AUCs) were calculated to determine ability to differentiate glaucomatous and healthy eyes and between early glaucomatous and healthy eyes.Mean (± standard deviation) mGCIPL and mGCC thickness were thinner in both healthy and glaucomatous eyes using SS-OCT compared to using SD-OCT. Fixed and proportional biases were detected between SS-OCT and SD-OCT measures. Diagnostic accuracy (AUCs) for differentiating between healthy and glaucomatous eyes for average and sectoral mGCIPL was similar in SS-OCT (0.65 to 0.81) and SD-OCT (0.63 to 0.83). AUCs for average cpRNFL acquired using SS-OCT and SD-OCT tended to be higher (0.83 and 0.85, respectively) than for average mGCC (0.82 and 0.78, respectively), and mGCIPL (0.73 and 0.75, respectively) but these differences did not consistently reach statistical significance. Minimum SD-OCT mGCIPL and mGCC thickness (unavailable in SS-OCT) had the highest AUC (0.86) among macular measurements.Assessment of mGCIPL thickness using SS-OCT or SD-OCT is useful for detecting glaucomatous damage, but measurements are not interchangeable for patient management decisions. Diagnostic accuracies of mGCIPL and mGCC from both SS-OCT and SD-OCT were similar to that of cpRNFL for glaucoma detection.
Project description:Introduction:To evaluate the sectorial thickness of single retinal layers and optic nerve using spectral domain optic coherence tomography (SD-OCT) and highlight the parameters with the best diagnostic accuracy in distinguishing between normal and glaucoma subjects at different stages of the disease. Material and Methods:For this cross-sectional study, 25 glaucomatous (49 eyes) and 18 age-matched healthy subjects (35 eyes) underwent a complete ophthalmologic examination including visual field testing. Sectorial thickness values of each retinal layer and of the optic nerve were measured using SD-OCT Glaucoma Module Premium Edition (GMPE) software. Each parameter was compared between the groups, and the layers and sectors with the best area under the receiver operating characteristic curve (AUC) were identified. Correlation of visual field index with the most relevant structural parameters was also evaluated. Results and Discussion:All subjects were grouped according to stage as follows: Controls (CTRL); Early Stage Group (EG) (Stage 1?+?Stage 2); Advanced Stage Group (AG) (Stage 3?+?Stage 4?+?Stage 5). mGCL TI, mGCL TO, mIPL TO, mean mGCL, cpRNFLt NS, and cpRNFLt TI showed the best results in terms of AUC according classification proposed by Swets (0.9?<?AUC?<?1.0). These parameters also showed significantly different values among group when CTRL vs EG, CTRL vs AG, and EG vs AG were compared. SD-OCT examination showed significant sectorial thickness differences in most of the macular layers when glaucomatous patients at different stages of the disease were compared each other and to the controls.
Project description:Purpose:To 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. Methods:In 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. Results:Participant 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. Conclusions:We 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 Relevance:In 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.
Project description:Purpose:To evaluate visual streak (VS) identification on spectral-domain optical coherence tomography (SD-OCT) scans in awake rabbits. To report thickness measurements in the VS and adjacent retina on OCT B-scans and histologic sections and to assess inter-method bias, precision and repeatability between OCT and histology. Methods:Vertical SD-OCT B-scan images through the optic nerve head and VS were acquired from 16 awake, ophthalmologically healthy experimental rabbits. Scans were acquired from both eyes, which were later enucleated and processed for light microscopy. Inner retina, inner nuclear layer, outer nuclear layer, outer retina (OR) and photoreceptor outer segment (PROS) thickness were measured on OCT images and digitalized microscopy slides in- and outside of the VS, and compared using linear mixed effects models. Results:Both SD-OCT and histology allowed retinal layer identification and measurement. On OCT, OR and PROS were thickest in the central VS and thinnest outside the VS. Histology mirrored OCT results for central outer retinal layers but shows discrepancies for other layers likely because of postmortem processing artifacts. The method comparison demonstrated better repeatability for OCT measurements compared with histology. Conclusions:Increased OR and PROS thickness compared with the adjacent retina allowed identification of the VS on SD-OCT in awake rabbits. OCT allows measurements devoid of processing artifacts in contrast to histology. Translational Relevance:SD-OCT is possible in awake rabbits. Easy and reliable identification of the VS may facilitate the positioning and use of rabbits as model species in human macular and generalized retinal disease research.