Fiber-based polarization-sensitive OCT for birefringence imaging of the anterior eye segment.
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ABSTRACT:
SUBMITTER: Yamanari M
PROVIDER: S-EPMC4354580 | biostudies-other | 2015 Feb
REPOSITORIES: biostudies-other
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Project description:PurposeTo quantify interquadrant differences in anterior chamber angle (ACA) configuration assessed on gonioscopy, EyeCam, and anterior segment optical coherence tomography (AS-OCT) in a cohort of Chinese Americans.MethodsSubjects aged 50 years or older were recruited from the Chinese American Eye Study (CHES), a population-based epidemiologic study in Los Angeles, CA. Each subject underwent a complete ocular exam, including gonioscopy, EyeCam, and AS-OCT, under dark ambient lighting. Gonioscopy and AS-OCT imaging and EyeCam image grading were performed by trained ophthalmologists.ResultsSeven hundred nine eyes from 709 subjects were analyzed. Less anatomic variation among the quadrants was detected on gonioscopy and EyeCam compared with AS-OCT (P < 0.05). The mean gonioscopy grade, EyeCam grade, and AS-OCT measurement for each quadrant varied by up to 10.3%, 6.4%, and 46.2% of the superior quadrant value, respectively. There were significant interquadrant differences (P < 0.05) among mean AOD750 measurements when grouping by quadrant and gonioscopy or EyeCam grade. Mean AOD750 measurements were smallest for the superior quadrant by between 14.3% and 38.1% and 17.4% and 37.9% on gonioscopy and EyeCam, respectively, compared with other quadrants.ConclusionsGonioscopy and EyeCam significantly underrepresent anatomic variations of the ACA compared with AS-OCT. Gonioscopy or EyeCam grades from different quadrants do not appear to be comparable or interchangeable, which supports reconsideration of current definitions and methods used to diagnose and manage primary angle closure disease.Translational relevanceAS-OCT imaging raises concerns about current clinical definitions and methods that rely gonioscopy or EyeCam to assess the ACA.
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Project description:We demonstrate swept source OCT utilizing vertical-cavity surface emitting laser (VCSEL) technology for in vivo high speed retinal, anterior segment and full eye imaging. The MEMS tunable VCSEL enables long coherence length, adjustable spectral sweep range and adjustable high sweeping rate (50-580 kHz axial scan rate). These features enable integration of multiple ophthalmic applications into one instrument. The operating modes of the device include: ultrahigh speed, high resolution retinal imaging (up to 580 kHz); high speed, long depth range anterior segment imaging (100 kHz) and ultralong range full eye imaging (50 kHz). High speed imaging enables wide-field retinal scanning, while increased light penetration at 1060 nm enables visualization of choroidal vasculature. Comprehensive volumetric data sets of the anterior segment from the cornea to posterior crystalline lens surface are also shown. The adjustable VCSEL sweep range and rate make it possible to achieve an extremely long imaging depth range of ~50 mm, and to demonstrate the first in vivo 3D OCT imaging spanning the entire eye for non-contact measurement of intraocular distances including axial eye length. Swept source OCT with VCSEL technology may be attractive for next generation integrated ophthalmic OCT instruments.
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Project description:In myopic eyes, pathological remodelling of collagen in the posterior sclera has mostly been observed ex vivo. Here we report the development of triple-input polarization-sensitive optical coherence tomography (OCT) for measuring posterior scleral birefringence. In guinea pigs and humans, the technique offers superior imaging sensitivities and accuracies than dual-input polarization-sensitive OCT. In 8-week-long studies with young guinea pigs, scleral birefringence was positively correlated with spherical equivalent refractive errors and predicted the onset of myopia. In a cross-sectional study involving adult individuals, scleral birefringence was associated with myopia status and negatively correlated with refractive errors. Triple-input polarization-sensitive OCT may help establish posterior scleral birefringence as a non-invasive biomarker for assessing the progression of myopia.
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Project description:PurposeTo develop a deep neural network that detects the scleral spur in anterior segment optical coherence tomography (AS-OCT) images.MethodsParticipants in the Chinese American Eye Study, a population-based study in Los Angeles, California, underwent complete ocular examinations, including AS-OCT imaging with the Tomey CASIA SS-1000. One human expert grader provided reference labels of scleral spur locations in all images. A convolutional neural network (CNN)-based on the ResNet-18 architecture was developed to detect the scleral spur in each image. Performance of the CNN model was assessed by calculating prediction errors, defined as the difference between the Cartesian coordinates of reference and CNN-predicted scleral spur locations. Prediction errors were compared with intragrader variability in detecting scleral spur locations by the reference grader.ResultsThe CNN was developed using a training dataset of 17,704 images and tested using an independent dataset of 921 images. The mean absolute prediction errors of the CNN model were 49.27 ± 42.07 µm for X-coordinates and 47.73 ± 39.70 µm for Y-coordinates. The mean absolute intragrader variability was 52.31 ± 47.75 µm for X-coordinates and 45.88 ± 45.06 µm for Y-coordinates. Distributions of prediction errors for the CNN and intragrader variability for the reference grader were similar for X-coordinates (P = 0.609) and Y-coordinates (P = 0.378). The mean absolute prediction error of the CNN was 73.08 ± 52.06 µm and the mean absolute intragrader variability was 73.92 ± 60.72 µm.ConclusionsA deep neural network can detect the scleral spur on AS-OCT images with performance similar to that of a human expert grader.Translational relevanceDeep learning methods that automate scleral spur detection can facilitate qualitative and quantitative assessments of AS-OCT images.
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Project description:Optical projection tomography (OPT) is a tool used for three-dimensional imaging of millimeter-scale biological samples, with the advantage of exhibiting isotropic resolution typically in the micron range. OPT can be divided into two types: transmission OPT (tOPT) and emission OPT (eOPT). Compared with eOPT, tOPT discriminates different tissues based on their absorption coefficient, either intrinsic or after specific staining. However, it fails to distinguish muscle fibers whose absorption coefficients are similar to surrounding tissues. To circumvent this problem, in this article we demonstrate a polarization sensitive OPT system which improves the detection and 3D imaging of muscle fibers by using polarized light. We also developed image acquisition and processing protocols that, together with the system, enable the clear visualization of muscles. Experimental results show that the muscle fibers of diaphragm and stomach, difficult to be distinguished in regular tOPT, were clearly displayed in our system, proving its potential use. Moreover, polarization sensitive OPT was fused with tOPT to investigate the stomach tissue comprehensively. Future applications of polarization sensitive OPT could be imaging other fiber-like structures such as myocardium or other tissues presenting high optical anisotropy.
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Project description:PurposeTo assess the effects of age and refractive status on anterior segment anatomical structures, including the ciliary body, using a new swept-source anterior segment optical coherence tomography (AS-OCT) device.MethodsThis prospective observational study included 63 healthy volunteers (mean age: 44.2 years). Images of the anterior segment were obtained using a new swept-source AS-OCT (ANTERION, Heidelberg Engineering GmbH, Heidelberg, Germany) with tracking and image averaging from the right eye of all participants. Repeatability as well as inter- and intra-observer reliability of biometric measurements were evaluated. The impact of image tracking and averaging on ciliary muscle measurements was tested. Univariate and multivariable statistical models were developed to evaluate the relationship of age and refractive status on anterior segment biometric measurements.ResultsFor all test-retest repeatability and inter- and intra-observer reproducibility of swept-source AS-OCT measurements, high intraclass correlation (ICC) was noted (0.88-1.00). The nasal maximum ciliary muscle thickness (CMTMAX) and distance between scleral spur to the thickest point of the ciliary muscle (SSMAX) were larger than those on the temporal side (p<0.001 and p = 0.006, respectively). Nasal and temporal CMTMAX (p = 0.004 and p<0.001, respectively) and lens thickness (p<0.01) increased with age. Nasal and temporal SSMAX decreased with older age and increasing hyperopia (p = 0.01 and p<0.001, respectively). Image averaging resulted in improved ciliary muscle measurements (p = 0.008 to 0.02). Lens vault increased with older age and increased hyperopia (p<0.01). OCT measurements of the angle decreased with older age and increased hyperopia (p<0.001 to 0.03). Aqueous depth decreased with older age and increased hyperopia (p<0.01). Pupil diameter decreased with older age (p<0.01).ConclusionsRepeatability and reproducibility of biometric measurements using the ANTERION AS-OCT were excellent. Image averaging improved the accuracy of ciliary muscle measurements. The device produced measurements of biometric parameters that described superficial and deep structures including the ciliary body and full lens thickness from a single image.
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Project description:PURPOSE:To develop and test deep learning classifiers that detect gonioscopic angle closure and primary angle closure disease (PACD) based on fully automated analysis of anterior segment OCT (AS-OCT) images. METHODS:Subjects were recruited as part of the Chinese-American Eye Study (CHES), a population-based study of Chinese Americans in Los Angeles, California, USA. Each subject underwent a complete ocular examination including gonioscopy and AS-OCT imaging in each quadrant of the anterior chamber angle (ACA). Deep learning methods were used to develop 3 competing multi-class convolutional neural network (CNN) classifiers for modified Shaffer grades 0, 1, 2, 3, and 4. Binary probabilities for closed (grades 0 and 1) and open (grades 2, 3, and 4) angles were calculated by summing over the corresponding grades. Classifier performance was evaluated by 5-fold cross-validation and on an independent test dataset. Outcome measures included area under the receiver operating characteristic curve (AUC) for detecting gonioscopic angle closure and PACD, defined as either 2 or 3 quadrants of gonioscopic angle closure per eye. RESULTS:A total of 4036 AS-OCT images with corresponding gonioscopy grades (1943 open, 2093 closed) were obtained from 791 CHES subjects. Three competing CNN classifiers were developed with a cross-validation dataset of 3396 images (1632 open, 1764 closed) from 664 subjects. The remaining 640 images (311 open, 329 closed) from 127 subjects were segregated into a test dataset. The best-performing classifier was developed by applying transfer learning to the ResNet-18 architecture. For detecting gonioscopic angle closure, this classifier achieved an AUC of 0.933 (95% confidence interval, 0.925-0.941) on the cross-validation dataset and 0.928 on the test dataset. For detecting PACD based on 2- and 3-quadrant definitions, the ResNet-18 classifier achieved AUCs of 0.964 and 0.952, respectively, on the test dataset. CONCLUSION:Deep learning classifiers effectively detect gonioscopic angle closure and PACD based on automated analysis of AS-OCT images. These methods could be used to automate clinical evaluations of the ACA and improve access to eye care in high-risk populations.
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Project description:PurposeThis study aimed to investigate the performance of deep learning algorithms in the opportunistic screening for primary angle-closure disease (PACD) using combined anterior segment parameters.MethodsThis was an observational, cross-sectional hospital-based study. Patients with PACD and healthy controls who underwent comprehensive eye examinations, including gonioscopy and anterior segment optical coherence tomography (ASOCT) examinations under both light and dark conditions, were consecutively enrolled from the Department of Ophthalmology at the Beijing Tongren Hospital between November 2020 and June 2022. The anterior chamber, anterior chamber angle, iris, and lens parameters were assessed using ASOCT. To build the prediction models, backward logistic regression was utilized to select the variables to discriminate patients with PACD from normal participants, and the area under the receiver operating characteristic curve was used to evaluate the efficacy of the opportunistic screening.ResultsThe data from 199 patients (199 eyes) were included in the final analysis and divided into two groups: PACD (109 eyes) and controls (90 eyes). Angle opening distance at 500 μm, anterior chamber area, and iris curvature measured in the light condition were included in the final prediction models. The area under the receiver operating characteristic curve was 0.968, with a sensitivity of 91.74 % and a specificity of 91.11 %.ConclusionASOCT-based algorithms showed excellent diagnostic performance in the opportunistic screening for PACD. These results provide a promising basis for future research on the development of an angle-closure probability scoring system for PACD screening.
| S-EPMC11002240 | biostudies-literature
Project description:Laser Doppler holography (LDH) is a full-field blood flow imaging technique able to reveal human retinal and choroidal blood flow with high temporal resolution. We here report on using LDH in the anterior segment of the eye without making changes to the instrument. Blood flow in the bulbar conjunctiva and episclera as well as in corneal neovascularization can be effectively imaged. We additionally demonstrate simultaneous holographic imaging of the anterior and posterior segments by simply adapting the numerical propagation distance to the plane of interest. We used this feature to track the movements of the retina and pupil with high temporal resolution. Finally, we show that the light backscattered by the retina can be used for retro-illumination of the anterior segment. Hence digital holography can reveal opacities caused by absorption or diffusion in the cornea and eye lens.
| S-EPMC8367265 | biostudies-literature
Project description:PurposeTo investigate the characteristics of anterior chamber angle parameters in congenital ectopia lentis (CEL) patients and to evaluate the sensitivity and specificity of anterior segment parameters in distinguishing CEL from healthy controls. Setting. Zhongshan Ophthalmic Center, Guangzhou, China.DesignCross-sectional study.Methods35 CEL patients and 35 age- and sex-matched healthy controls were recruited. Axial length (AL) and anterior segment parameters including anterior chamber width (ACW), angle open distance (AOD), angle recess area (ARA), trabecular-iris space area (TISA), and trabecular-iris angle (TIA) were measured. All the above parameters and the ratio index of angle parameters, which was defined as the angle parameter value of the narrower side to that of the contralateral side, were compared between CEL and controls. Receiver operating characteristic (ROC) curves were also plotted to evaluate the diagnostic performance of anterior chamber angle parameters in CEL patients.ResultsAll angle parameters of the contralateral side to the dislocated lens side were significantly smaller than those of the dislocated lens side in CEL (all P < 0.05). For the diagnostic performance of anterior chamber angle parameters, the ratio index of TIAr500 combined with TIAr750 had the best diagnostic performance for CEL screening (AUC = 0.798), and TIAr500 of 0.887 and TIAr750 of 0.917 were detected to be the optimal cut-off points, representing a sensitivity of 89.8% and specificity of 68.7%.ConclusionThe contralateral side to the dislocated lens side in the CEL had a narrower anterior chamber angle. TIAr500 combined with TIAr750 is the optimal combination strategy for ectopia lentis screening.
| S-EPMC9192328 | biostudies-literature