Detection Of Angle Closure Research Articles

Diagnostic criteria of anterior segment swept-source optical coherence tomography to detect gonioscopic angle closure

AimsTo compare the diagnostic performance of 360° anterior segment optical coherence tomography assessment by applying normative percentile cut-offs versus iris trabecular contact (ITC) for detecting gonioscopic angle closure.MethodsIn this multicentre...

Diagnostic Abilities of Three-Dimensional Anterior Segment Optical Coherence Tomography in Detecting Angle Closure.

Three-dimensional (3D) angle parameters and cutoff values for detecting angle closure were proposed. The 3D parameters demonstrated excellent diagnostic performance. Certain horizontal two-dimensional (2D) parameters [ie, trabecular iris space area (TISA)-750, angle opening distance (AOD)-750, and AOD-500] can attain similar performance to their high-performing 3D counterparts. To investigate the diagnostic performance of single horizontal 2D versus 3D angle parameters from swept-source anterior segment optical coherence tomography (CASIA2) in detecting angle closure. The cross-sectional study included 118 phakic patients (59 open angles, 59 closed angles). AOD, angle recess area (ARA), and TISA at 250, 500, and 750μm from scleral spur were measured in 360-degree radial-scan images. The 3D information of each measurement was analyzed in 2 patterns: (1) average 3D parameter-the averaged value from 360-degree angle values and (2) estimate 3D parameter-the estimation of surface area of circumferential angle inlet (using AOD) or circumferential angle volume (using ARA and TISA). The areas under the receiver operating characteristic curve [areas under the curve (AUCs)] of eighteen 3D parameters were compared with 2D horizontal parameters. Among 3D parameters, AOD-500 estimate 3D gave the highest AUC (AUC: 0.950, cutoff: 6.09mm 2 ), followed by AOD-750 estimate 3D (AUC: 0.948, cutoff: 8.26mm 2 ). 3D parameters significantly increased the AUC of ARA-250 and TISA-250 (all P < 0.02) compared with the 2D parameters. No significant improvement in AUC was demonstrated for AOD-250 and all parameters at 500 and 750μm. No significant difference in AUC was found among the 6 maximum AUC parameters, which were AOD-750 horizontal 2D, AOD-500 estimate 3D, TISA-750 horizontal 2D, AOD-500 horizontal 2D, AOD-750 estimate 3D, and TISA-750 average 3D. The 3D-angle parameters had high performance in detecting angle closure. However, comparing a horizontal measurement to 3D parameters, the AUC improvement was mostly insignificant.

ROLE OF ANTERIOR SEGMENT SPECTRAL DOMAIN OCT VS GONIOSCOPY IN DETECTING PRIMARY ANGLE CLOSURE IN A TERTIARY CARE CENTER IN UPPER ASSAM.

Objective- To evaluate anterior chamber angle to detect primary angle closure using anterior segment SD OCT vs Gonioscopy in a Tertiary Care Centre in upper assam. 30 eyes of 20 patients were examined. All patients unde Materials and methods- rwent comprehensive ocular examination, which included best corrected visual acuity, slit lamp examination, dilated fundus examination, intraocular pressure (IOP) measurement by Goldmann applanation tonometer, and gonioscopy. Consecutive patients fullling the inclusion and exclusion criteria were selected . After this, AS SD OCT was performed. Results A total of 30 eyes of 20 patients were examined over a period of six months. The mean age was found to be 50.75 ± 12.05 years. Out of 120 quadrants examined, primary angle closure was found in 75 quadrants in the gonioscopy (PTM not visible) and in 85 quadrants in the anterior segment OCT (Iridotrabecular contact). Overall sensitivity was found to be 95%, and specicity was found to be 70%. The mean trabecular iris angle and angle opening distance at 500 μm were found to be 10 degrees and 185 μm respectively. Conclusion Anterior segment SD OCT is a very sensitive tool that can act as a good screening tool for detecting angle closure

Comparison of Gonioscopy and Anterior Segment OCT for Detecting Angle Closure in Different Quadrants of Anterior Chamber Angle in Angle Closure Glaucoma

Purpose: To measure angle of anterior chamber with Gonioscopy and compare with anterior segment OCT. Study Design: Descriptive observational study. Place and Duration of Study: This study was conducted at the Department of Ophthalmology, Pakistan institute of Medical Sciences, Islamabad from 1st March 2021 to 31st August 2021. Methods: A total number of 102 patients participated in the study. Study included participants older than 30 years of age, of either gender, who were either diagnosed as a case of angle closure-Glaucoma or were angle closure-Glaucoma suspect. Sampling was done using convenient sampling technique. The selected patients underwent gonioscopy and the anterior segment OCT and the grades of the angle were determined. Grading was compared between the two techniques. The collected data was analyzed by using SPSS 23 version. Result: The mean age of patients was 59.16 ± 6.03 years. Out of 102 patients, 34 (33.3%) patients were male and 63 (66.7%) patients were female. The mean intraocular pressure was 17.80 ± 4.25 (mmHg). The accuracy of angle closure detection by Gonioscopy was 35.3% and by anterior segment, OCT was 60.8%. The p value was significant in both the groups. The Anterior segment OCT turned out to be better than Gonioscopy. Conclusion: Anterior segment OCT is more efficient in determination of angle of anterior chamber than gonioscopy. Using anterior segment OCT to examine anterior chamber angle and surrounding tissues helps in diagnosing early stages of disease and directing therapy.

MVGL-Net: A generalizable multi-view convolutional network for anterior segment OCT

ObjectiveCorrect diagnosis of primary angle-closure disease (PACD) and classification of plateau iris configuration (PIC) existence is essential for appropriate glaucoma treatment. A fast non-contact method that can automatically detect PACD and PIC would be valuable for improving treatment decisions and reducing the misdiagnosis rate. MethodsIn this work, we propose an automated method to analyze anterior segment optical coherence tomography (AS-OCT) images and test it on two tasks using two multi-institution datasets containing more than 12,000 image slices from more than 400 eyes. Our method, called multi-view glaucoma network (MVGL-Net), leverages the multi-view nature of AS-OCT images for PACD diagnosis and, more importantly, can detect PIC with minimal transfer learning. ResultsThe MVGL-Net achieves comparable prediction results to other published models when used for PACD diagnosis. In the PIC diagnosis task, MVGL-Net significantly outperforms the existing models on PACD and achieves performance comparable to manual measurements on the AS-OCT images reported in the literature with an AUC of 0.71. ConclusionsThe experimental results demonstrate that the MVGL-Net model is a fast, generalizable approach that, when compared with existing models, achieves comparable results for angle-closure detection and improved results for PIC diagnosis, a more challenging medical imaging task.

Diagnostic Performance of Optical Coherence Tomography and Nonspecialist Gonioscopy to Detect Angle Closure.

AimTo compare the usefulness of gonioscopy performed by general ophthalmologists (GO) and anterior segment optical coherence tomography (AS-OCT) in detecting angle closure in patients with a shallow anterior chamber.MethodsForty-four patients with a shallow anterior chamber (defined by a ratio of peripheral anterior chamber depth to peripheral corneal thickness lower than 1/2) were included in this cross-sectional study. Gonioscopy was performed in all subjects by two glaucoma experts (GE1 and GE2) and one GO. Anterior segment imaging was performed using Visante® OCT (Carl Zeiss Meditec Inc.). Agreement between examiners was assessed with first-order agreement coefficients (AC1). Diagnostic accuracies of GO gonioscopy and AS-OCT were evaluated using sensitivity, specificity, and area under the receiver operating characteristic (AROC) curves.ResultsFor static gonioscopy, the agreement between GE1 and GE2 was substantial (AC1 = 0.65), and that between GE1 and GO was moderate (AC1 = 0.50). For indentation gonioscopy, the agreement between GE1 and GE2 was slightly lower (AC1 = 0.55); however, the agreement between GE1 and GO showed a larger reduction (AC1 = 0.12). GO's gonioscopy presented a low specificity (25%) and the AROC to angle closure detection was lower than AS-OCT (0.56–0.73). Combined information of GO gonioscopy and AS-OCT improved specificity (85.7%) and AROC (0.77) of angle closure evaluation.ConclusionAgreement between GO and glaucoma experts was moderate for static gonioscopy and slight for indentation gonioscopy. AS-OCT performed better than GO gonioscopy in detecting angle closure in patients with a shallow anterior chamber. The addition of AS-OCT to clinical information in patients with GO positive gonioscopy improved the specificity and AROC of gonioscopy test.How to cite this articleEsporcatte BLB, Vessani RM, Melo Jr LAS, et al. Diagnostic Performance of Optical Coherence Tomography and Nonspecialist Gonioscopy to Detect Angle Closure. J Curr Glaucoma Pract 2022;16(1):53–58.

Diagnostic accuracy of AS-OCT vs gonioscopy for detecting angle closure: a systematic review and meta-analysis.

PurposeThis study aims to review the literature that compares the accuracy of Anterior Segment-Optical Coherence Tomography (AS-OCT) against gonioscopy in detecting eyes with angle closure. It is currently unclear how AS-OCT fits into clinical practice for detecting angle closure. This is a systematic review and meta-analysis.MethodsA literature search was performed on Medline, Embase, Scopus and the Cochrane Central Register of Controlled Trials to identify studies that investigated the diagnostic accuracy of AS-OCT in detecting eyes with angle closure as diagnosed by gonioscopy. Eligible studies included in the analysis met stringent inclusion criteria determining the sensitivity and specificity of AS-OCT.ResultsThe initial search identified 727 studies, of which 23 were included in the final analysis. We found substantial variation in the parameters being studied and methodologies. The sensitivity of AS-OCT ranged from 46 to 100% (median 87%). Twenty-one studies identified parameters that showed sensitivity above 80%. The specificity ranged from 55.3 to 100% (median 84%).ConclusionAS-OCT demonstrates good sensitivity for detecting angle closure. It may provide an avenue to address high rates of undiagnosed angle closure, such as found in developing Asian countries. However, AS-OCT is not yet able to replace gonioscopy. Clinicians should consider whether the diagnostic accuracy of AS-OCT is acceptable for their specific clinical use before adopting it. More studies are needed to determine the utility of AS-OCT, including longitudinal studies to determine the significance of eyes classified to have closed angles by AS-OCT but open on gonioscopy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00417-021-05271-4.

Population-Based Utility of van Herick Grading for Angle-Closure Detection

We report the sensitivity and specificity of van Herick (VH) grading in detecting gonioscopically-defined primary angle closure suspects (PACS) among subjects screened for participation in a population-based trial in southern China. A cut-off of VH≤25% was found to have sensitivity and specificity rates of 98.2% and 25.9%, respectively. Rates were adjusted for missing gonioscopy data, resulting in a sensitivity and specificity of 92.5% and 61.5%, respectively.

Assessment of Generative Adversarial Networks for Synthetic Anterior Segment Optical Coherence Tomography Images in Closed-Angle Detection

PurposeTo develop generative adversarial networks (GANs) that synthesize realistic anterior segment optical coherence tomography (AS-OCT) images and evaluate deep learning (DL) models that are trained on real and synthetic datasets for detecting angle closure.MethodsThe GAN architecture was adopted and trained on the dataset with AS-OCT images collected from the Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, synthesizing open- and closed-angle AS-OCT images. A visual Turing test with two glaucoma specialists was performed to assess the image quality of real and synthetic images. DL models, trained on either real or synthetic datasets, were developed. Using the clinicians’ grading of the AS-OCT images as the reference standard, we compared the diagnostic performance of open-angle vs. closed-angle detection of DL models and the AS-OCT parameter, defined as a trabecular-iris space area 750 µm anterior to the scleral spur (TISA750), in a small independent validation dataset.ResultsThe GAN training included 28,643 AS-OCT anterior chamber angle (ACA) images. The real and synthetic datasets for DL model training have an equal distribution of open- and closed-angle images (all with 10,000 images each). The independent validation dataset included 238 open-angle and 243 closed-angle AS-OCT ACA images. The image quality of real versus synthetic AS-OCT images was similar, as assessed by the two glaucoma specialists, except for the scleral spur visibility. For the independent validation dataset, both DL models achieved higher areas under the curve compared with TISA750. Two DL models had areas under the curve of 0.97 (95% confidence interval, 0.96–0.99) and 0.94 (95% confidence interval, 0.92–0.96).ConclusionsThe GAN synthetic AS-OCT images appeared to be of good quality, according to the glaucoma specialists. The DL models, trained on all-synthetic AS-OCT images, can achieve high diagnostic performance.Translational RelevanceThe GANs can generate realistic AS-OCT images, which can also be used to train DL models.

Towards ‘automated gonioscopy’: a deep learning algorithm for 360° angle assessment by swept-source optical coherence tomography

AimsTo validate a deep learning (DL) algorithm (DLA) for 360° angle assessment on swept-source optical coherence tomography (SS-OCT) (CASIA SS-1000, Tomey Corporation, Nagoya, Japan).MethodsThis was a reliability analysis from a...

Glaucoma Expert-Level Detection of Angle Closure in Goniophotographs With Convolutional Neural Networks: The Chinese American Eye Study

To compare the performance of a novel convolutional neural network (CNN) classifier and human graders in detecting angle closure in EyeCam (Clarity Medical Systems, Pleasanton, California, USA) goniophotographs. Retrospective cross-sectional study. Subjects from the Chinese American Eye Study underwent EyeCam goniophotography in 4 angle quadrants. A CNN classifier based on the ResNet-50 architecture was trained to detect angle closure, defined as inability to visualize the pigmented trabecular meshwork, using reference labels by a single experienced glaucoma specialist. The performance of the CNN classifier was assessed using an independent test dataset and reference labels by the single glaucoma specialist or a panel of 3 glaucoma specialists. This performance was compared to that of 9 human graders with a range of clinical experience. Outcome measures included area under the receiver operating characteristic curve (AUC) metrics and Cohen kappa coefficients in the binary classification of open or closed angle. The CNN classifier was developed using 29,706 open and 2,929 closed angle images. The independent test dataset was composed of 600 open and 400 closed angle images. The CNN classifier achieved excellent performance based on single-grader (AUC=0.969) and consensus (AUC=0.952) labels. The agreement between the CNN classifier and consensus labels (κ=0.746) surpassed that of all non-reference human graders (κ=0.578-0.702). Human grader agreement with consensus labels improved with clinical experience (P=0.03). A CNN classifier can effectively detect angle closure in goniophotographs with performance comparable to that of an experienced glaucoma specialist. This provides an automated method to support remote detection of patients at risk for primary angle closure glaucoma.

Potential of the Pentacam in Screening for Narrow Angles in Patients with Chronic Angle-Closure Glaucoma

Background: Chronic angle-closure glaucoma (CACG) is a visually destructive disease. Effective management of CACG requires identifying eyes with narrow angle.&#x0D; Objective: To compare pentacam with gonioscopy in detecting narrow angles in eyes with CACG.&#x0D; Method: We enrolled 101 eyes with glaucoma. Gonioscopy was performed on all eyes. Using Shaffer’s grading, subjects were classified into angle closure and open angle. Anterior chamber volume (ACV) and anterior chamber depth (ACD) were measured with the pentacam. Receiver operating curve was constructed for each parameter and the area under the curve (AUC) was calculated.&#x0D; Results: Ten eyes (9.9%) were classified as angle closure on gonioscopy. To detect narrow angles, ACV (AUC 0.956; 95% confidence interval (CI) 0.894–0.987) performed similar to ACD (AUC=0.930, p=0.33). Using a cutoff of 102 mm3 , ACV had 100% sensitivity and 88.5% specificity for detecting narrow angles in CACG patients. With an ACV cutoff of 102 mm3 , the PPV for detecting angle closure was 48.9% (95% CI, 34.8–68.2), while the NPV was 100% (94.1– 100%), using 9.9% prevalence of angle closure from this study.&#x0D; Conclusion: ACV and ACD measured by the pentacam have the potential to determine narrow angles in eyes with CACG.&#x0D; Keywords: Chronic angle-closure glaucoma, Pentacam HR, Anterior chamber volume, Gonioscopy

Evaluation of glaucoma cases with gonioscopy and optical coherence tomography

Glaucoma is the second leading cause of blindness in the adult population of India. Diagnosis and management depends on categorization of Glaucoma into open or closed angle. : To compare the accuracy of Gonioscopy and Anterior Segment Optical Coherence Tomography (ASOCT) in studying the structures of anterior chamber angle of the eye and find out the agreement between them in detecting angle closure. Cross -sectional observational study. The present study is a hospital based cross-sectional study of patients between 20 to 80 years of age with Glaucoma attending the outdoor patient department in a tertiary care government hospital (New civil hospital), Surat. Patients having Corneal Opacity, and anti-Glaucoma surgeries done were excluded. All diagnosed cases of Glaucoma were evaluated by Gonioscopy in the dark with a Goldman 3 mirror lens Gonioscope at high (16x) magnification for static assessment (without indentation). A narrow slit beam, 2mm* 1mm, was cast during Gonioscopy, avoiding direct illumination over the pupil. The angle in each quadrant was graded with the Shaffer grading system. Anterior Segment OCT was done by TOPCON 3D OCT-1 MAESTRO machine. Imaging was performed in dark room conditions. Patients were imaged gazing straight ahead. Imaging of a single meridional section of the Anterior Chamber Angle at superior, inferior, temporal and nasal quadrants were performed. Grading of Anterior Chamber Angles on AS-OCT is termed as Closed if there is no visualization of Scleral Spur and/or any degree of irido-trabecular contact. kappa value, sensitivity &amp; specificity, positive &amp; negative likelihood ratio. Total 50 Glaucoma patients were examined by Gonioscopy and AS OCT. Total number of Angles examined were 400. Total number of Angles closed on Gonioscopy were 136 (34%). Total number of Angles closed on AS OCT were 190 (47.5%). Agreement between Gonioscopy and AS OCT in detecting angle closure in all 4 quadrants was ‘Moderate to Good’ by Kappa Value.

A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images

Anterior segment optical coherence tomography (AS-OCT) provides an objective imaging modality for visually identifying anterior segment structures. An automated detection system could assist ophthalmologists in interpreting AS-OCT images for the presence of angle closure. Development of an artificial intelligence automated detection system for the presence of angle closure. A deep learning system for automated angle-closure detection in AS-OCT images was developed, and this was compared with another automated angle-closure detection system based on quantitative features. A total of 4135 Visante AS-OCT images from 2113 subjects (8270 anterior chamber angle images with 7375 open-angle and 895 angle-closure) were examined. The deep learning angle-closure detection system for a 2-class classification problem was tested by 5-fold cross-validation. The deep learning system and the automated angle-closure detection system based on quantitative features were evaluated against clinicians' grading of AS-OCT images as the reference standard. The area under the receiver operating characteristic curve of the system using quantitative features was 0.90 (95% confidence interval [CI] 0.891-0.914) with a sensitivity of 0.79 ± 0.037 and a specificity of 0.87 ± 0.009, while the area under the receiver operating characteristic curve of the deep learning system was 0.96 (95% CI 0.953-0.968) with a sensitivity of 0.90 ± 0.02 and a specificity of 0.92 ± 0.008, against clinicians' grading of AS-OCT images as the reference standard. The results demonstrate the potential of the deep learning system for angle-closure detection in AS-OCT images.

Angle-Closure Detection in Anterior Segment OCT Based on Multilevel Deep Network

Irreversible visual impairment is often caused by primary angle-closure glaucoma, which could be detected via anterior segment optical coherence tomography (AS-OCT). In this paper, an automated system based on deep learning is presented for angle-closure detection in AS-OCT images. Our system learns a discriminative representation from training data that captures subtle visual cues not modeled by handcrafted features. A multilevel deep network is proposed to formulate this learning, which utilizes three particular AS-OCT regions based on clinical priors: 1) the global anterior segment structure; 2) local iris region; and 3) anterior chamber angle (ACA) patch. In our method, a sliding window-based detector is designed to localize the ACA region, which addresses ACA detection as a regression task. Then, three parallel subnetworks are applied to extract AS-OCT representations for the global image and at clinically relevant local regions. Finally, the extracted deep features of these subnetworks are concatenated into one fully connected layer to predict the angle-closure detection result. In the experiments, our system is shown to surpass previous detection methods and other deep learning systems on two clinical AS-OCT datasets.

Assessment of Circumferential Angle Closure with Swept-Source Optical Coherence Tomography: a Community Based Study

To evaluate the diagnostic performance of swept-source optical coherence tomography (SS-OCT, CASIA SS-1000; Tomey Corporation, Nagoya, Japan) for angle closure detection, in comparison with gonioscopy, in a community setting. Reliability analysis. A total of 2027 phakic subjects aged ≥50 years, with no previous history of glaucoma, laser (including peripheral iridotomy), intraocular surgery, or ocular trauma, were consecutively recruited from a community polyclinic in Singapore. Gonioscopy was performed by a single trained ophthalmologist. SS-OCT angle scans, which obtain radial scans for the entire circumference of the angle, were analyzed by a single examiner, masked to the subject's clinical details. On SS-OCT images, angle closure was defined as contact between the iris and any part of the angle wall anterior to the scleral spur. Different cutoff values of the degree of circumferential angle closure (≥35%, ≥50%, and ≥75%) were taken for analysis to assess SS-OCT performance in detecting angle closure. A total of 1857 subjects (91.6%) were included in the final analysis after excluding poor-quality SS-OCT scans. Almost 90% of the subjects were Chinese, with a mean age of 61.8 ± 6.7 years, and more than half were women (63.5%). The overall AUC of SS-OCT manual grading against gonioscopy was 0.84 (95% confidence interval, 0.81-0.88). The prevalence of angle closure on SS-OCT was 26.1% for the ≥35% definition, with an area under the curve of 0.80 (0.77-0.84), sensitivity of 82.5% (75.3%-88.4%), and specificity of 78.5% (76.5%-80.4%). The first-order agreement coefficient statistics for the 2-quadrant gonioscopic definition of angle-closure with corresponding ≥35%, ≥50%, and ≥75% angle closure definitions for SS-OCT were good at 0.89 (0.83-0.93), 0.88 (0.842-0.93), and 0.88 (0.831-0.99), respectively. In this large community-based study, SS-OCT exhibited moderate performance for angle closure detection compared to gonioscopy as the reference standard.

Low Sensitivity of the Van Herick Method for Detecting Gonioscopic Angle Closure Independent of Observer Expertise

To evaluate the diagnostic performance characteristics of the Van Herick assessment (VHA) for identifying angle closure compared to gold-standard gonioscopy, as conducted by trained observers of varying expertise. Reliability analysis. Patients (n= 131) from a glaucoma referral clinic aged ≥50 years without prior ocular surgery or iridotomy underwent unilateral VHA by 1 of 11 trained ophthalmic technicians, followed by VHA and indirect gonioscopy by 1 of 15 ophthalmology residents and 1 of 4 glaucoma specialist attending physicians. Observers were masked to others' gradings. Cohen's kappa (κ) assessed test reproducibility. VHA sensitivity and specificity for identifying gonioscopic angle closure were calculated. Mean patient age was 62.0 ± 8.7 years, 56% of patients were male, and 84% were African American. Angles were gonioscopically closed in 14.5% of eyes. Moderate agreement was observed comparing technician or resident VHA to attending VHA (κ= 0.48 and κ= 0.56, respectively). Resident and attending gonioscopy demonstrated excellent agreement (κ= 0.94). Sensitivities of technician, resident, and attending VHA for detecting angle closure were 57.9% (95% confidence interval: 34.0%-78.9%), 78.9% (53.9%-93.0%), and 68.4% (43.5%-86.4%), respectively. Specificities were 88.5% (80.3%-93.6%), 88.2% (80.3%-93.3%), and 87.5% (79.6%-92.8%), respectively. VHA, even when performed by experienced ophthalmologists, misses a substantial proportion of angle closure while incorrectly identifying roughly 1 in 8 open-angle eyes as closed. These results suggest that clinical assessment of anterior chamber angle configuration is best accomplished with gonioscopy.

Biometric Parameters in Different Stages of Primary Angle Closure Using Low-Coherence Interferometry

To compare ocular biometric parameters using low-coherence interferometry among siblings affected with different degrees of primary angle closure (PAC). In this cross-sectional comparative study, a total of 170 eyes of 86 siblings from 47 families underwent low-coherence interferometry (LenStar 900; Haag-Streit, Koeniz, Switzerland) to determine central corneal thickness, anterior chamber depth (ACD), aqueous depth (AD), lens thickness (LT), vitreous depth, and axial length (AL). Regression coefficients were applied to show the trend of the measured variables in different stages of angle closure. To evaluate the discriminative power of the parameters, receiver operating characteristic curves were used. Best cutoff points were selected based on the Youden index. Sensitivity, specificity, positive and negative predicative values, positive and negative likelihood ratios, and diagnostic accuracy were determined for each variable. All biometric parameters changed significantly from normal eyes to PAC suspects, PAC, and PAC glaucoma; there was a significant stepwise decrease in central corneal thickness, ACD, AD, vitreous depth, and AL, and an increase in LT and LT/AL. Anterior chamber depth and AD had the best diagnostic power for detecting angle closure; best levels of sensitivity and specificity were obtained with cutoff values of 3.11 mm for ACD and 2.57 mm for AD. Biometric parameters measured by low-coherence interferometry demonstrated a significant and stepwise change among eyes affected with various degrees of angle closure. Although the current classification scheme for angle closure is based on anatomical features, it has excellent correlation with biometric parameters.

Gonioscopy and ultrasound biomicroscopy in the detection of angle closure in patients with shallow anterior chamber.

To assess the agreement between gonioscopy and ultrasound biomicroscopy (UBM) in detecting angle closure in Chinese patients with shallow anterior chamber. An observational comparative study of the two different examination methods was conducted. Patients with normal intraocular pressure and temporal peripheral anterior chamber depth less than a quarter of corneal thickness based on slit lamp examination were included in this study from December 2007 to May 2009 in the outpatient clinic of First Hospital of Tsinghua University. Gonioscopy was performed with a Goldman goniolens in dark room first and followed by full beam light and indentation. If the filtering trabecular meshwork was invisible or any peripheral anterior synechia was found, that quadrant of the angle was considered closed. UBM was first undertaken in a darkened room then repeated with normal room lighting. If iridotrabecular apposition was showed, that quadrant of the angle was considered closed. The status of angle closure of each quadrant with different methods was recorded. 85 eyes of 46 patients were included in this study. The agreement between gonioscopy and UBM was poor (Κ<0.4) with Kappa analysis in both dark and light conditions in each quadrant. The accordance of agreement between gonioscopy and UBM was hardly affected by age or sex, while in dark condition, eyes with deeper anterior chamber (P=0.005) or plateau iris configuration tended to produce different results (P=0.075) in the 2 methods. Gonioscopy and UBM are both indispensable methods for detecting angle closure, neither can completely replace the other.

Development of a Score and Probability Estimate for Detecting Angle Closure Based on Anterior Segment Optical Coherence Tomography

To develop a score along with an estimated probability of disease for detecting angle closure based on anterior segment optical coherence tomography (AS OCT) imaging. Cross-sectional study. A total of 2047 subjects 50 years of age and older were recruited from a community polyclinic in Singapore. All subjects underwent standardized ocular examination including gonioscopy and imaging by AS OCT (Carl Zeiss Meditec). Customized software (Zhongshan Angle Assessment Program) was used to measure AS OCT parameters. Complete data were available for 1368 subjects. Data from the right eyes were used for analysis. A stepwise logistic regression model with Akaike information criterion was used to generate a score that then was converted to an estimated probability of the presence of gonioscopic angle closure, defined as the inability to visualize the posterior trabecular meshwork for at least 180 degrees on nonindentation gonioscopy. Of the 1368 subjects, 295 (21.6%) had gonioscopic angle closure. The angle closure score was calculated from the shifted linear combination of the AS OCT parameters. The score can be converted to an estimated probability of having angle closure using the relationship: estimated probability = e(score)/(1 + e(score)), where e is the natural exponential. The score performed well in a second independent sample of 178 angle-closure subjects and 301 normal controls, with an area under the receiver operating characteristic curve of 0.94. A score derived from a single AS OCT image, coupled with an estimated probability, provides an objective platform for detection of angle closure.