Dataset Information

A Novel Method of Quantitative Anterior Chamber Depth Estimation Using Temporal Perpendicular Digital Photography.

ABSTRACT:

Purpose

We hypothesize that: (1) Anterior chamber depth (ACD) is correlated with the relative anteroposterior position of the pupillary image, as viewed from the temporal side. (2) Such a correlation may be used as a simple quantitative tool for estimation of ACD.

Methods

Two hundred sixty-six phakic eyes had lateral digital photographs taken from the temporal side, perpendicular to the visual axis, and underwent optical biometry (Nidek AL scanner). The relative anteroposterior position of the pupillary image was expressed using the ratio between: (1) lateral photographic temporal limbus to pupil distance ("E") and (2) lateral photographic temporal limbus to cornea distance ("Z"). In the first chronological half of patients (Correlation Series), E:Z ratio (EZR) was correlated with optical biometric ACD. The correlation equation was then used to predict ACD in the second half of patients (Prediction Series) and compared to their biometric ACD for agreement analysis.

Results

A strong linear correlation was found between EZR and ACD, R = -0.91, R² = 0.81. Bland-Altman analysis showed good agreement between predicted ACD using this method and the optical biometric ACD. The mean error was -0.013 mm (range -0.377 to 0.336 mm), standard deviation 0.166 mm. The 95% limits of agreement were ±0.33 mm.

Conclusions

Lateral digital photography and EZR calculation is a novel method to quantitatively estimate ACD, requiring minimal equipment and training.

Translational relevance

EZ ratio may be employed in screening for angle closure glaucoma. It may also be helpful in outpatient medical clinic settings, where doctors need to judge the safety of topical or systemic pupil-dilating medications versus their risk of triggering acute angle closure glaucoma. Similarly, non ophthalmologists may use it to estimate the likelihood of acute angle closure glaucoma in emergency presentations.

SUBMITTER: Zamir E

PROVIDER: S-EPMC4981489 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Novel Method of Quantitative Anterior Chamber Depth Estimation Using Temporal Perpendicular Digital Photography.

Zamir Ehud E Kong George Y X GY Kowalski Tanya T Coote Michael M Ang Ghee Soon GS

Translational vision science & technology 20160729 4

<h4>Purpose</h4>We hypothesize that: (1) Anterior chamber depth (ACD) is correlated with the relative anteroposterior position of the pupillary image, as viewed from the temporal side. (2) Such a correlation may be used as a simple quantitative tool for estimation of ACD.<h4>Methods</h4>Two hundred sixty-six phakic eyes had lateral digital photographs taken from the temporal side, perpendicular to the visual axis, and underwent optical biometry (Nidek AL scanner). The relative anteroposterior po ...[more]

PMID: 27540496

Similar Datasets

Project description:PurposeTo develop a deep learning (DL) algorithm for predicting anterior chamber depth (ACD) from smartphone-acquired anterior segment photographs.MethodsFor algorithm development, we included 4,157 eyes from 2,084 Chinese primary school students (aged 11-15 years) from Mojiang Myopia Progression Study (MMPS). All participants had with ACD measurement measured with Lenstar (LS 900) and anterior segment photographs acquired from a smartphone (iPhone Xs), which was mounted on slit lamp and under diffuses lighting. The anterior segment photographs were randomly selected by person into training (80%, no. of eyes = 3,326) and testing (20%, no. of eyes = 831) dataset. We excluded participants with intraocular surgery history or pronounced corneal haze. A convolutional neural network was developed to predict ACD based on these anterior segment photographs. To determine the accuracy of our algorithm, we measured the mean absolute error (MAE) and coefficient of determination (R 2) were evaluated. Bland Altman plot was used to illustrate the agreement between DL-predicted and measured ACD values.ResultsIn the test set of 831 eyes, the mean measured ACD was 3.06 ± 0.25 mm, and the mean DL-predicted ACD was 3.10 ± 0.20 mm. The MAE was 0.16 ± 0.13 mm, and R 2 was 0.40 between the predicted and measured ACD. The overall mean difference was -0.04 ± 0.20 mm, with 95% limits of agreement ranging between -0.43 and 0.34 mm. The generated saliency maps showed that the algorithm mainly utilized central corneal region (i.e., the site where ACD is clinically measured typically) in making its prediction, providing further plausibility to the algorithm's prediction.ConclusionsWe developed a DL algorithm to estimate ACD based on smartphone-acquired anterior segment photographs. Upon further validation, our algorithm may be further refined for use as a ACD screening tool in rural localities where means of assessing ocular biometry is not readily available. This is particularly important in China where the risk of primary angle closure disease is high and often undetected.

Project description:PurposeTo assess the relationship between anterior chamber depth (ACD) and lens thickness (LT), as well as its three main components (anterior and posterior cortex and nucleus thickness), in cataractous and non-cataractous eyes, depending on the axial length (AxL).MethodsAnterior and posterior cortex and nucleus thickness of the crystalline lens, ACD, and AxL were measured using optical low-coherence reflectometry in cataractous and non-cataractous eyes. They were also classified into hyperopia, emmetropia, myopia, and high myopia, depending on AxL; thus, eight subgroups were created. A minimum sample size of 44 eyes (of 44 patients) for each group was recruited. Linear models were fitted for the whole sample and each AxL subgroup to assess if there were differences in the relationships between the crystalline lens variables and ACD, including age as a covariate.ResultsThree hundred seventy cataract patients (237 females, 133 males) and 250 non-cataract controls (180 females, 70 males), aged 70.5 ± 9.4 and 41.9 ± 15.5 years, respectively, were recruited. The mean AxL, ACD, and LT for the cataractous and non-cataractous eyes were 23.90 ± 2.05, 24.11 ± 2.11, 2.64 ± 0.45, and 2.91 ± 0.49, 4.51 ± 0.38, 3.93 ± 0.44 mm, respectively. The inverse relationship of LT, anterior and posterior cortex, and nucleus thickness with ACD was not significantly (p ≥ 0.26) different between cataractous and non-cataractous eyes. Further subclassification of the sample depending on AxL showed that the inverse relationship between the posterior cortex and ACD was no longer significant (p > 0.05) for any non-cataractous AxL group. LT, anterior and posterior cortex, and nucleus thickness was not significantly (p ≥ 0.43) different between cataractous and non-cataractous eyes for the whole sample, and all AxL groups after adjusting for age.ConclusionsThe presence of cataracts does not modify the inverse relationship of the LT, anterior and posterior cortex, and nucleus with ACD. And this relationship does not seem to depend importantly on AxL. Besides, the possible differences in LT, anterior and posterior cortex, and nucleus between cataractous and non-cataractous eyes may not be caused by lens opacification, but possibly by the progressive lens growth due to aging.

Dataset Information

A Novel Method of Quantitative Anterior Chamber Depth Estimation Using Temporal Perpendicular Digital Photography.

Purpose

Methods

Results

Conclusions

Translational relevance

Publications

A Novel Method of Quantitative Anterior Chamber Depth Estimation Using Temporal Perpendicular Digital Photography.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets