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

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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

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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:BACKGROUND:The validity of using the Remote Food Photography Method (RFPM) for measuring food intake of minority preschool children's intake is not well documented. OBJECTIVE:Our aim was to determine the validity of intake estimations made by human raters using the RFPM compared with those obtained by weighing all foods and beverages consumed by 3- to 5-year-old children (weighed method). DESIGN:We conducted a cross-sectional observational study. PARTICIPANTS/SETTINGS:A convenience sample of 54 3- to 5-year-old Hispanic and African-American children were observed during a 12-hour period at Baylor Metabolic Research Unit between June 2013 and January 2014. MAIN OUTCOME MEASURES:All foods/beverages consumed by the children were provided by Baylor research coordinators who took and wirelessly transmitted before-and-after pictures of the trays to trained human raters at the Pennington Biomedical Research Center who estimated grams consumed. Energy and macronutrients were calculated using the Food and Nutrient Database for Dietary Studies or food facts data provided by manufacturers. STATISTICAL ANALYSES:Paired t test, mean differences, and Bland-Altman limits of agreement were performed. RESULTS:Compared to the weighed method, the rater method significantly overestimated total intake by 34±71 g (P<0.0001), with a mean percent error of 2.9% (root mean square error=7.1%), and total energy intake by 75±102 kcal (P<0.0001), with a mean percent error of 7.5% (root mean square error=12.3%). The standard error for the macronutrient intakes ranged from 11.0% to 20.2%. The Bland-Altman approach demonstrated a positive slope for the rater method relative to the weighed method for total intake in grams (P=0.006), carbohydrate (P=0.01), and protein (P=0.01) (ie, magnitude of the bias increased with increasing intakes). CONCLUSIONS:The rater method overestimated total intake in grams and energy in kilocalories in minority preschool children in a well-controlled condition and needs to be further tested in a free-living environment.

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

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