**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, *R*^{2} = 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.

^{1}A straight line, roughly tangential to the temporal limbal arc was traced freehand. Perpendicular to it, a line passing through the temporal limbus and the estimated center of the pupillary image was drawn and extended anteriorly to intersect with the cornea. A corneal mark was placed at the anterior corneal intersection point (Fig. 2).

- To test our first hypothesis, the chronological first half of eyes were labelled “Correlation Series.” Pearson's coefficient (
*R*) was calculated for the correlation between EZR and the biometric ACD in this series, using Microsoft Excel. The line of best fit for the scatter diagram of this correlation series was generated and its linear equation was recorded. - To test our second hypothesis, the correlation equation derived from the Correlation Series was used to predict ACD in the remaining half (the Prediction Series). This prediction was then compared to the biometric ACD of those eyes. Scatter plots of the Prediction Series were generated, showing predicted (x axis) versus biometric ACD (y axis), and Bland-Altman agreement analysis (MedCalc, MedCalc Software, Ostend, Belgium) was used to show the agreement between predicted ACD and biometric ACD measurement.
- Intraclass correlation coefficient (ICC) was used for the assessment of intra- and interobserver reliability in measurement of EZR. ICCs were calculated using SPSS (version 16.0, SPSS, Inc., Chicago, IL) with Two-Way Mixed model set to examine absolute agreement.

*R*was −0.90,

*R*

^{2}was 0.81 and the linear equation of the line of best fit was: ACD = −3.273EZR + 4.18 (Fig. 3).

^{2}There, too, the basis for the estimate is an approximately constant corneal thickness that is used as a comparator.

*Z*may be shown to be dependent on

*R*and WTW, as shown in Figure 6, with the equation . Using our biometrically obtained values for

*R*and WTW for each eye in our study, this calculation yielded Z values with a mean of 2.8 mm and a narrow normal distribution (Fig. 7). We therefore chose EZR as a candidate measure for correlation with ACD. As shown in Appendix 1, the theoretical relationship between EZR and ACD is approximately linear. Both the theoretical and empirically derived correlations support hypothesis 1. We also showed that the empirically derived correlation can be used as an instrument to estimate the ACD with clinically acceptable accuracy, supporting hypothesis 2. The error of this estimate, compared to gold standard ACD measurement, had a 95% limit of agreement of ± 0.33 mm, and the error's coefficient of variation was less than 7% of the average ACD in our series. This magnitude of agreement is comparable with the limits of agreement between established automated methods for ACD measurement, such as partial coherence laser interferometry (IOL Master), scanning peripheral anterior chamber analyser and anterior segment OCT: In a study by Lavanya et al.,

^{3}these methods demonstrated 95% limits of agreement of 0.4 to 0.5 mm in ACD measurements when analyzed for agreement between them.

^{4,5}which in turn also changes the value of Z. We assumed both of these parameters to be constant in reaching our theoretical equations. Our observational data show that despite the above approximations and sources of error, our predicted ACD values were of clinically acceptable accuracy in a large series of eyes.

^{6–8}A simple tool for estimating ACD may assist in identifying patients at risk or excluding the risk of angle closure glaucoma, either as a screening tool or on an individual patient basis. Assessment of the risk of inducing acute angle closure is also relevant for non ophthalmologists prescribing anticholinergics, antiemetics, antidepressants, and various anaesthetic agents that may trigger acute angle closure in susceptible patients. ACD is sensitive but not specific enough for screening for angle closure glaucoma on its own, but its high sensitivity and high negative predictive value mean that if an ACD is deeper than a threshold level, the risk of ACG is low.

^{7–11}This makes it useful when angle closure glaucoma needs to be ruled out, such as in the hands of general physicians treating patients with an acutely red eye.

^{12}However, it is subjective and qualitative. In contrast, our method is objective, photography-based (therefore also allowing re-examination of the data or remote analysis) and quantitative.

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