ORIGINAL ARTICLE |
https://doi.org/10.5005/jp-journals-10078-1446 |
The Efficacy of the Temporal View in Detection of Shallow Anterior Chamber
1,3Department of Ophthalmology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
2Department of Cataract and Medical Retina, ASG Eye Hospital, Bhopal, Madhya Pradesh, India
Corresponding Author: Yogish S Kamath, Department of Ophthalmology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India, e-mail: yogish.kamath@manipal.edu
Received: 29 June 2024; Accepted: 28 August 2024; Published on: 29 October 2024
ABSTRACT
Aim and background: The study aims to determine the accuracy of utilizing a temporal view in the detection of a shallow anterior chamber (AC), in comparison to the conventional anterior view, by evaluation of photographs of the anterior segment of the eye.
Materials and methods: Two hundred fifty students who had completed basic undergraduate ophthalmology training as part of their medical education graded the AC depth in anterior segment photographs as “shallow” or “not shallow.” Each eye was photographed from the anterior and temporal views. A total of 40 photographs of 20 eyes were provided.
Results: The ability to detect a shallow AC by temporal view had a sensitivity of 73.3%, compared to 63.2% in the anterior view. The specificity of the temporal view was better at 66.2% compared to the anterior view, which was 65.3%. The overall accuracy of the temporal view in detecting a shallow AC was higher than the anterior view (68.3 vs 64.7%, respectively). Combining both techniques increased the detection of a shallow AC to 88.3%.
Conclusion: In our study, the temporal view was more accurate in detecting a shallow AC compared to the anterior view. Integrating the temporal view of AC depth assessment with the traditional anterior view further improves the chances of detecting a shallow AC.
Keywords: Angle-closure glaucoma, Mass screening, Photography, Training technique
How to cite this article: Kuzhuppilly NI, Chandna R, Kamath YS. The Efficacy of the Temporal View in Detection of Shallow Anterior Chamber. J Curr Glaucoma Pract 2024;18(3):98–102.
Source of support: Nil
Conflict of interest: None
INTRODUCTION
Glaucoma is an important cause of irreversible blindness globally. In Asian countries, the prevalence of primary angle closure glaucoma is higher than in Western countries.1 The estimated prevalence of primary angle closure glaucoma is 4.32% in people older than 40 years of age in South India. Asians and Indians are at higher risk of angle closure glaucoma compared to Caucasian populations.2 Angle closure glaucoma is a silent disease in about two-thirds of cases and is associated with a shallow anterior chamber (AC).
Anterior chamber depth is the distance between the posterior vertex of the cornea and the anterior apex of the lens. The ability to detect or screen for a shallow AC is a skill that every medical graduate and personnel working in ophthalmology should possess. A shallow AC is associated with angle closure glaucoma and other ocular disorders such as globe rupture, hypermetropia, intumescent cataract, and plateau iris. The early detection of these conditions significantly alters the course of the disease.
India trains about 50,000 medical students every year and has one of the largest health forces globally.3 An estimated 9,43,529 medical practitioners of modern medicine are registered in India, including approximately 17,000 ophthalmologists, most of whom are in urban areas, which makes the availability of eye care services highly skewed.3,4 Proper training of medical students in ophthalmology is therefore essential in ensuring adequate competency for the early referral of potentially blinding conditions.5
Standard training of Bachelor of Medicine and Bachelor of Surgery (MBBS) students in the detection of a shallow AC is based on an anterior view of the eye, with a flashlight shown into the eye from an oblique angle. They are taught to observe the shadow seen on the nasal iris, where a wider shadow indicates the presence of a shallow AC.6 However, no standardization of this test exists, and the efficacy of this method is variable. Detecting a shallow AC is also possible by looking at the eye from the side, that is, the temporal aspect, and has shown good accuracy.7,8
This project aimed to determine whether medical students and graduates with basic training in ophthalmology are able to detect a shallow AC more accurately when presented with standard photographs of the eye in the anterior view versus the temporal view.
MATERIALS AND METHODS
The study was conducted prospectively after approval from the Institutional Ethics Committee, and consent was obtained from all participants prior to participation.
Students who had completed basic undergraduate ophthalmology training in their MBBS course were eligible to participate in the study.
Participants and their analyses were excluded if there was incomplete evaluation of photographs. If the same student completed the analysis multiple times, the first attempt was retained and the rest discarded. MBBS students in their first 3 years of medical education or those who had not cleared their undergraduate ophthalmology examinations were excluded from participation. Ophthalmologists and postgraduates in ophthalmology beyond the first year were also excluded.
Forty photographs of 20 eyes were chosen for the study from a preexisting database. Each eye was photographed from the anterior and temporal views. Six of the 20 eyes had a shallow AC, and the remaining had normal AC depth. The AC depth measurement for each of the eyes was known, as it had been recorded using the IOL Master 500 earlier.
These photographs were uploaded onto the web software Google Forms, and students at our college and hospital were provided with the link via email or messaging platforms from June 2021 to June 2022. The consent form was included on the first page of the form, and only after giving consent could participants proceed to the page with the photographs. Based on the knowledge gained from MBBS ophthalmology training, the students were required to grade the photographs as “shallow” or “not shallow.” No additional training was provided to the students prior to this study. The photographs were presented in a random order, as the “shuffle” setting was enabled. This ensured that the anterior and temporal views of the same eye were not presented together, to avoid one view influencing the decision on the other view. No clinical information was provided with the photographs. The responses were downloaded in Microsoft Excel format.
The outcome measures included the sensitivity, specificity, and accuracy of the anterior view and temporal view tests in detecting a shallow AC from photographs of the eyes.
Statistical Methods
The sample size was calculated at a 95% confidence interval, with an anticipated sensitivity of 75%, absolute precision of 0.1, and a prevalence of 30%, resulting in 240 students. To allow for errors or incomplete submissions, the final sample size was set at 250.9 IBM Statistical Package for the Social Sciences (SPSS) Statistics for Windows, Version 23.0 (IBM SPSS Statistics Inc., Chicago, Illinois, United States), and Microsoft Excel (version 2016) were used for analysis. Sensitivity, specificity, and accuracy of detecting AC depth by anterior and temporal views were calculated using the crosstabs function. An independent samples t-test was used to determine the significance of the difference in AC depths between eyes with shallow and normal AC depths. A p-value < 0.05 was considered significant.
RESULTS
Two hundred fifty students took part in evaluating photographs of 20 eyes. A total of 40 photographs were examined by each student, as each eye was evaluated in both the anterior and temporal views.
Out of the 20 eyes chosen for evaluation, 14 had a normal AC depth with a mean of 3.5 ± 0.2 mm. Six eyes had a shallow AC depth with a mean of 2.3 ± 0.1 mm. The difference between them was significant (p < 0.0001).
All the students who participated in the study had completed their undergraduate ophthalmology training and cleared their ophthalmology examination. Final year MBBS students, interns, nonophthalmology postgraduates, and first-year ophthalmology postgraduate students took part, with the majority being in the internship phase of medical education. First-year ophthalmology residents identified AC depth better than other groups of students (Fig. 1).
Fig. 1: The proportion of correct answers obtained from different groups
In evaluating the photographs of the eyes, the temporal view assessment had better sensitivity in detecting shallow ACs at 73.3%, compared to the anterior view at 63.2%. The specificity of the temporal view assessment was also better at 66.2% compared to the anterior view, which was 65.3%. The overall accuracy of the temporal view in detecting shallow AC was higher, at 68.3 vs 64.7%. When both techniques were combined, shallow AC was detected in 88.3% of total assessments. The negative predictive value, which is the probability that the disease is not present when the test result is negative, was higher than the positive predictive value for both the anterior and temporal views. The positive and negative predictive values were higher for the temporal view compared to the anterior view test, at 48.2 and 85.3% vs 43.9 and 80.6%, respectively (Table 1).
| True shallow | True not shallow | Total | Sensitivity | Specificity | Positive predictive value | Negative predictive value | Accuracy | ||
|---|---|---|---|---|---|---|---|---|---|
| Anterior view test | Shallow | 948 | 1,214 | 2,162 | 63.2% (CI 60.7–65.7%) | 65.3% (CI 63.7–66.9%) | 43.9% (CI 42.4–45.3%) | 80.6% (CI 79.4–81.6%) | 64.7% (CI 63.3–66%) |
| Not shallow | 552 | 2,286 | 2,838 | ||||||
| Total | 1,500 | 3,500 | 5,000 | ||||||
| Temporal view test | Shallow | 1,100 | 1,183 | 2,283 | 73.3% (CI 71–75.6%) | 66.2% (CI 64.6–67.8%) | 48.2% (CI 46.8–49.6%) | 85.3% (CI 84.2–86.3%) | 68.3% (CI 67–69.6%) |
| Not shallow | 400 | 2,317 | 2,717 | ||||||
| Total | 1,500 | 3,500 | 5,000 |
CI, confidence interval
The percentage of correct responses for each of the photographs is depicted in Figure 2. It can be seen that, for each eye with a shallow AC, the temporal view assessment performed better than the anterior view. The most confusing photograph for the assessors was eye number 10, which is shown in Figure 3.
Fig. 2: The percentage of correct responses per photograph presented
Fig. 3: The photograph with highest variable and/or wrong responses
There was no significant correlation between the measured AC depth of each eye and the percentage of correct responses obtained. For the anterior view, the Pearson correlation coefficient was 0.203 (p = 0.391), and for the temporal view, it was –0.233 (p = 0.323) (Table 2).
| AC depth (mm) | Eye (serial number) | Percentage of correct responses (%) | |
|---|---|---|---|
| Anterior view | Temporal view | ||
| 4.1 | 6 | 69.6 | 82.8 |
| 3.6 | 3 | 71.2 | 62 |
| 3.5 | 12 | 63.2 | 60.8 |
| 3.46 | 4 | 65.6 | 72 |
| 3.44 | 8 | 61.2 | 70.4 |
| 3.44 | 10 | 60 | 48.8 |
| 3.44 | 14 | 58.8 | 61.2 |
| 3.43 | 7 | 72 | 70.4 |
| 3.4 | 5 | 66.8 | 74.4 |
| 3.4 | 13 | 64.8 | 56.8 |
| 3.39 | 11 | 56.8 | 72 |
| 3.31 | 2 | 71.6 | 66 |
| 3.31 | 9 | 72.8 | 78 |
| 3.15 | 1 | 60 | 51.2 |
| 2.53 | 19 | 64.8 | 64.4 |
| 2.44 | 18 | 54 | 69.2 |
| 2.38 | 17 | 58.8 | 78 |
| 2.32 | 15 | 74 | 75.2 |
| 2.3 | 20 | 61.2 | 74.8 |
| 2.26 | 16 | 66.4 | 78.4 |
DISCUSSION
In this study, we aimed to determine if students with basic training in ophthalmology could detect a shallow AC better when viewing the eye from the anterior view or from the temporal side. We established that both views work moderately well, but the temporal view performed better.
Assessment of AC depth is important for several reasons, the most important being screening for the risk of angle closure glaucoma. The presentation of glaucoma can vary from an asymptomatic eye to a red, painful eye. This asymptomatic eye, which has the potential to cause permanent visual field changes, may go unnoticed by the patient for several years, making screening for such individuals an essential intervention. Currently, screening for glaucoma can only be performed by an experienced ophthalmologist using instruments such as the slit lamp biomicroscope, tonometer, and a 90D lens or an ophthalmoscope.
Torchlight assessment of AC depth can be used as a screening tool for shallow AC.10 Shallow AC is an indicator of a narrow angle of the AC. Slit lamp evaluation with the Van Herrick technique is better at detecting shallow AC, but it is not infallible.11-13 The conclusive detection of a narrow or occludable angle is performed through gonioscopy. Investigations such as anterior segment optical coherence tomography (OCT) and ultrasound biomicroscopy are available, but for community screening, AC depth can easily be assessed for shallow AC with a torchlight.
A common situation where screening for shallow AC is needed is at rural cataract screening camps, where dilated evaluation is carried out before selecting patients for surgery. Another scenario is in teleophthalmologic glaucoma screening, which might involve taking a dilated fundus photo and transmitting the data to a remote ophthalmologist. This could potentially cause an iatrogenic angle closure crisis while aiding glaucoma diagnosis. In teleophthalmology, AC depth would help classify cases as open-angle or angle-closure glaucoma.14 AC depth screening is also needed in emergency departments when patients present with headache, nausea, vomiting, and eye pain.15 An angle closure attack may be missed by the emergency physician in such cases. In these scenarios, screening for AC depth is a skill that would be useful not only for ophthalmologists but also for physicians.
Students who had basic ophthalmology training were chosen as assessors, with the majority being interns. No ophthalmologists were included. The goal was to select a group of assessors that reflects the real-world scenario, where screening for shallow ACs is typically conducted by general physicians, health workers, ophthalmic assistants, and others who have only basic training in eye evaluation. Since not all examiners will have the same level of skill even after training, a sufficiently large sample size of assessors was chosen.
The photos were presented in a jumbled manner so that the anterior and temporal views of the same eye were not presented consecutively. This ensured that the assessing students would not be influenced by the other view of the same eye when grading a photograph. We chose a set of photographs such that 30% of the eyes had a shallow AC, which roughly reflects the expected prevalence of shallow AC in Indian eyes. AC depth varies across populations, and Indians have a higher proportion of angle closure glaucoma.1,16,17
With this study, we have shown that students who have traditionally received training to detect shallow ACs using an anterior view performed better at detecting shallow AC with a temporal view, for which they had not been trained. The sensitivity and specificity were better with the temporal view for detecting shallow AC. In a real-world scenario, we would want shallow AC to be detected at least 70% of the time. This threshold is achieved by the temporal view but not by the anterior view. Combining the two techniques increased sensitivity to 88.3%. Furthermore, the negative predictive value of both the anterior and temporal view tests is higher than 80%, with the temporal view performing better. This is important because when an eye is classified as having normal AC depth, it should not be shallow, to avoid potentially missing a case of angle closure glaucoma or inducing an angle closure crisis upon pupillary dilatation.
The high combined sensitivity opens up the possibility of training students and other personnel in both anterior and temporal view techniques to detect shallow AC, thereby minimizing the chances of missing angle closure glaucoma. Previous studies have described a technique where shallow AC detection is possible using the temporal view, taking the pupil plane as a reference.7,8 In this technique, if the pupil plane is within the anterior one-third or closer to the cornea in the distance between the limbus and corneal apex on the temporal view, the chances of AC being shallow are higher. Integrating this information with a temporal view photograph and applying deep learning techniques could potentially increase sensitivity in detecting shallow AC.18,19
It is observed that the most confusing eye for assessment, eye number 10, had a relatively darker iris (Fig. 3). A darker iris might interfere with assessors’ ability to correctly identify the shadows on the iris in the anterior view and the position of the pupil in the temporal view. Adequate illumination is required in such situations to minimize errors. Another limitation of our study is that student assessors may not fully represent clinical scenarios, where ophthalmic technicians or general physicians are aware that their choices impact actual patients and would therefore be more motivated to make accurate assessments. In real life, it is possible to achieve better results than those found in this study.
In the future, we plan to continue research by training students in both anterior and temporal views to assess AC depth. Following this training, we will reassess sensitivity and specificity in detecting shallow AC using both views. Ophthalmology training for residents has been streamlined and refined over the years.20,21 There are many innovations in this area.22-24 Similar innovations and competency-based ophthalmology training for undergraduate medical students and paramedical staff need to be pursued to ensure that ophthalmology services are available at the grassroots level.25
In conclusion, we found that assessment of AC depth using a novel temporal view performed better compared to the anterior view when the test was conducted by students with basic ophthalmology training. Integrating the temporal view of AC depth assessment with the traditional anterior view further improves the chances of detecting shallow AC.
However, further studies may be needed to assess the application of this technique by healthcare professionals in a real-world community setting, where additional factors such as the prevalence of angle closure suspects and the skill of performing the flashlight test would be taken into consideration.
ORCID
Neetha IR Kuzhuppilly https://orcid.org/0000-0002-7297-829X
Ravi Chandna https://orcid.org/0000-0001-7502-6510
Yogish S Kamath https://orcid.org/0000-0002-9829-2595
REFERENCES
1. Jacob A, Thomas R, Koshi SP, et al. Prevalence of primary glaucoma in an urban south Indian population. Indian J Ophthalmol 1998;46(2):81–86. PMID: 9847479.
2. Tham YC, Li X, Wong TY, et al. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology 2014;121(11):2081–2090. DOI: 10.1016/j.ophtha.2014.05.013
3. Potnuru B. Aggregate availability of doctors in India: 2014-2030. Indian J Public Health 2017;61(3):182–187. DOI: 10.4103/ijph.IJPH_143_16
4. Resnikoff S, Lansingh VC, Washburn L, et al. Estimated number of ophthalmologists worldwide (International Council of Ophthalmology update): will we meet the needs? Br J Ophthalmol 2020;104(4):588–592. DOI: 10.1136/bjophthalmol-2019-314336
5. Divya K, Suvetha K, Sen A, et al. Needs assessment of ophthalmology education for undergraduate medical students - a study from a medical college in South India. Educ Health (Abingdon) 2017;30(3):223–227. DOI: 10.4103/efh.EfH_52_16
6. Congdon NG, Quigley HA, Hung PT, et al. Screening techniques for angle-closure glaucoma in rural Taiwan. Acta Ophthalmol Scand 1996;74(2):113–119. DOI: 10.1111/j.1600-0420.1996.tb00053.x
7. Zamir E, Kong GY, Kowalski T, et al. A novel method of quantitative anterior chamber depth estimation using temporal perpendicular digital photography. Transl Vis Sci Technol 2016;5(4):10. DOI: 10.1167/tvst.5.4.10
8. Chandna R, Kuzhuppilly NIR, Kamath YS. Smartphone-acquired image photogrammetry for detection of shallow anterior chamber. Clin Ophthalmol 2021;15:1875–1885. DOI: 10.2147/OPTH.S306835
9. Malhotra RK, Indrayan A. A simple nomogram for sample size for estimating sensitivity and specificity of medical tests. Indian J Ophthalmol 2010;58(6):519–522. DOI: 10.4103/0301-4738.71699
10. Sparks BI 3rd. Tangential penlight angle estimation. J Am Optom Assoc 1997;68(7):432–434. PMID: 9248250.
11. Thomas R, George T, Braganza A, et al. The flashlight test and van Herick’s test are poor predictors for occludable angles. Aust N Z J Ophthalmol 1996;24(3):251–256. DOI: 10.1111/j.1442-9071.1996.tb01588.x
12. Gispets J, Cardona G, Verdú M, et al. Sources of variability of the van Herick technique for anterior angle estimation. Clin Exp Optom 2014;97(2):147–151. DOI: 10.1111/cxo.12094
13. Choudhari NS, Chandran P, Rao HL, et al. LVPEI glaucoma epidemiology and molecular genetic study: teleophthalmology screening for angle-closure disease in an underserved region. Eye (Lond) 2020;34(8):1399–1405. DOI: 10.1038/s41433-019-0666-x
14. Luo Q, Xue W, Yuan Y, et al. Peripheral anterior chamber depth and screening techniques for primary angle closure disease in community elderly Chinese. BMC Ophthalmol 2020;20(1):353. DOI: 10.1186/s12886-020-01618-3
15. Giamberardino MA, Affaitati G, Costantini R, et al. Acute headache management in emergency department. A narrative review. Intern Emerg Med 2020;15(1):109–117. DOI: 10.1007/s11739-019-02266-2
16. Casson RJ. Anterior chamber depth and primary angle-closure glaucoma: an evolutionary perspective. Clin Exp Ophthalmol 2008;36(1):70–77. DOI: 10.1111/j.1442-9071.2008.01672.x
17. Jonas JB, Nangia V, Gupta R, et al. Anterior chamber depth and its associations with ocular and general parameters in adults. Clin Exp Ophthalmol 2012;40(6):550–556. DOI: 10.1111/j.1442-9071.2011.02748.x
18. Qian Z, Xie X, Yang J, et al. Detection of shallow anterior chamber depth from two-dimensional anterior segment photographs using deep learning. BMC Ophthalmol 2021;21(1):341. DOI: 10.1186/s12886-021-02104-0
19. Yoo TK, Ryu IH, Kim JK, et al. A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs. Comput Methods Programs Biomed 2022;219:106735. DOI: 10.1016/j.cmpb.2022.106735
20. Grover AK, Honavar SG, Azad R, et al. A national curriculum for ophthalmology residency training. Indian J Ophthalmol 2018;66(6):752–783. DOI: 10.4103/ijo.IJO_327_18
21. Pujari A, Saluja G, Bhaskaran K, et al. Animal and cadaver human eyes for residents’ surgical training in ophthalmology. Surv Ophthalmol 2022;67(1):226–251. DOI: 10.1016/j.survophthal.2021.05.004
22. He B, de Smet MD, Sodhi M, et al. A review of robotic surgical training: establishing a curriculum and credentialing process in ophthalmology. Eye (Lond) 2021;35(12):3192–3201. DOI: 10.1038/s41433-021-01599-7
23. Zhang Z, Li S, Sun L, et al. Skills assessment after a grape-based microsurgical course for ophthalmology residents: randomised controlled trial. Br J Ophthalmol 2022:107(9):1395–1402. DOI: 10.1136/bjophthalmol-2022-321135
24. Greyner-Almeida HD, Mahdavi Fard A, Chen C, et al. A portable, low-cost practice model for microsurgical skills training. Int Ophthalmol 2022;42(8):2323–2333. DOI: 10.1007/s10792-022-02229-1
25. Clarkson JG. Training in ophthalmology is critical for all physicians. Arch Ophthalmol 2003;121(9):1327. DOI: 10.1001/archopht.121.9.1327
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