Glyxambi
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
  • Users Online: 2772
  • Home
  • Print this page
  • Email this page


 
   Table of Contents      
ORIGINAL ARTICLE
Year : 2019  |  Volume : 67  |  Issue : 10  |  Page : 1560-1563

Smartphone photography for screening amblyogenic conditions in children


Department of Ophthalmology, King Georges' Medical University, Lucknow, Uttar Pradesh, India

Date of Submission03-Jan-2019
Date of Acceptance08-May-2019
Date of Web Publication23-Sep-2019

Correspondence Address:
Dr. Siddharth Agrawal
Department of Ophthalmology, King Georges' Medical University, Lucknow - 226 003, Uttar Pradesh
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijo.IJO_2090_18

Rights and Permissions
  Abstract 


Purpose: To validate the smartphone photography as a screening tool for amblyogenic conditions in children. Methods: Children between 5 to 8 years attending eye out patient department (OPD) were photographed (by an optometrist) with a smartphone to capture their pupillary red reflexes followed by clinical examination by the principal investigator (PI). The PI on the basis of clinical examination identified children with significant amblyogenic conditions and, subsequently, two ophthalmologists independently categorized the photographs on the basis of color, symmetry, and shape of the pupillary reflex into normal or abnormal. The identification of amblyogenic conditions on clinical examination was compared to that on photography. Refractive errors <3D and anisometropia <2D were excluded. Sensitivity, specificity, positive predictive value, and negative predictive value of smartphone photography screening were determined. Results: In all, 250 children were screened. Clinically 23.6% were harboring amblyogenic conditions. The mean sensitivity and specificity of screening by smartphone were 94% and 91%, respectively. Conclusion: Smartphone photography is a reliable tool for detection of amblyogenic conditions in children.

Keywords: Amblyopia, smartphone photography, vision screening


How to cite this article:
Gupta R, Agrawal S, Srivastava RM, Singh V, Katiyar V. Smartphone photography for screening amblyogenic conditions in children. Indian J Ophthalmol 2019;67:1560-3

How to cite this URL:
Gupta R, Agrawal S, Srivastava RM, Singh V, Katiyar V. Smartphone photography for screening amblyogenic conditions in children. Indian J Ophthalmol [serial online] 2019 [cited 2019 Oct 18];67:1560-3. Available from: http://www.ijo.in/text.asp?2019/67/10/1560/267423



A good screening test should be inexpensive, easy to administer, not harmful, and reliable.[1] Several photographic techniques have been tried for screening of amblyogenic factors since 1979.[2] They work on the principle of Bruckner test frequently used for amblyopia screening in developing countries.[3],[4] In recent times, photo screening has gained attention as a method for large-scale vision screening. However, need for special equipment and recurring costs limit its utility in the developing world.[5]

This study attempts to use the smartphone photography as a screening tool for amblyogenic conditions in children. With smartphone's widespread use, photographs can easily be obtained even in the most remote areas without any need for additional resource or skill. Screening done with photographs will be more objective and less time consuming compared to vision screening in children. These photographs can even be archived and help in creating lasting records. Furthermore, these digital photographs can be analyzed by an expert available far from the screening area and, thus, overcome geographic and economical barriers in providing medical care especially in developing countries. With many potential benefits, screening done with smartphone photographs may well prove to be a promising alternative.


  Methods Top


Considering the obvious already discussed advantages of smartphone photography as a screening modality in children, we conducted a pilot study prior to this study to compare the inter- and intraobserver variability by presenting the same set of 50 photographs (of normal children and those with conditions altering the pupillary light reflex) for analysis to the same ophthalmologists (as in this study) in random sequences where each photograph appeared twice. The interrater agreement (kappa value) was 0.61, which showed substantial agreement. Prior to the pilot study, 20 photographs (10 normal and 10 abnormal) were together viewed and analyzed by two ophthalmologists on Windows Photo viewer on a 15” LED screen to lay down criteria for normal reflex. Images were magnified when in doubt. Well centered, round, homogenous, reddish, symmetrical glow with a horizontal diameter of half to one-fourth of corneal diameter was considered normal. Any deviation from this was considered abnormal. After the pilot study, errors in its observations were analyzed with aim to minimize them in future. Main limitations of the pilot study being OPD-based sample without predefined age.

This prospective cross-sectional study was designed to validate the utility of smartphone in detecting amblyogenic conditions. It was conducted after institutional ethical committee approval (Ref Code: 89th E.C.M.IIB Thesis/P5) in children attending the eye OPD for the first time with an ocular complaint. 250 consecutive children aged between 5 to 8 years with consenting parents were recruited after informed written consent.

Sample size calculation: Reviewing our records, the prevalence of the moderate-to-high refractive errors, anisometropia, strabismus, developmental cataract, and corneal opacities in the target population was estimated at a minimum of 20%. A higher frequency of these conditions in our patients could be attributed to ours being a tertiary care referral center for pediatric patients. The confidence level of 95% was agreed to be acceptable (z = 1.96, P = 0.2, and d = 0.05). The sample size was calculated to be 245 by the formula n = z2 P(1-P)/d2. We recruited a total of 250 children considering the possibility of few photographs being ineligible for analysis due to the lack of clarity. An agreement of 80% between photographs and clinical diagnosis was considered as limit for noninferiority of photography over clinical examination in detecting the above conditions.

Technique of photography: Photography was done in a moderately illuminated room to have a mesopic pupil size of about 6.5 mm. Subject was made to sit at 1-m distance at same level as the technician with both eyes fixing at the phone camera. Photograph was taken with a smartphone (OPPO A37f) with camera specification of 8MP rear camera with pixel density of 293 pixels per inch, with a resolution of 720 × 1280 pixels and color reproduction 16M with a f/2.4 aperture and LED flash (switched on). Centre of the flash was 4 mm away from the center of the camera. The photograph was repeated if the child moved, closed eyes, assumed a head posture (head tilt, face turn, and chin position were specifically checked), or the image captured was blurred. An average of two attempts was required each time. Fixing at a distant object could potentially relax the accommodative effort but when the subject did so the clarity of the red reflex was lost. Hence, we kept the camera as the point of fixation.

This was followed by clinical examination by the PI ophthalmologist to categorize the children into normal or abnormal based on refraction and ocular findings. Ocular surface diseases, refractive errors ≤ 3D and anisometropia ≤ 2D were considered as normal.

The methodology is explained in [Flowchart 1] and [Flowchart 2].



Statistical analysis

Categorical variables were presented in number and percentage. Categorical variables were compared using chi-square test/Fischer's exact test as appropriate. The data were entered in MS EXCEL spreadsheet and analysis was done using statistical package for social sciences (SPSS) version 16.0.


  Results Top


Mean age of the patients was 6.08 ±1.11 years. None of the photographs were rejected for analysis. The PI categorized 59 (23.6%) subjects as abnormal. These were considered the “gold standard values” against which the test (photograph analysis) was validated. Ophthalmologist 1 and 2 considered 73 (29.2%) and 72 (28.8%) of photographs as abnormal, respectively. The agreement between PI and ophthalmologist 1 was 83.2% and between PI and ophthalmologist 2 was 87.1%. The level of significance was <0.001 in both. The results are summarized in [Table 1] and [Table 2]. Among the clinically positive 59 patients, 32 had bilateral (including 8 with anisometropia and 7 with strabismus) and 17 had unilateral disease. [Figure 1] shows photographs in different conditions. The interrater agreement (kappa value) between ophthalmologist 1 and 2 was 0.928, which shows near perfect agreement.[6]
Table 1: Summary of results

Click here to view
Table 2: Details of gold standard “positive” (+) patients

Click here to view
Figure 1: Photographs in different conditions (top to bottom) 1. Normal 2. Left esotropia 3. Hypermetropia (+4.0D) both eyes 4. Anisometropia (RE emmetropia, LE +3.0D) 5. Myopia (-6.0D) both eyes 6. Normal 7. Retinoblastoma RE 8. Anisometropia (RE emmetropia, LE +6.5D) 9. Left esotropia 10. Myopia (-4.5D) both eyes

Click here to view



  Discussion Top


Our study focuses on reliability of smartphone photography as a screening test for significant visual morbidity in children. This is the first Indian study done to evaluate the utility of smartphone photographs as screening modality for amblyogenic conditions in children (Pubmed search). Digital camera has been used in the past but the universal availability of smartphones makes it more relevant.[7] Studies done in past using photoscreeners demonstrated a sensitivity and specificity ranging from 37% to 94% and from 40% to 90%, respectively.[8],[9],[10] This wide range in sensitivity and specificity makes these photoscreeners unreliable as screening tools. In contradiction to these results, our study demonstrated a high mean sensitivity (94%) and specificity (91%) in detecting the presence of visual morbidity. Agreement between clinical and photograph analysis was about 85%. Additionally, a high level of agreement between ophthalmologists in our study further points to the reliability of the smartphone photo analysis as the screening test. This high yield and agreement in our study could be due to a pilot study done by the same team of investigators in the past. Standard guidelines were formalized to categorize the Bruckner reflexes as normal or abnormal and same were applied in this study too. It would be interesting to do a comparative study with the photoscreener in future.

All high refractive errors ≥ 5D were successfully screened in this study. Moderate refractive errors between 3D and 5D were responsible for all the false negatives. Low refractive errors and anisometropia were excluded due to near normal appearing Bruckner reflex, and these have lesser amblyogenic potential. This may, however, be considered a study limitation.

Apart from refractive errors, the photographs had 100% sensitivity for all other conditions. Clinical photographs in past have been found useful in detecting ocular conditions like retinoblastoma.[11] In this study too, the only case of retinoblastoma was successfully screened by both the ophthalmologists. Due to rarity of such occurrences and limited sample size, we cannot highlight the sensitivity and specificity of our test for specific ocular morbidities.

The next step would be to validate this test in community, in younger children, and for specific ocular morbidities. Using appropriate statistical variables for community-based screening considering confidence level of 99% (z = 2.58, P = 0.05, and d = 0.0125), a sample size of about 2500 would be required. With encouraging results of this study, we are already working on this larger study.

Using a relatively in-expensive modality like smartphone, the screening method becomes vastly economical. Compared to the photoscreeners that cost $600 in addition to significant recurring expenses, smartphones are available for $100 only.[12] This makes it an ideal screener for developing countries. As most of the analyses are based on objectifying various characteristics of Bruckner's reflex (color, size, shape, and symmetry), software can be developed for quick and accurate analyses. An artificial intelligence based system can lessen the burden of screening from limited trained human resources in developing countries, which can further economize the screening process. However, it should be understood that tests based on Bruckner reflex require a minimum standard of photograph and would require a basic training of the photographer. Also, conditions not affecting the media clarity like diseases of the optic nerve and retina are likely to be missed by this screening modality.


  Conclusion Top


Smartphone photography is a reliable tool for detection of amblyogenic conditions in children.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Maxim LD, Niebo R, Utell MJ. Screening tests: A review with examples. Inhal Toxicol 2014;26:811-28.  Back to cited text no. 1
    
2.
Kaakinen K, Tommila V. A clinical study on the detection of strabismus, anisometropia or ametropia of children by simultaneous photography of the corneal and the fundus reflexes. Acta Ophthalmol (Copenh) 1979;57:600-11.  Back to cited text no. 2
    
3.
Amitava AK, Kewlani D, Khan Z, Razzak A. Assessment of a modification of Brückner's test as a screening modality for anisometropia and strabismus. Oman J Ophthalmol 2010;3:131-5.  Back to cited text no. 3
[PUBMED]  [Full text]  
4.
Jain P, Kothari MT, Gode V. The opportunistic screening of refractive errors in school-going children by pediatrician using enhanced Brückner test. Indian J Ophthalmol 2016;64:733-6.  Back to cited text no. 4
[PUBMED]  [Full text]  
5.
Kinori M, Molina I, Hernandez EO, Robbins SL, Granet DB, Coleman AL, et al. The PlusoptiX photoscreener and the retinomax autorefractor as community-based screening devices for preschool children. Curr Eye Res 2018;43:654-8.  Back to cited text no. 5
    
6.
Mary L. McHugh. Interrater reliability: The kappa statistic. Biochem Med (Zagreb) 2012;22:276-82.  Back to cited text no. 6
    
7.
Bani SA, Amitava AK, Sharma R, Danish A. Beyond photography: Evaluation of the consumer digital camera to identify strabismus and anisometropia by analyzing the Bruckner's reflex. Indian J Ophthalmol 2013;61:608-11.  Back to cited text no. 7
[PUBMED]  [Full text]  
8.
Carrera A, Saornil MA, Zamora MI, Maderuelo A, Cañamares S, Pastor JC. Detecting amblyogenic diseases with the photographic Bruckner test. Strabismus 1993;1:3-9.  Back to cited text no. 8
    
9.
Kennedy RA, Thomas DE. Evaluation of the iScreen digital screening system for amblyogenic factors. Can J Ophthalmol 2000;35:258-62.  Back to cited text no. 9
    
10.
Arnold RW, Arnold AW, Stark L, Arnold KK, Leman R, Armitage MD. Amblyopia detection by camera: Gateway to portable, inexpensive vision screening (calibration and validation of inexpensive, pocket-sized photoscreeners). Alaska Med 2004;46:63-72.  Back to cited text no. 10
    
11.
Abdolvahabi A, Taylor BW, Holden RL. Colorimetric and longitudinal analysis of leukocoria in recreational photographs of children with retinoblastoma. PLoS One 2013;30;8:e76677.  Back to cited text no. 11
    
12.
Rogers DL, Neely DE, Chapman JB, Plager DA, Sprunger DT, Sondhi N. Comparison of the MTI photoscreener and the Welch-Allyn SureSight autorefractor in a tertiary care center. J AAPOS 2008;12:77-82.  Back to cited text no. 12
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2]



 

Top
 
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
Methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed255    
    Printed1    
    Emailed0    
    PDF Downloaded104    
    Comments [Add]    

Recommend this journal