Smartphone-acquired image photogrammetry for detection of shallow anterior chamber

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Purpose: This study aimed to explore the role of smartphone imaging of the eye using two perspectives — anterior and temporal — in the detection of a shallow anterior chamber (AC). The AC depth (ACD) of an eye can be used as a surrogate marker for identification of eyes at risk of developing angle-closure disease. Methods: A prospective observational study was conducted at a university teaching hospital in South India. Each eye was photographed with a smartphone using the two perspectives, followed by quantitative measurement of ACD using optical biometry. The percentage of nasal iris illuminated was measured from the image acquired using the flashlight method (anterior perspective), whereas pupil position relative to the cornea was measured from the image acquired using the temporal perpendicular method (temporal perspective). The recei-ver-operating characteristic curve and area under the curve (AUC) were studied for both perspectives independently for overall predictive accuracy in detection of shallow AC (ACD <2.7 mm, obtained by IOL Master). Results: A total of 275 eyes were examined, of which 77 (28%) had an ACD <2.7 mm. The accuracy of detection of shallow AC was found to be 95.2% for both perspectives when used alone or in combination. AUC of the anterior perspective was 0.99 (95% CI 0.982–0.997). The AUC for the temporal perspective was 0.993 (95% CI 0.988–0.999). Conclusion: Smartphone-acquired image photogrammetry of an eye with anterior and temporal perspectives independently and in combination provided accuracy nearing 95% in the detection of shallow AC (ACD <2.7 mm). Registration: This trial was registered with the Clinical Trial Registry of India (CTRI/2018/ 09/015867, September 28, 2018).

Original languageEnglish
Pages (from-to)1875-1885
Number of pages11
JournalClinical Ophthalmology
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Ophthalmology


Dive into the research topics of 'Smartphone-acquired image photogrammetry for detection of shallow anterior chamber'. Together they form a unique fingerprint.

Cite this