Evaluation of a Hirschberg Test-Based Application for Measuring Ocular Alignment and Detecting Strabismus

ABSTRACT

Purpose: Photographic Hirschberg test applications are practical options for screening in areas where a specialist is not available. A semi-automated Hirschberg test-based application was developed and evaluated on its ability to detect and measure strabismus at distance and near fixation.

Methods: This is a prospective cross-sectional inter-rater agreement study conducted at a tertiary hospital. Study A evaluated the ability of the application to determine the presence or absence of strabismus in subjects of unknown strabismus status (n = 28). Study B evaluated the ability of the application to measure the deviation of strabismic subjects (n = 8). All subjects underwent alternate prism cover test (APCT) at distance and near fixation. Facial photographs at distance and near fixation were taken. Each photograph underwent automated face and eye detection, manual limbus and corneal reflex identification, and strabismus detection and measurement.

Results: The application obtained a matching rate of 95.14% for the face and eyes. The application yielded a sensitivity of 92.86% for horizontal strabismus at distance and near fixation, however, with low specificity values (7.692%, 14.81%, and 8%). The Bland–Altman plots derived from Study B showed bias values of application measurements between 3.625Δ and 6.125Δ with wide intervals of the limits of agreement. Repeatability of the measurements yielded bias values of −0.625Δ and 2.5Δ for horizontal and vertical strabismus at distance and 4.375Δ and 1.25Δ at near fixation, respectively.

Conclusion: This semi-automated Hirschberg test-based application can effectively determine the face and eye location and shows potential as a screening tool for horizontal strabismus.

KEYWORDS:

• Strabismus
• Hirschberg test
• application
• smartphone
• screening

Acknowledgments

Francis Bautista, Lorenzo Miguel Pinaroc, and Mike del Castillo of Indigo Research, Quezon City, Philippines for extending their data science and computer vision expertise into ophthalmology and taking on this project. Dr. Ivan Imperial, whose knowledge in statistical analysis proved essential in bringing light to the significance of this research. And to the patients of the St. Luke’s Medical Center Out-patient department, for contributing their time and patience in bringing this study to fruition.

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Additional information

Funding

The authors received no external financial support for the research, authorship, and/or publication of this article.