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BRIEF RESEARCH REPORT article

Front. Ophthalmol.
Sec. New Technologies in Ophthalmology
Volume 4 - 2024 | doi: 10.3389/fopht.2024.1396511

Diagnostic accuracy of a modularized, virtual-reality-based automated pupillometer for detection of relative afferent pupillary defect in unilateral optic neuropathies

Provisionally accepted
Rahul Negi Rahul Negi 1,2Manasa Kalivemula Manasa Kalivemula 1Karan Bisht Karan Bisht 1Manjushree Bhate Manjushree Bhate 3Virender Sachdeva Virender Sachdeva 3,4Shrikant R. Bharadwaj Shrikant R. Bharadwaj 2,5*
  • 1 Centre for Technology Innovation, L V Prasad Eye Institute, Hyderabad, Andhra Pradesh, India
  • 2 Hyderabad Eye Research Foundation, L V Prasad Eye Institute, Hyderabad, Andhra Pradesh, India
  • 3 Child Sight Institute, L V Prasad Eye Institute, Hyderabad, India
  • 4 Nimmagadda Prasad Children's Eye Care Centre, L V Prasad Eye Institute, Visakhapatnam, India
  • 5 Brien Holden Institute of Optometry and Vision Sciences, L V Prasad Eye Institute, Hyderabad, India

The final, formatted version of the article will be published soon.

    Purpose: To describe the construction and diagnostic accuracy of a modularized, virtual reality (VR)based, pupillometer for detecting relative afferent pupillary defect (RAPD) in unilateral optic neuropathies, vis-à-vis, clinical grading by experienced neuro-ophthalmologists.Methods: Protocols for the swinging flashlight test and pupillary light response analysis used in a previous stand-alone pupillometer was integrated into the hardware of a Pico Neo 2 Eye® VR headset with built-in eye tracker. Each eye of 77 cases (mean±1SD age: 39.1±14.9yrs) and 77 age-similar controls were stimulated independently thrice for 1sec at 125lux light intensity, followed by 3sec of darkness. RAPD was quantified as the ratio of the direct reflex of the stronger to the weaker eye. Device performance was evaluated using standard ROC analysis.The median (25th -75th quartiles) pupil constriction of the affected eye of cases was 38% (17 -23%) smaller than their fellow eye (p<0.001), compared to an interocular difference of +/-6% (3 -15%) in controls. The sensitivity of RAPD detection was 78.5% for the entire dataset and it improved to 85.1% when the physiological asymmetries in the bilateral pupillary miosis were accounted for. Specificity and the area under ROC curve remained between 81 -96.3% across all analyses.Conclusions: RAPD may be successfully quantified in unilateral neuro-ophthalmic pathology using a VRtechnology-based modularized pupillometer. Such an objective estimation of RAPD provides immunity against biases and variability in the clinical grading, overall enhancing its value for clinical decision making.

    Keywords: Diagnostic accuracy, infrared, Neuro-ophthalmic pathology, edge detection, Swinging flashlight test, virtual reality

    Received: 05 Mar 2024; Accepted: 07 Aug 2024.

    Copyright: © 2024 Negi, Kalivemula, Bisht, Bhate, Sachdeva and Bharadwaj. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Shrikant R. Bharadwaj, Hyderabad Eye Research Foundation, L V Prasad Eye Institute, Hyderabad, Andhra Pradesh, India

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.