Measuring Relative Afferent Pupillary Defect
NCT05799066 · Status: ACTIVE_NOT_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 71
Last updated 2025-05-16
Summary
The goal of this prospective reliability study is to test the effectiveness of a commercially available, off-the-shelf virtual reality head-mounted display (VR HMD) and machine learning (ML) algorithms in detecting Relative Afferent Pupillary Defect (RAPD) in a group of subjects with known RAPD and another group with no known RAPD.
The main questions it aims to answer are:
* Does the use of the VR HMD and ML to replace the standard of care swinging flashlight test provide a more reliable and objective pupil measurement to detect RAPD?
* Can RAPD be detected by the VR HMD and ML algorithms at an earlier stage than the standard of care swinging light test?
Participants will be asked to undergo the standard of care swinging flashlight test, have their pupils manually measured, then have the test repeated using the VR HMD and ML.
Researchers will compare the measurements taken manually, following the standard of care swinging light test and those recorded by the VR HMD and ML to help answer the above questions.
Conditions
- Relative Afferent Pupil Defect (RAPD)
Interventions
- DIAGNOSTIC_TEST
-
Swinging Light test
The swinging light or pen light test with manual pupil measurements is the standard of care test for RAPD. This test consists of a light being shone in one eye for 3 to 4 seconds then shown in the other eye for 3 to 4 seconds, repeating 2 to 3 times. Pupils are measured manually immediately after the light test. Measurements are recorded in patient's medical record.
- DIAGNOSTIC_TEST
-
Virtual Reality Head-Mounted Display (VR HMD)
A light is shone from within the VR HMD, pupillary measurements are taken and recorded by the machine learning (ML) algorithm.
Sponsors & Collaborators
-
University of Nevada, Reno
collaborator OTHER -
The University of Texas Medical Branch, Galveston
lead OTHER
Principal Investigators
-
Kevin H Merkley, MD, MBA · University of Texas
Study Design
- Allocation
- NON_RANDOMIZED
- Purpose
- SCREENING
- Masking
- NONE
- Model
- PARALLEL
Eligibility
- Min Age
- 18 Years
- Max Age
- 85 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2023-05-04
- Primary Completion
- 2026-05-14
- Completion
- 2026-05-14
Countries
- United States
Study Locations
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