Pilot Study of Smartphone Infrared Pupillography and Pupillometry

Abstract

To describe and validate a novel portable smartphone-based infrared pupillographer. Materials and Methods: A prototype infrared smartphone pupillographer device was custom designed for this project. Infrared video and photo pupillography were attempted on 12 patients with different clinical pupillary examination findings. Captured pupillography media files were assessed by three masked investigators, and the agreement between their qualitative clinical evaluation was tested against the evaluation of the neuro-ophthalmologist who performed the real-time examination and pupillography. Quantitative measurements of the pupillary diameter were performed by three investigators using a custom designed smartphone application on three different smartphones and on a personal computer. Measurements obtained by the three investigators using the smartphone and the desktop computer were compared. Results: Infrared video pupillography of high quality was successfully captured for light and near pupillary reflexes, and infrared still photographs were obtained in light and dark conditions in 23 eyes of the 12 patients. Examination findings included relative afferent pupillary defect (n = 5), normal pupillary examination (n = 4), anisocoria (n = 2), and relative afferent pupillary reflex by reverse (n = 1). There was 100% agreement in the qualitative pupillary evaluation of the masked investigators compared with real time clinical examination. Quantitative measurements of pupillary size obtained on the smartphone and desktop computer showed excellent agreement among the three investigators with intraclass correlation (ICC) coefficient ranging from 0.982-0.986 (P<0.001) and 0.995 (P<0.001) for the smartphone and the desktop computer groups, respectively. Level of agreement ranged between −0.27 and 0.32. Mean pupil diameter errors were 0.03 ± 0.15 mm between groups (P = 0.248). Conclusion:This pilot study demonstrates the feasibility of smartphone-based infrared pupillography for high quality photo and video documentation of pupillary examination at the bedside and in the clinic with accurate and reproducible measurements of the pupillary size in light and dark conditions.

Introduction of Deep Learning-Based Infrared Image Analysis to Marginal Reflex Distance1 Measurement Method to Simultaneously Capture Images and Compute Results: Clinical Validation Study

“…Additionally, several studies have used IR images for eye segmentation [18,19]. However, the main purpose of eye segmentation is gaze tracking to analyze human behavior, and it is not relevant to MRD1 measurements.…”

Medical Students’ Perspectives Regarding the Use of a Slit-Lamp Smartphone Adapter for Clinical Slit-Lamp Photography

“…The ubiquity and ever-ready presence in addition to the high level of connectivity, portability, and multi-functionality of smartphones make them an important and widely used tool for ophthalmic clinical photography [3][4][5][6]. Smartphone camera use for slit-lamp photography has been proven effective and reliable for the documentation of different ocular conditions, including assessment of glaucomatous optic neuropathy [7], grading of diabetic retinopathy [8], evaluation of senile cataracts [9], and postoperative cataract surgery imaging [4].…”

Iris Color Matters—A Contractility Analysis With Dynamic Volume-Rendered Optical Coherence Tomography Pupillometry

“…Most evaluations of pupillary function are based on the use of pen torches, infrared dynamic pupillometry, or smartphone-based methods. 6 – 8 Pupillary light response is a well-established parameter for assessing neurological afferent and efferent pathways of the eye. However, the reproducibility of such measurements is often poor, both in subjective assessments and for quantitative approaches.…”