Objective:

To study pupillary light reflex (PLR) parameters in a pilot cohort of patients with dementia, compared to healthy controls, using a smartphone pupillometry application.

Background:

Decrease in cholinergic signaling is a significant component of neurodegenerative diseases, and its impact on PLR parameters may be useful as a detectable disease biomarker. However, no studies have yet investigated smartphone pupillometry for quantitative biomarker-based assessment of neurodegenerative disease.

Design/Methods:

We analyzed seven specific PLR parameters in a neurodegenerative disease cohort enrolled in a dedicated specialist clinic and compared them to previously collected healthy controls. The smartphone based pupillometry (Apertur, Inc) developed using HIPPA compliant cloud-based neural network, has an ability to improve the precision of findings over time. The PLR parameters included maximum diameter, minimum diameter, latency, percent change, mean constriction velocity, maximum constriction velocity, and mean dilation velocity. A one-tailed, two-sample independent t-test with post-hoc Bonferroni (corrected p≤0.007) was used.

Results:

Seven neurodegenerative disease patients and 141 healthy controls were enrolled. Neurodegenerative disease patients were 86% male with mean age of 74 years. Six had dementia or mild cognitive impairment due to Alzheimer’s disease while one had frontotemporal dementia. Two neurodegenerative disease patients were taking cholinesterase inhibitorss, and mean Montreal Cognitive Assessment (MoCA) was 20. Compared to healthy controls, neurodegenerative disease patients had smaller maximum diameter (mean±standard deviation; 3.08±0.65mm vs 4.2±0.99mm; p=0.007), lower percentage change (19.06±2.75% vs 33.8±8.22%; p<0.001), shorter latency (0.5±0.26s vs 0.9±0.77s; p=0.0067), reduced mean constriction velocity (0.4±0.24mm/s vs 0.85±0.39mm/s; p=0.004), and lower maximum constriction velocity (2.02±0.53mm/s vs 3.79±1.58mm/s; p<0.001).  

Conclusions:

In this pilot study, we utilized a novel smartphone pupillometer application requiring no external hardware to investigate PLR parameters in a cohort of neurodegenerative disease patients compared to healthy controls. Our findings demonstrate the potential for smartphone pupillometry in quantitative neurodegenerative disease assessment.