Detection of Parkinson's Disease Through Automated Pupil Tracking of the Post-illumination Pupillary Response

Abstract

Parkinson's disease (PD) is one of the most common neurodegenerative disorders, but it is often diagnosed after the majority of dopaminergic cells are already damaged. It is critical to develop biomarkers to identify the disease as early as possible for early intervention. PD patients appear to have an altered pupillary response consistent with an abnormality in photoreceptive retinal ganglion cells. Tracking the pupil size manually is a tedious process and offline automated systems can be prone to errors that may require intervention; for this reason in this work we describe a system for pupil size estimation with a user interface to allow rapid adjustment of parameters and extraction of pupil parameters of interest for the present study. We implemented a user-friendly system designed for clinicians to automate the process of tracking the pupil diameter to measure the post-illumination pupillary response (PIPR), permit manual corrections when needed, and continue automation after correction. Tracking was automated using a Kalman filter estimating the pupil center and diameter over time. The resulting system was tested on a PD classification task in which PD subjects are known to have similar responses for two wavelengths of light. The pupillary response is measured in the contralateral eye to two different light stimuli (470 and 610 nm) for 19 PD and 10 control subjects. The measured Net PIPR indicating different responsiveness to the wavelengths was 0.13 mm for PD subjects and 0.61 mm for control subjects, demonstrating a highly significant difference (p < 0.001). Net PIPR has the potential to be a biomarker for PD, suggesting further study to determine clinical validity.