Tracking eye movements to diagnose Parkinson's

Identifying and distinguishing Parkinson’s from other progressive brain disorders is difficult because there are no biological tests a doctor can administer to diagnose the illness. Instead, doctors primarily rely on medical history and clinical assessment.

At Queen’s University, PhD candidate Heidi Riek is tracking the eye movements of people with Parkinson’s to create a tool to make that diagnosis easier.

Riek, a neuroscientist, is analyzing the results of tests involving a video camera and software that continuously measures eye movements, including the speed at which they glance between two fixed points. That movement is called a saccade.

“This is the type of eye movement we use in our daily life all the time to look between two objects in a scene,” Riek says.

To conduct the tests, researchers have people with Parkinson’s sit in front of a computer screen and look at, or away from, dots that appear on the screen. The camera tracks the movements of their pupils.

Riek analyzes the speed and distance of the saccades, as well as how soon they begin after the dot comes onto the screen. She compares these measurements to the saccades of people who do not have Parkinson’s, and to the eye movements of people with Alzheimer’s, Amyotrophic Lateral Sclerosis (ALS), frontotemporal dementia, and cerebrovascular disease.

She also notes if participants are able to follow directions accurately on where to look in relation to the dots – instructions people living with dementia may have difficulty following.

“Often what we see in neurodegenerative disease is an increased number of errors, particularly on the task when people are asked to look away from the dot,” Riek says.

The Ontario Neurodegenerative Disease Research Initiative (ONDRI) has already collected much of the data Riek is analyzing. The initiative involves people with Parkinson’s and people with other neurodegenerative disorders.

The eye movement patterns that Riek’s research will generate would provide a baseline against which doctors could compare the eye movements of their own patients. The findings could determine whether someone has Parkinson’s, the disease’s stage of progression, and whether dementia is present.

“We’re hoping eventually we’ll be able to develop a clinical tool that will automatically help doctors detect the presence of Parkinson’s,” she says.

“This would be particularly valuable if eye movements were able to detect Parkinson’s at earlier stages.”

Riek hopes this tool will also identify differences in people’s eye movements based on their age and sex and other variables. Those differences could eventually result in earlier and better treatment for people with Parkinson’s.

“A diagnostic tool like this that is able to tease out some of that individual variation between patients could be really helpful to make sure everybody is getting the treatment that best supports them,” she says.