Unstructured Eye Tracking as a Diagnostic and Prognostic Biomarker in Parkinsonian Disorders

Summary

Study Rationale:

No accurate tests currently exist to diagnose Parkinson's disease (PD) and the conditions which mimic it (atypical parkinsonism) at a very early stage. Similarly there are no accurate ways to track how these diseases progress in a very precise manner. Recording eye movements and pupils may be a very sensitive way of doing this and may contain important information about a patient's diagnosis and their cognitive and motor function.

Hypothesis:

We hypothesize that measuring eye movements and pupil changes while people watch short video clips will differentiate PD and atypical parkinsonism at an early stage. We hypothesize that eye movements and pupil changes will be able to track how a person's disease changes over time and could even predict their disease course from the start.

Before we can do this, we need to be able to accurately differentiate between PD and atypical parkinsonism and see how eye movements vary among people with the same disease.

Study Design:

We will ask a large number of people with PD and atypical parkinsonism to watch very brief video clips while we record eye movements and pupil responses. This is like changing the television channel every few seconds and observing what happens to a person's eyes as they search the new clip. We will compare these results between different disease groups and correlate them with clinical features of PD and atypical parkinsonism.

Impact on Diagnosis/Treatment of Parkinson's disease:

This may have enormous impact in the assessment of people with PD. It may become an important diagnostic tool, a prognostic marker at the early stage of disease, as well as providing the ability to track disease progression in clinical trials.

Next Steps for Development:

Once we can demonstrate that eye tracking can differentiate these conditions, we will follow a large number of patients to see how their eye movements and pupils change over time with their disease. If this is a reliable way to track disease it could be used to measure disease progression in these conditions and response to treatment.

Conditions

• Parkinson's Disease and Parkinsonism
• Progressive Supranuclear Palsy
• Multiple System Atrophy
• Corticobasal Degeneration

Interventions

BEHAVIORAL

Free-viewing eye tracking

Participants will watch 20 minutes of video clips while their eye movements, pupil size and blink rate are recorded

Sponsors & Collaborators

• Queen's University

  collaborator OTHER

• Conor Fearon

  lead OTHER

Principal Investigators

• Conor Fearon, MB PhD · Dublin Neurological Institute at the Mater Misericordiae University Hospital

Study Design

Allocation

NON_RANDOMIZED

Purpose

DIAGNOSTIC

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Max Age

100 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2022-12-01

Primary Completion

2024-08-15

Completion

2024-08-15

Countries

• Ireland

Study Locations