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Neuroimaging for Parkinsonian Syndromes

This observational study aims to improve how we diagnose and predict the progression of Parkinson's disease (PD), Multiple System Atrophy (MSA), and Progressive Supranuclear Palsy (PSP). Researchers are looking for ways to use brain imaging (neuroimaging) to tell these conditions apart and to understand how quickly Parkinson's disease might progress in an individual. They will analyze different types of brain scans using advanced computer techniques. The study plans to enroll 90 participants, including people with Parkinson's disease, MSA, and PSP. Success will be measured by finding imaging markers that can predict how fast PD progresses and distinguish between these different neurodegenerative diseases. The current recruitment status is unclear.

Study design
This is an observational study with a planned enrollment of 90 participants. It involves two parts: studying existing data from people with Parkinson's disease and recruiting new participants with PD, MSA, and PSP.
What's involved
Participants will undergo several types of neuroimaging. Newly recruited participants will also have clinical scales performed at each study visit over two years to track disease severity.
Compensation
Not stated in the trial record.
Follow-up
Newly recruited participants will be followed clinically over 2 years. Imaging biomarkers will be measured at Baseline.

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NCT03872102

Facilitating Diagnostics and Prognostics of Parkinsonian Syndromes Using Neuroimaging

Recruiting
Not specifiedAll AgesObservational
University of Texas Southwestern Medical Center
~90 participants
Updated 2026-01-27 on ClinicalTrials.gov

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Imaging biomarker of progression rate
Measured over Baseline
+1 more outcome measured

Conditions

Parkinson Disease
Multiple System Atrophy
Progressive Supranuclear Palsy

Explore related trials

Multiple System AtrophyParkinson DiseaseProgressive Supranuclear Palsy

Where it's being run

1 sites across 1 states
Texas1

Study leadership

  • Padraig E O'Suilleabhain, MD · PRINCIPAL_INVESTIGATOR · University of Texas Southwestern Medical Center
  • Albert Montillo, PhD · PRINCIPAL_INVESTIGATOR · University of Texas Southwestern Medical Center

Who to contact

Padraig E O'Suilleabhain, MD
[email protected]
214-648-2943
Email the study team

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Do you actually qualify for this trial?

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Eligibility criteria

Inclusion

Diagnosis of Parkinson disease
Existence of sufficient clinical data from previous UTS Southwestern longitudinal study to determine progression rate (categorized as fast or slow)
Availability of suitable matched participant in the alternate progression group (fast or slow)
Willingness to participate in the imaging studies required for this study and to provide written informed consent
Duration of PD (since diagnosis) is \< 5 years
Willing to participate in imaging and clinical scoring visits, and provide written informed consent
Subject and investigator agree that it is highly likely subject will be able to participate throughout the 2-year study period (no plans to move)
Duration of MSA (since diagnosis) is \< 5 years
Willing to participate in imaging and clinical scoring visits, and provide written informed consent
Subject and investigator agree that it is highly likely subject will be able to participate throughout the 2-year study period (no plans to move away during the study)
Willing to participate in imaging and clinical scoring visits, and provide written informed consent
Subject and investigator agree that it is highly likely subject will be able to participate throughout the 2-year study period (no plans to move away during the study)
Roughly age and sex matched with the subjects in the PD cohort
No history or examination findings suggestive of any neurodegenerative disease
Normal gait, balance, and eye movements for age
No clinical evidence for symptomatic orthostatic hypotension
Willing to participate in imaging and clinical scoring visits, and provide written informed consent
Subject and investigator agree that it is highly likely subject will be able to participate throughout the 2-year study period (no plans to move away during the study)

Exclusion

Any contraindications to undergoing the multimodal imaging program
All females of child-bearing potential, between the ages of 18-55, will be excluded from the study, unless they are confirmed to be not pregnant with a pregnancy test prior to scanning
This study will require constant clear communication throughout the duration of the study; therefore, non-English speakers will be excluded
Right-handed finger amputees
Cast on right hand or fingers at the time of enrollment
Has clinically significant liver, kidney, lung, metabolic or hormone disturbances which pose safety risk
Has a current clinically significant heart disease that poses a safety risk
Has a current clinically significant infectious disease or a medical comorbidity which poses a safety risk
Has a history of relevant severe drug allergy or hypersensitivity
Have a history of drug, alcohol, or substance dependence or abuse within the last year, or prior prolonged history of dependence or abuse
Currently undergoing chemotherapy or radiation for cancer
Recreational drug use in past six months
Central nervous systems disease or brain injury that would preclude participation in this study
Psychiatric or neurological disorder that would preclude participation in this study
Inability to keep or maintain research appointments
Severe disease progression such that participation in the imaging tests would be impossible or difficult
Non-availability of a suitable matched participant in the alternate progression group (fast or slow)

What this trial measures

  • Imaging biomarker of progression rateBaseline

    The imaging biomarker consists of a machine learning model that distinguishes fast and slow progressors using the neuroimaging data. The performance of the model will be assessed quantitatively using widely adopted performance metrics: sensitivity, specificity, and accuracy.

  • Imaging biomarker that discriminates different neurodegenerative diseasesBaseline

    The imaging biomarker consists of a machine learning model that differentiates the parkinsonian diseases: PD, PSP, and MSA using the neuroimaging data. The performance of the model will be assessed quantitatively using widely adopted performance metrics from the classification confusion matrix. The metrics will include disease sensitivity, disease specificity, and disease specific accuracy and overall accuracy.