Viewing Study NCT03872102


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Study NCT ID: NCT03872102
Status: RECRUITING
Last Update Posted: 2025-01-22
First Post: 2019-03-07
Is NOT Gene Therapy: False
Has Adverse Events: False

Brief Title: Facilitating Diagnostics and Prognostics of Parkinsonian Syndromes Using Neuroimaging
Sponsor: University of Texas Southwestern Medical Center
Organization:

Study Overview

Official Title: Quantitative Diagnostics of Parkinsonian Syndromes Using Multi-modal Neuroimaging and Deep Learning
Status: RECRUITING
Status Verified Date: 2025-01
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
Brief Summary: The goals of this study are: 1) to identify biomarkers using neuroimaging that are associated with progression rate using statistical methods, and 2) to identify biomarkers that are associated with the differential diagnosis of Parkinson's disease and atypical parkinsonism.
Detailed Description: Management of patients with parkinsonian symptoms has two critical gaps: (1) there are no clinically accepted biomarkers that may be used to inform disease progression rate in an individual with Parkinson disease (PD), and (2) no biomarkers exist to inform differential diagnosis of conditions that exhibit parkinsonian symptoms and signs. This 2-year study aims to develop a multi-modal neuroimaging biomarker that enables the prediction of disease progression rate in PD, and a biomarker that enables the differential diagnosis of PD, multiple systems atrophy (MSA), progressive supranuclear palsy (PSP), and healthy controls.

This study consists of two parts; neuroimaging of a defined population of mid to late stage PD subjects currently followed at UT Southwestern Medical Center, and recruitment of new subjects with PD, MSA, and PSP who will be followed clinically over 2 years and who will undergo neuroimaging.

Participants will be asked to undergo several types of neuroimaging which will be analyzed using machine learning techniques.

At each study visit of the newly recruited cohorts, appropriate clinical scales will be performed based on their diagnosis and used to track and measure disease severity and progression.

Study Oversight

Has Oversight DMC: True
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: