Diagnosis of PD and PD Progression Using DWI (K23)

The University of Alabama at Birmingham

Status: Completed

Conditions: Parkinson's Disease

Treatments: Other: Diffusion Weighted Imaging (DWI)

Study type: Observational

Funder types: Other

Identifiers

NCT02837172

K23NS083620

Details and patient eligibility

About

This project will evaluate the utility of diffusion tensor imaging (DTI) as an adjunctive method to improve early diagnosis of Parkinson's disease (PD). Two populations will be evaluated in this study: 1) Individuals with uncertain PD diagnosis who receive a DaTscan, and 2) individuals with well characterized PD and healthy controls, drawn from the fully enrolled Parkinson's Progression Markers Initiative (PPMI) PD and control cohorts.

Full description

Specific Aim 1a: Compare the outcome of a DTI based prediction with a contemporaneous clinical DAT scan in 100 subjects with suspected parkinsonism, and determine rate of concordance between the two diagnostic techniques.

Specific Aim 1b: Compare predictive accuracy of a baseline DTI with a "gold standard" expert diagnosis after 36 months of follow up in 100 subjects receiving DaTscan for suspected parkinsonism.

Specific Aim 2a: Use TBM to evaluate volume and cross-sectional caliber (based on point-wise fiber track direction) of the fimbria, pallidonigral tracts, and subthalamic-nigral tracts in PD and healthy controls. Ascertain if changes in white matter volume and caliber can be used to predict presence of PD from the PPMI study. Secondarily, using a model free approach, determine what white matter features based on TBM predict presence of disease.

Specific Aim 2b: Use TBM to determine if an increased rate of change in volume and cross-sectional caliber of the fimbria, and hypertrophic pallidonigral, and subthalamic-nigral tracts identified in aim 2a, are associated with a more rapid rate of disease progression in PD. Secondarily, using a model free approach, determine what white matter features based on TBM predict a faster rate of disease progression over the 5 year course of the PPMI study.

Specific Aim 3a: Compare DTI FA in TD-PD and PIGD-PD in the thalamus and lobule IX of the cerebellum , studying subjects from the PPMI study. Predict signal in these regions will predict phenotypic expression of disease. Using TBM and bootstrapping, determine the relationship between phenotypic expression of disease and white matter input/output pathways from the thalamus, and from lobule IX of the cerebellum.

Enrollment: 58 patients

Sex: All

Ages: 19+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients 19 and older
• Referred for clinical DaTscan for possible PD
• Controls from the PPMI dataset.

Exclusion criteria

• Pregnant women
• Participants that cannot participate in MRI (metallic artifact or other contraindication(s) to MRI at 3T)

Trial design

58 participants in 3 patient groups

Parkinson's disease from UAB

Description:

MDS-UPDRS,Montreal Cognitive Assessment, PDQ-39, Diffusion Weighted Imaging (DWI), and neurological examination.

Treatment:

Other: Diffusion Weighted Imaging (DWI)

Parkinson's disease from PPMI dataset

Description:

Obtain retrospective and prospective de-identified data from the The Parkinson's Progression Markers Initiative (PPMI) dataset on Parkinson's disease (PD) subjects that have the following characteristics: within 2 years of diagnosis, positive DaTscan, and not (at study entry) on any PD related medication.

Controls from PPMI dataset

Description:

Obtain retrospective and prospective de-identified DTI imaging and data from the PPMI dataset