Diagnosis of PD and PD Progression Using DWI
| Status: | Recruiting |
|---|---|
| Conditions: | Parkinsons Disease |
| Therapuetic Areas: | Neurology |
| Healthy: | No |
| Age Range: | 19 - Any |
| Updated: | 5/19/2018 |
| Start Date: | September 2014 |
| End Date: | December 2019 |
| Contact: | Frank Skidmore, MD |
| Email: | fskidmore@uabmc.edu |
| Phone: | 205-934-6510 |
Diagnosis of Parkinson's Disease and Prediction of Progression Using Diffusion Weighted Imaging
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.
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.
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.
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.
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)
We found this trial at
1
site
1720 2nd Ave S
Birmingham, Alabama 35233
Birmingham, Alabama 35233
(205) 934-4011
Phone: 205-934-6510
University of Alabama at Birmingham The University of Alabama at Birmingham (UAB) traces its roots...
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