Parkinson's DiseaseK23NCT02837172
Diagnosis of PD and PD Progression Using DWI
An observational study of Parkinson's Disease, run by University of Alabama at Birmingham at 1 site in United States.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 19 years and older
- Conditions the study is for
- Parkinson's Disease
- What is being tested?
- Diffusion Weighted Imaging (DWI)
- How many people
- 58 participants
- Where
- 1 siteUnited States
- Study dates
- 25 Sep 2014to 14 Apr 2019
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 100 PD subjects with DaTscan, and 210 (140 PD/70 control) from the PPMI dataset
Who may be able to join
- Patients 19 and older
- Referred for clinical DaTscan for possible PD
- Controls from the PPMI dataset.
Who cannot join
- Pregnant women
- Participants that cannot participate in MRI (metallic artifact or other contraindication(s) to MRI at 3T)
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Alabama at Birmingham
Birmingham, Alabama, 35233
About this study
Official title: 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.
Read the detailed 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.
- Conditions
- Parkinson's Disease
- Being tested
- Diffusion Weighted Imaging (DWI)
- Medical subject headings
- Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diffusion Weighted Imaging (DWI)Other
MDS-UPDRS,Montreal Cognitive Assessment, PDQ-39, DTI imaging (MRI), and neurological examination.
Expert evaluation: Record review, PD Medical History and PD Family History Form, the Montreal Cognitive Assessment, PDQ-39. standard, full, neurological examination, and MDS-UPDRS
| Study group | Role | What they receive |
|---|---|---|
| Parkinson's disease from UAB | MDS-UPDRS,Montreal Cognitive Assessment, PDQ-39, Diffusion Weighted Imaging (DWI), and neurological examination. Receives: Other: Diffusion Weighted Imaging (DWI) | |
| Parkinson's disease from PPMI dataset | 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 | Obtain retrospective and prospective de-identified DTI imaging and data from the PPMI dataset |
What is being measured
The primary outcome is the main question the study is designed to answer.
MRI and DAT scan: Accuracy of diagnosis of Parkinson's disease in a clinically relevant population
The study investigators will measure if MRI, specifically diffusion weighted imaging, can predict existence of Parkinson's disease. The study investigators will valuate if the derived MRI prediction matches or exceeds the accuracy of DATscan in detecting Parkinson's disease. The clinical/radiology reading of the DAT scan will determine the DAT scan diagnosis. The MRI scan diagnosis will be derived from statistical analysis of the full 5-dimensional brain DWI signal, as well as signals such as MRI T1 and resting fMRI signal. Methods of analysis will include using standard statistical techniques, the investigators published novel statistical techniques, and techniques such as Deep Learning and other artificial intelligence/learning algorithms.
Measured: 3-5 years
Secondary outcomes (1)
Can MRI profile risk for tremor and postural instability in PD
The study investigators will measure if MRI, specifically diffusion weighted imaging, can predict at disease onset which individuals with Parkinson's disease are at risk of developing significant postural instability and gait dysfunction.The MRI scan prediction will be derived from statistical analysis of the full 5-dimensional brain DWI signal, as well as signals such as MRI T1 and resting fMRI signal. Methods of analysis will include using standard statistical techniques, the investigators published novel statistical techniques, and techniques such as Deep Learning and other artificial intelligence/learning algorithms.
Measured: 3-5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Jul 2016 (estimated)
- Study start25 Sep 2014
- Primary completion14 Apr 2019
- Study completion14 Apr 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Parkinson's DiseaseStudies of the same condition, open and under way.
- More trials run by University of Alabama at BirminghamThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Other
- Enrolment
- 58 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Alabama at Birmingham
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Dr. Frank Michael Skidmore, University of Alabama at Birmingham
- Investigators
- Frank Skidmore, MD, Principal investigator, University of Alabama at Birmingham
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02837172
- Sponsor's protocol ID
- K23NS083620
- Acronym
- K23
- Status last verified
- Jun 2019
- First submitted
- 29 Apr 2016
- Last updated
- 19 Jun 2019
- Results posted
- No
- Data monitoring committee
- No
- Individual data sharing
- Yes: progress report information to NIH
Study at a glance
From the registry record, last updated by the sponsor on 19 Jun 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Diagnosis of Parkinson's Disease and Prediction of Progression Using Diffusion Weighted Imaging
- ClinicalTrials.gov ID
- NCT02837172
- Acronym / sponsor ID
- K23 / K23NS083620
- Conditions
- Parkinson's Disease
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 58 participants (actual)
- Lead sponsor
- University of Alabama at BirminghamUniversity, hospital or other
- Study start
- 25 Sep 2014 (actual)
- Primary completion
- 14 Apr 2019 (actual)
- Study completion
- 14 Apr 2019 (actual)
- First posted
- 19 Jul 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Case-control
- Time perspective
- Other
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Parkinson's disease from UAB | – | Other: Diffusion Weighted Imaging (DWI)MDS-UPDRS,Montreal Cognitive Assessment, PDQ-39, Diffusion Weighted Imaging (DWI), and neurological examination. |
| Parkinson's disease from PPMI dataset | – | –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 | – | –Obtain retrospective and prospective de-identified DTI imaging and data from the PPMI dataset |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 100 PD subjects with DaTscan, and 210 (140 PD/70 control) from the PPMI dataset
Key inclusion criteria (3 listed)
- Patients 19 and older
- Referred for clinical DaTscan for possible PD
- Controls from the PPMI dataset.
Key exclusion criteria (2 listed)
- Pregnant women
- Participants that cannot participate in MRI (metallic artifact or other contraindication(s) to MRI at 3T)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Diffusion Weighted Imaging (DWI)MDS-UPDRS,Montreal Cognitive Assessment, PDQ-39, DTI imaging (MRI), and neurological examination. Expert evaluation: Record review, PD Medical History and PD Family History Form, the Montreal Cognitive Assessment, PDQ-39. standard, full, neurological examination, and MDS-UPDRS | Other | Parkinson's disease from UAB |
Primary outcome
MRI and DAT scan: Accuracy of diagnosis of Parkinson's disease in a clinically relevant population
Time frame: 3-5 years
The study investigators will measure if MRI, specifically diffusion weighted imaging, can predict existence of Parkinson's disease. The study investigators will valuate if the derived MRI prediction matches or exceeds the accuracy of DATscan in detecting Parkinson's disease. The clinical/radiology reading of the DAT scan will determine the DAT scan diagnosis. The MRI scan diagnosis will be derived from statistical analysis of the full 5-dimensional brain DWI signal, as well as signals such as MRI T1 and resting fMRI signal. Methods of analysis will include using standard statistical techniques, the investigators published novel statistical techniques, and techniques such as Deep Learning and other artificial intelligence/learning algorithms.
1 secondary outcome
Can MRI profile risk for tremor and postural instability in PD
Time frame: 3-5 years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Jun 2019.
- Individual participant dataSharing planned: Yes. progress report information to NIH
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Frank Skidmore, MD principal investigator
University of Alabama at Birmingham
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Parkinson's Disease, run by University of Alabama at Birmingham at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Jun 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
MRI and DAT scan: Accuracy of diagnosis of Parkinson's disease in a clinically relevant population (time frame: 3-5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Jun 2019.