The Use of Resting State, fMRI and DTI in the Identification of Chronic Pain Conditions
| Status: | Recruiting |
|---|---|
| Conditions: | Chronic Pain, Chronic Pain |
| Therapuetic Areas: | Musculoskeletal |
| Healthy: | No |
| Age Range: | 20 - 70 |
| Updated: | 12/10/2016 |
| Start Date: | November 2016 |
| End Date: | January 2018 |
| Contact: | David S Wack, Ph.D. |
| Email: | dswack@buffalo.edu |
| Phone: | 716-838-5889 |
Resting state fMRI scans of chronic pain sufferers will be compared to those of healthy
normals and may be sufficiently different to allow a high level of classification accuracy
of whether subjects have chronic pain. In addition, investigators will utilize DTI and a
brief activation state using pain rumination to assess whether investigators can reliably
find differences between chronic pain sufferers and healthy normals.
normals and may be sufficiently different to allow a high level of classification accuracy
of whether subjects have chronic pain. In addition, investigators will utilize DTI and a
brief activation state using pain rumination to assess whether investigators can reliably
find differences between chronic pain sufferers and healthy normals.
Resting state fMRI scans of chronic pain sufferers may be sufficiently different from scans
of normal subjects to allow a high level of classification accuracy of whether subjects have
chronic pain. In addition, investigators will utilize DTI and a brief activation state using
pain rumination to assess whether investigators can reliably find differences between
chronic pain sufferers and healthy normals. The analysis will use pattern recognition
methods in a leave N out cross validation design. The success of the classifications will be
the mean of all the validation runs.
of normal subjects to allow a high level of classification accuracy of whether subjects have
chronic pain. In addition, investigators will utilize DTI and a brief activation state using
pain rumination to assess whether investigators can reliably find differences between
chronic pain sufferers and healthy normals. The analysis will use pattern recognition
methods in a leave N out cross validation design. The success of the classifications will be
the mean of all the validation runs.
Inclusion Criteria:
Daily Pain lasting for more than 6 months. Ages eligible for study are between 20 and 70
years.
Exclusion Criteria:
Adults unable to consent Children, teenagers Pregnant women Prisoners Subjects who do not
know English MRI exclusion criteria
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