Researchers at the University of California at Los Angeles (UCLA) are launching a database of brain scans and other clinical information to help researchers better understand chronic-pain conditions.
The hub, which is being called the Pain and Interoception Imaging Network (PAIN), will be at the Gail and Gerald Oppenheimer Family Center for Neurobiology of Stress at UCLA. The university says it will be the first-ever standardized database for brain imaging associated with chronic pain, and already 14 institutions in North America and Europe are participating. The UCLA team has received a $300,000 grant from the National Institutes of Health for the imaging network.
"We are now recognizing that chronic pain is a brain disease, and if we want to treat it more effectively, we need to better understand and treat the mechanisms in the brain that are driving it," stated Emeran Mayer, M.D. a professor of medicine in the divisions of digestive diseases, physiology and psychiatry at the David Geffen School of Medicine at UCLA and executive director of the Gail and Gerald Oppenheimer Family Center for Neurobiology of Stress at UCLA.
Mayer, in a press release, adds that brain imaging is one of the “most promising technologies for breakthrough findings in chronic pain.” At this moment though, research is limited since most institutions can only support small studies on their own and lack access to large samples of patients. He also points to standardization of acquired data as an issue, which makes it difficult ot combine brain scans from multiple investigators that are obtained using different scanners, techniques and sets of clinical data.
With PAIN, researchers say they wish to include information from more than a thousand patients, including both adults and children. Along with the brain scans, researchers will also have access to clinical and biological information on patients, including symptom measures; psychosocial factors, gene expression, immune system information, data on bacteria in the intestines, and environmental data.
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