Mathematical Tool Helps Predict the Occurrence of Migraines in Concussion Patients
By MedImaging International staff writers Posted on 03 Feb 2016 |
Researchers have developed a mathematical tool to help find which concussion patients are most likely to suffer migraines.
The study results were published online in the journal Radiology. Patients with concussion injuries commonly suffer from post-traumatic migraine headaches. To investigate the relationship between headaches and concussion-related damage to the brain, researchers normally use a Magnetic Resonance Imaging (MRI) technique called Diffusion Tensor Imaging (DTI). Researchers create histograms of the whole brain, and then a mean Fractional Anistropy (FA). There are shortcomings with the FA technique however.
Instead of using the FA technique, the researchers analyzed the MRI scan results using Shannon entropy, an information theory model that that reveals areas of entropy, in the brain. The researchers then assessed the performance of Shannon entropy for use as a diagnostic tool for concussion patients with and without post-traumatic migraines. The study included 74 concussion patients – 57 with post-traumatic migraines and 17 without, 22 healthy control patients, and 20 control patients with migraine headaches. Mean FA and Shannon entropy results were calculated from the total brain FA histograms and compared between concussion patients and the control patients, and between those patients with, and those without post-traumatic migraine.
The results showed that using Shannon entropy analysis of FA histograms was more successful than mean FA as a diagnostic test to differentiate between concussion patients and controls. In addition, Shannon entropy was better in determining which concussion patients would develop post-traumatic migraines. The results also suggested that Shannon entropy could provide a reproducible biomarker that can be calculated automatically and can help triage patients after initial injury, and predict which patients are more likely to have severe symptoms.
Study author Lea M. Alhilali, MD, from the University of Pittsburgh Medical Center (UPMC; Pittsburgh, PA, USA), said, “Mean FA represents an average. If someone has a higher FA to begin with and they lose white matter integrity from trauma, they still might average out to have a normal mean FA. A healthy brain has high entropy, but people with injuries to the white matter from trauma may lose some of that complexity and have less entropy. This approach requires just one histogram for the entire brain. If it continues to show promise, then it could be added to the regular brain MRI as part of the study. Additional research is needed to study other potential applications of Shannon entropy, such as predicting future cognitive performance in concussion patients.”
Related Links:
UPMC
The study results were published online in the journal Radiology. Patients with concussion injuries commonly suffer from post-traumatic migraine headaches. To investigate the relationship between headaches and concussion-related damage to the brain, researchers normally use a Magnetic Resonance Imaging (MRI) technique called Diffusion Tensor Imaging (DTI). Researchers create histograms of the whole brain, and then a mean Fractional Anistropy (FA). There are shortcomings with the FA technique however.
Instead of using the FA technique, the researchers analyzed the MRI scan results using Shannon entropy, an information theory model that that reveals areas of entropy, in the brain. The researchers then assessed the performance of Shannon entropy for use as a diagnostic tool for concussion patients with and without post-traumatic migraines. The study included 74 concussion patients – 57 with post-traumatic migraines and 17 without, 22 healthy control patients, and 20 control patients with migraine headaches. Mean FA and Shannon entropy results were calculated from the total brain FA histograms and compared between concussion patients and the control patients, and between those patients with, and those without post-traumatic migraine.
The results showed that using Shannon entropy analysis of FA histograms was more successful than mean FA as a diagnostic test to differentiate between concussion patients and controls. In addition, Shannon entropy was better in determining which concussion patients would develop post-traumatic migraines. The results also suggested that Shannon entropy could provide a reproducible biomarker that can be calculated automatically and can help triage patients after initial injury, and predict which patients are more likely to have severe symptoms.
Study author Lea M. Alhilali, MD, from the University of Pittsburgh Medical Center (UPMC; Pittsburgh, PA, USA), said, “Mean FA represents an average. If someone has a higher FA to begin with and they lose white matter integrity from trauma, they still might average out to have a normal mean FA. A healthy brain has high entropy, but people with injuries to the white matter from trauma may lose some of that complexity and have less entropy. This approach requires just one histogram for the entire brain. If it continues to show promise, then it could be added to the regular brain MRI as part of the study. Additional research is needed to study other potential applications of Shannon entropy, such as predicting future cognitive performance in concussion patients.”
Related Links:
UPMC
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