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fMRI imaging may predict patients' response to antidepressant therapy

by Lauren Dubinsky, Senior Reporter | January 26, 2017
Alzheimers/Neurology MRI
90 percent accurate
Medication that treats major depressive disorder takes eight to 12 weeks to work, and patients may not respond to the first drug prescribed. A new study published in the journal Brain, shows that fMRI imaging may help to predict a patient’s response to antidepressant therapy.

"This is an important step toward individualized medicine for depression treatment,” Scott Langenecker, associate professor at UIC, said in a statement. “Using cognitive tests and fMRI, we can identify who will respond best to antidepressant therapy and who may need other effective therapies that work through different mechanisms, like psychotherapy.”

Researchers at the University of Illinois at Chicago and University of Michigan recruited 36 adults with major depressive disorder who were not being treated with medications at the time. They had them undergo fMRI exams and fill out surveys regarding their depressive symptoms.
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During the fMRI exams, the patients watched the letters, ‘X,’ ‘Y’ and ‘Z,’ flash across a screen. They were instructed to press a button every time they saw a letter, but to not press the button a second time if the same letter repeated.

A unique analysis technique was used to identify the areas of the brain that were highly active when the patients made an error during the cognitive task. The error detection network activates when someone notices they’ve made a mistake and the interference processing network activates when deciding what information to focus on.

The researchers assigned 22 patients to take the selective serotonin reuptake inhibitor Effexor, and 14 were assigned to the serotonin-norepinephrine reuptake inhibitor Cymbalta. The patients completed surveys and interviews at the start of antidepressant therapy and 10 weeks later to determine if their symptoms had lessened.

The study revealed that patients with stronger brain activity in the error detection network or interference processing network were less likely to experience a reduction in depressive symptoms from medication. Alternatively, the patients who made more errors during the cognitive task were more likely to respond to the treatment.

"Using our model, we were able to predict with a very high degree of accuracy — in fact 90 percent — which patients would respond well to antidepressant treatment, and which would not," said Langenecker.

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