fMRI May Help Predict Antidepressant Treatment Response

January 30, 2017

Functional MRI may help determine which patients with depression will respond to antidepressant therapy.

Functional MRI brain images may help predict positive responses to antidepressant therapy, according to a study published in Brain.

Researchers from the University of Illinois at Chicago and the University of Michigan in Ann Arbor sought to identify communication in the brain using neural and performance predictors during a cognitive control task to predict treatment response.

Forty-nine subjects participated in the open-label study. All had major depressive disorder. Thirty-six of the patients completed treatment, had useable data, and were included in most data analyses. Twenty-two patients included in the data analysis sample received treatment with escitalopram and 14 received duloxetine, all for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict percent reduction in Hamilton Depression Rating Scale scores after treatment. The subjects were instructed to watch the letters X, Y, and Z flash across a screen while they underwent the fMRI scan, and they were asked to press a button every time they saw a letter but not to press the button a second time if the same letter repeated. Follow up at 10 weeks included surveys and interviews to determine the extent of their symptoms.[[{"type":"media","view_mode":"media_crop","fid":"56147","attributes":{"alt":"Scott Langenecker, PhD","class":"media-image media-image-right","id":"media_crop_5194855587911","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"7055","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"height: 203px; width: 170px; border-width: 0px; border-style: solid; margin: 1px; float: right;","title":"Scott Langenecker, PhD","typeof":"foaf:Image"}}]]

The researchers found that patients whose brain activity was stronger in the error detection network or the interference processing network were found less likely to experience an eventual reduction of their depressive symptoms on medication. In addition, those who made more errors during the cognitive task were more likely to respond to antidepressant 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," corresponding author Scott Langenecker, PhD, an associate professor of psychology and psychiatry at UIC, said in a release.

"This is an important step toward individualized medicine for depression treatment. 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," Langenecker said.