Functional MRI Scan Better Predicts Patient Response to Antidepressants

Functional MRI (fMRI) scans could help predict whether a patient with depression will respond positively to antidepressant therapy.

In a study published in the journalBrain, investigators conducted fMRI scans on patients with major depressive disorder who would be starting antidepressant therapy.

The results of the study showed that patients who demonstrated more communication within 2 brain networks—–error detection network and interference processing network––while making a mistake during an assigned cognitive test were less likely to respond to antidepressant medication.

The error detection network engages when an individual becomes aware that he or she has made a mistake, while the interference processing network activates when deciding what information to focus on.

“We believe that increased cross-talk within these networks may reflect a propensity to ruminate on negative occurrences, such as a mistake, or a deficit in emotional regulation when faced with a mistake, and our medications may be less effective in helping these types of patients,” said first author Natania Crane.

Antidepressants take approximately 8 to 12 weeks before making a noticeable impact, and finding the right drug can take months, according to the authors. Furthermore, patients may be unresponsive or suffer adverse events that require them to switch medications.

By predicting a patient’s response to an antidepressant, it could help reduce the time it takes for them to feel better, said corresponding author Scott Langenecker. Additionally, this approach could reduce health care costs.

Prior studies have shown that fMRI can identify discrete areas of the brain that are hyperactive or underactive in patients with major depressive disorder. These findings suggest that neuroimaging could be useful in predicting a patient’s response to a particular therapy.

In the new study, investigators examined the brain activation patterns in participants performing cognitive-control tasks to see if they predicted response to drug treatment. Using a unique analysis technique, the investigators were able to determine which areas of the brain were highly active during the commission of errors on a cognitive task correlated with treatment response. Additionally, they examined how the strength of communication within the 2 brain networks predicted treatment response.

Included in the study were 36 adult patients with major depressive disorder who were being treated with antidepressants at the time of the study. The investigators performed fMRI scans on the study participants and required them to take surveys regarding their depressive symptoms.

Twenty-two participants received escitalopram (Effexor) and 14 patients received duloxetine (Cymbalta). The participants were instructed to watch the letters X, Y, and Z flash across a screen during an fMRI scan. Each time they saw a letter they were to press a button, but if the same letter was later repeated, they were asked to not press the button a second time.

Follow-up was during and after 10 weeks of antidepressant therapy. Surveys and interviews were conducted to determine whether the prescribed drugs had lessened their symptoms.

The results of the study showed that patients whose brain activity was stronger in the error detection network or the interference processing network, were less likely to experience an eventual reduction in their symptoms while on medication.

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

Additionally, the investigators found that participants who made errors during the cognitive task were more likely to respond to antidepressant therapy.

“This is an important step toward individualized medicine for depression treatment,” Langenecker concluded. “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.”