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MRI scans could predict major depressive disorder risk

Xinhua, October 8, 2015 Adjust font size:

Researchers have discovered that functional magnetic resonance imaging (fMRI) could be used to predict which patients with recovered major depressive disorder are most likely to have more depressive episodes, according to a study released Wednesday by King's College London.

With the help of fMRI, researchers were able to predict which patients would go on to have another depressive episode and which would remain in remission with an overall accuracy of 75 percent.

To test the new approach, researchers from King's College London and the University of Manchester, gave 64 patients, who were in remission from major depressive disorder and not on prescribed medication, fMRI scans to look for atypical connections in the brain.

During the scans, the participants were asked to imagine acting badly towards their best friends and they experienced self-blaming emotions such as guilt. Over the following 14 months they were seen regularly and monitored for symptoms. At the end of the study, 37 remained in remission while 27 had had a recurrence of their depression.

In the fMRI scans of those who went on to have another episode of depression, there was a higher connectedness between two parts of the brain that have been previously linked to guilt: the anterior temporal lobe and the subgenual region, according to the study.

Researchers said people who remained in remission over the following year did not have this increased interconnectedness. The researchers also tested the approach on a control group of 39 people with no personal or family history of major depressive disorder, finding that they also did not have the increased interconnectedness.

Based on the information, researchers could make a relatively accurate prediction of the mental disease.

"Before this approach can be rolled out and used in the clinic, we need to test it out in an independent group of patients and improve it, so that its accuracy reaches 80 percent," said Dr Roland Zahn, the lead researcher from King's College London.

If future studies could reach this mark, then this approach would be vitally important as "there are currently no accurate ways to predict those who will have a recurrence following recovery", he said. Endit