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Can brain imaging help to diagnose depression?

MARCH 13, 2008

Dr. Cynthia Fu of the Institute of Psychiatry, King’s College London is the lead author of a research report investigating how brain imaging can be applied to help diagnose depression. Dr Fu works in the Departments of Psychological Medicine and the SGDP Centre,

At the present time, the diagnosis of depression is based entirely on clinical signs and symptoms.  Unfortunately, there are no biological tests available for the diagnosis of depression (or other psychiatric disorders).  Patients with depression tend to be more critical about themselves, they tend to perceive things more negatively, and to be more pessimistic about events in their lives.  The researchers analysed the brain responses of patients with depression looking at faces with different emotional expressions.  The pattern of brain activity for facial processing was able to distinguish between patients with depression and healthy individuals.  Over 80% of the patients with depression were correctly identified as suffering from depression.  Similarly, over 80% of the healthy individuals were correctly classified as being healthy controls.  Moreover, as patients were seen on several occasions after they had begun antidepressant medication, the researchers also found that the pattern of brain response could predict which patients showed the greatest clinical improvement before they began treatment. 

The researchers emphasize that these are pilot data, but these findings may provide the first steps toward developing biological diagnostic markers and predictors of treatment response for depression – and more generally for other psychiatric disorders.  The paper “Pattern Classification of Sad Facial Processing: Toward the Development of Neurobiological Markers in Depression” has been published on line by the journal Biological Psychiatry and will be printed in the hard copy of the journal on 1 April, Volume 63, Issue 7, pp 656-662.

The authors are:  Cynthia H.Y. Fu, Janaina Mourao-Miranda, Sergi G. Costafreda, Akash Khanna, Andre F. Marquand, Steve C.R. Williams, and Michael J. Brammer.
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