Literature DB >> 9430506

Brain structure and function and the outcomes of treatment for depression.

A F Leuchter1, I A Cook, S H Uijtdehaage, J Dunkin, R B Lufkin, C Anderson-Hanley, M Abrams, S Rosenberg-Thompson, R O'Hara, S L Simon, S Osato, A Babaie.   

Abstract

BACKGROUND: Depressed patients have a variety of brain structural alterations, the most common being atrophy and deep white-matter lesions. Alterations in brain function also are common, particularly regional decreases in cerebral metabolism and perfusion.
METHOD: We review here the evidence that alterations in brain structure and function may explain some of the heterogeneity in outcomes of depression. We also report initial results suggesting that measurement of brain structure and function may help to predict outcomes of treatment for depression. Brain structure was examined using three-dimensional reconstruction and volumetric analysis of magnetic resonance imaging (MRI) scans. Brain function was examined using quantitative electroencephalography (QEEG), performed at baseline and serially during the course of treatment. QEEG measures included coherence (a measure of synchronized activity between brain regions) and cordance (a measure strongly associated with regional cerebral perfusion).
RESULTS: Depressed patients have been reported to have larger volumes of white-matter lesions than controls. We have found that some types of white-matter lesions are associated with lower coherence and that subjects with low coherence had significantly poorer outcomes of treatment for depression at 2-year follow-up. Depressed subjects had low cordance at baseline, which decreased further during the course of effective treatment. Subjects who did not improve had little or no change in cordance. Changes in cordance were detected prior to the onset of clinical response, with decreases seen as early as 48 hours after the initiation of treatment in subjects who showed eventual response.
CONCLUSION: These preliminary results suggest that functional imaging using QEEG may be useful for assessing, and possibly predicting, outcomes of treatment for depression.

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Year:  1997        PMID: 9430506

Source DB:  PubMed          Journal:  J Clin Psychiatry        ISSN: 0160-6689            Impact factor:   4.384


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