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Published on: June 26, 2013
Can neuroimaging help us to understand and classify somatoform disorders? A systematic and critical review
Michael Browning1, Paul Fletcher, Michael Sharpe
1Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford OX3 7JX, UK. michael.browning@psych.ox.ac.uk
Objective:
Debate about the nature of somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of Diagnostic and Statistical Manual of Mental Disorders and International Statistical Classification of Diseases and Related Health Problems diagnostic classifications. In the current paper, we review systematically the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders?
Methods:
Studies reporting neuroimaging findings in patients with a somatoform disorder or a functional somatic syndrome (such as fibromyalgia) were found using Pubmed, PsycINFO, and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review.
Results:
A relatively mature literature on symptoms of pain and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared with nonclinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in gray matter density; however, methodological considerations restrict the interpretation of these findings.
Conclusions:
Whereas the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders, this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis, there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies.
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