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Feasibility of studying brain morphology in major depressive disorder with structural magnetic resonance imaging and clinical data from the electronic medical record: A pilot study
Abstract For certain research questions related to long-term outcomes or to rare disorders, designing prospective studies is impractical or prohibitively expensive. Such studies could instead utilize clinical and magnetic resonance imaging data (MRI) collected as part of routine clinical care, store...
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Published in: | Psychiatry research. Neuroimaging 2013-03, Vol.211 (3), p.202-213 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Abstract For certain research questions related to long-term outcomes or to rare disorders, designing prospective studies is impractical or prohibitively expensive. Such studies could instead utilize clinical and magnetic resonance imaging data (MRI) collected as part of routine clinical care, stored in the electronic medical record (EMR). Using major depressive disorder (MDD) as a disease model, we examined the feasibility of studying brain morphology and associations with remission using clinical and MRI data exclusively drawn from the EMR. Advanced automated tools were used to select MDD patients and controls from the EMR who had brain MRI data, but no diagnosed brain pathology. MDD patients were further assessed for remission status by review of clinical charts. Twenty MDD patients (eight full-remitters, six partial-remitters, and six non-remitters), and 15 healthy control subjects met all study criteria for advanced morphometric analyses. Compared to controls, MDD patients had significantly smaller right rostral-anterior cingulate volume, and level of non-remission was associated with smaller left hippocampus and left rostral-middle frontal gyrus volume. The use of EMR data for psychiatric research may provide a timely and cost-effective approach with the potential to generate large study samples reflective of the real population with the illness studied. |
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ISSN: | 0925-4927 1872-7506 |
DOI: | 10.1016/j.pscychresns.2012.07.007 |