Pre-treatment amygdala volume predicts electroconvulsive therapy response
Publication year
2014Source
Frontiers in Psychiatry, 5, (2014), article 169ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
Psychiatry
Donders Centre for Cognitive Neuroimaging
Journal title
Frontiers in Psychiatry
Volume
vol. 5
Subject
130 000 Cognitive Neurology & Memory; Radboudumc 13: Stress-related disorders DCMN: Donders Center for Medical NeuroscienceAbstract
BACKGROUND: Electroconvulsive therapy (ECT) is an effective treatment for patients with severe depression. Knowledge on factors predicting therapeutic response may help to identify patients who will benefit most from the intervention. Based on the neuroplasticity hypothesis, volumes of the amygdala and hippocampus are possible candidates for predicting treatment outcome. Therefore, this prospective cohort study examines the predictive value of amygdala and hippocampal volumes for the effectiveness of ECT. METHODS: Prior to ECT, 53 severely unipolar depressed patients [mean age 57 +/- 14 years; 40% (n = 21) male] received structural magnetic resonance imaging (MRI) at 1.5 T. Normalized amygdala and hippocampal volumes were calculated based on automatic segmentation by FreeSurfer (FS). Regression analyses were used to test if the normalized volumes could predict the response to a course of ECT based on the Montgomery-Asberg Depression Rating Scale (MADRS) scores. RESULTS: A larger amygdala volume independently and significantly predicted a lower post-ECT MADRS score (beta = -0.347, P = 0.013). The left amygdala volume had greater predictive value for treatment outcome relative to the right amygdala volume. Hippocampal volume had no independent predictive value. CONCLUSION: A larger pre-treatment amygdala volume predicted more effective ECT, independent of other known predictors. Almost all patients continued their medication during the study, which might have influenced the course of treatment in ways that were not taken into account.
This item appears in the following Collection(s)
- Academic publications [238430]
- Donders Centre for Cognitive Neuroimaging [3824]
- Electronic publications [122512]
- Faculty of Medical Sciences [90359]
- Open Access publications [97507]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.