Surface-based functional brain imaging analysis of major depressive disorder after electroconvulsive therapy.

BACKGROUND

The neural mechanisms underlying electroconvulsive therapy (ECT) in treating major depressive disorder (MDD) remain unclear. Previous neuroimaging studies have primarily employed voxel-based methods, which report only 35 % of the spatial localization of surface-based methods. This study aimed to investigate the antidepressant mechanisms of ECT using surface-based analyses.

METHOD: Longitudinal resting-state functional magnetic resonance imaging data were collected from 46 MDD patients undergoing ECT. Surface-based analyses were performed to investigate alterations in the amplitude of low-frequency fluctuations (ALFF) and functional connectivity. Correlation analyses explored relationships between ALFF, functional connectivity, and depressive symptoms. Support vector regression (SVR) was used to assess whether baseline functional connectivity could predict treatment response. A second independent cohort of 38 MDD patients was used for validation analyses.

RESULT: ECT increased ALFF in the left dorsolateral prefrontal cortex, left orbitofrontal cortex (OFC), and left inferior frontal cortex (IFC). Functional connectivity within the default mode network (DMN) and between the frontoparietal network and DMN also increased. Elevated IFC-OFC functional connectivity was strongly associated with depression remission, and baseline functional connectivity predicted symptom improvement. Similar changes in brain network functional connectivity were observed in the validation cohort, consistent with findings from the primary cohort.

CONCLUSION

This study advances understanding of the antidepressant effects of ECT through surface-based analysis and identifies potential predictive markers for assessing ECT efficacy in treating MDD.