Relapse of depression following treatment is high. Biomarkers predictive of an individual's relapse risk could provide earlier opportunities for prevention. Since electroconvulsive therapy (ECT) elicits robust and rapidly acting antidepressant effects, but has a >50% relapse rate, ECT presents a valuable model for determining predictors of relapse-risk. Although previous studies have associated ECT-induced changes in brain morphometry with clinical response, longer-term outcomes have not been addressed. Using structural imaging data from 42 ECT-responsive patients obtained prior to and directly following an ECT treatment index series at two independent sites (UCLA: n = 17, age = 45.41±12.34 years; UNM: n = 25; age = 65.00±8.44), here we test relapse prediction within 6-months post-ECT. Random forests were used to predict subsequent relapse using singular and ratios of intra and inter-hemispheric structural imaging measures and clinical variables from pre-, post-, and pre-to-post ECT. Relapse risk was determined as a function of feature variation. Relapse was well-predicted both within site and when cohorts were pooled where top-performing models yielded balanced accuracies of 71-78%. Top predictors included cingulate isthmus asymmetry, pallidal asymmetry, the ratio of the paracentral to precentral cortical thickness and the ratio of lateral occipital to pericalcarine cortical thickness. Pooling cohorts and predicting relapse from post-treatment measures provided the best classification performances. However, classifiers trained on each age-disparate cohort were less informative for prediction in the held-out cohort. Post-treatment structural neuroimaging measures and the ratios of connected regions commonly implicated in depression pathophysiology are informative of relapse risk. Structural imaging measures may have utility for devising more personalized preventative medicine approaches.

Background

Ketamine elicits an acute antidepressant effect in patients with major depressive disorder (MDD). Here, we used diffusion imaging to explore whether regional differences in white matter microstructure prior to treatment may predict clinical response 24h following ketamine infusion in 10 MDD patients.

Methods

FSL's Tract-Based Spatial Statistics (TBSS) established voxel-level differences in fractional anisotropy (FA) between responders (patients showing >50% improvement in symptoms 24h post-infusion) and non-responders in major white matter pathways. Follow-up regions-of-interest (ROI) analyses examined differences in FA and radial (RD), axial (AD) and mean diffusivity (MD) between responders and non-responders and 15 age- and sex-matched controls, with groups compared pairwise.

Results

Whole brain TBSS (p<0.05, corrected) and confirmatory tract-based regions-of-interest analyses showed larger FA values in the cingulum and forceps minor in responders compared to non-responders; complementary decreases in RD occurred in the cingulum (p<0.05). Only non-responders differed from controls showing decreased FA in the forceps minor, increased RD in the cingulum and forceps minor, and increased MD in the forceps minor (p<0.05).

Limitations

Non-responders showed an earlier age of onset and longer current depressive episode than responders. Though these factors did not interact with diffusion metrics, results may be impacted by the limited sample size.

Conclusions

Though findings are considered preliminary, significant differences in FA, RD and MD shown in non-responders compared to responders and controls in fronto-limbic and ventral striatal pathways suggest that the structural architecture of specific functional networks mediating emotion may predict ketamine response in MDD.

Background

Electroconvulsive therapy (ECT) elicits a rapid and robust clinical response in patients with refractory depression. Neuroimaging measurements of structural plasticity relating to and predictive of ECT response may point to the mechanisms underlying rapid antidepressant effects and establish biomarkers to inform other treatments. Here, we determine the effects of diagnosis and of ECT on global and local variations of hippocampal and amygdala structures in major depression and predictors of ECT-related clinical response.

Methods

Longitudinal changes in hippocampal and amygdala structures were examined in patients with major depression (N = 43, scanned three times: prior to ECT, after the second ECT session, and within 1 week of completing the ECT treatment series), referred for ECT as part of their standard clinical care. Cross-sectional comparisons with demographically similar controls (N = 32, scanned twice) established effects of diagnosis.

Results

Patients showed smaller hippocampal volumes than controls at baseline (p < .04). Both the hippocampal and the amygdala volumes increased with ECT (p < .001) and in relation to symptom improvement (p < .01). Hippocampal volume at baseline predicted subsequent clinical response (p < .05). Shape analysis revealed pronounced morphometric changes in the anterior hippocampus and basolateral and centromedial amygdala. All structural measurements remained stable across time in controls.

Conclusions

ECT-induced neuroplasticity in the hippocampus and amygdala relates to improved clinical response and is pronounced in regions with prominent connections to ventromedial prefrontal cortex and other limbic structures. Smaller hippocampal volumes at baseline predict a more robust clinical response. Neurotrophic processes including neurogenesis shown in preclinical studies may underlie these structural changes.

Objective

Symptom heterogeneity in major depressive disorder obscures diagnostic and treatment-responsive biomarker identification. Whether symptom constellations are differentially changed by electroconvulsive therapy (ECT) remains unknown. We investigate the clustering of depressive symptoms over the ECT index and whether ECT differentially influences symptom clusters.

Methods

The 17-item Hamilton Depression Rating Scale (HDRS-17) was collected from 111 patients with current depressive episode before and after ECT from 4 independent participating sites of the Global ECT-MRI Research Collaboration. Exploratory factor analysis of HDRS-17 items pre- and post-ECT treatment identified depressive symptom dimensions before and after ECT. A 2-way analysis of covariance was used to determine whether baseline symptom clusters were differentially changed by ECT between treatment remitters (defined as patients with posttreatment HDRS-17 total score ≤8) and nonremitters while controlling for pulse width, titration method, concurrent antidepressant treatment, use of benzodiazepine, and demographic variables.

Results

A 3-factor solution grouped pretreatment HDRS-17 items into core mood/anhedonia, somatic, and insomnia dimensions. A 2-factor solution best described the symptoms at posttreatment despite poorer separation of items. Among remitters, core mood/anhedonia symptoms were significantly more reduced than somatic and insomnia dimensions. No differences in symptom dimension trajectories were observed among nonremitting patients.

Conclusions

Electroconvulsive therapy targets the underlying source of depressive symptomatology and may confer differential degrees of improvement in certain core depressive symptoms. Our findings of differential trajectories of symptom clusters over the ECT index might help related predictive biomarker studies to refine their approaches by identifying predictors of change along each latent symptom dimension.