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Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

ABSTRACT: Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies.

SUBMITTER: Sun H

PROVIDER: S-EPMC7229344 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Sun Hailun H Jiang Rongtao R Qi Shile S Narr Katherine L KL Wade Benjamin Sc BS Upston Joel J Espinoza Randall R Jones Tom T Calhoun Vince D VD Abbott Christopher C CC Sui Jing J

NeuroImage. Clinical 20191106

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 tota ...[more]

PMID: 31735637

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Project description:Novel and non-routine tasks often require information processing and behavior to adapt from moment to moment depending on task requirements and current performance. This ability to adapt is an executive function that is referred to as cognitive control. Patients with moderate-to-severe traumatic brain injury (TBI) have been reported to exhibit impairments in cognitive control and functional magnetic resonance imaging (fMRI) has provided evidence for TBI-related alterations in brain activation using various fMRI cognitive control paradigms. There is some support for greater and more extensive cognitive control-related brain activation in patients with moderate-to-severe TBI, relative to comparison subjects without TBI. In addition, some studies have reported a correlation between these activation increases and measures of injury severity. Explanations that have been proposed for increased activation within structures that are thought to be directly involved in cognitive control, as well as the extension of this over-activation into other brain structures, have included compensatory mechanisms, increased demand upon normal processes required to maintain adequate performance, less efficient utilization of neural resources, and greater vulnerability to cognitive fatigue. Recent findings are also consistent with the possibility that activation increases within some structures, such as the posterior cingulate gyrus, may reflect a failure to deactivate components of the default mode network (DMN) and that some cognitive control impairment may result from ineffective coordination between the DMN and components of the salience network. Functional neuroimaging studies examining cognitive control-related activation following mild TBI (mTBI) have yielded more variable results, with reports of increases, decreases, and no significant change. These discrepancies may reflect differences among the various mTBI samples under study, recovery of function in some patients, different task characteristics, and the presence of comorbid conditions such as depression and posttraumatic stress disorder that also alter brain activation. There may be mTBI populations with activation changes that overlap with those found following more severe injuries, including symptomatic mTBI patients and those with acute injuries, but future research to address such dysfunction will require well-defined samples with adequate controls for injury characteristics, comorbid disorders, and severity of post-concussive symptoms.

Dataset Information

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Publications

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

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