The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy. Academic Article uri icon

abstract

  • Major depression, currently the world's primary cause of disability, leads to profound personal suffering and increased risk of suicide. Unfortunately, the success of antidepressant treatment varies amongst individuals and can take weeks to months in those who respond. Electroconvulsive therapy (ECT), generally prescribed for the most severely depressed and when standard treatments fail, produces a more rapid response and remains the most effective intervention for severe depression. Exploring the neurobiological effects of ECT is thus an ideal approach to better understand the mechanisms of successful therapeutic response. Though several recent neuroimaging studies show structural and functional changes associated with ECT, not all brain changes associate with clinical outcome. Larger studies that can address individual differences in clinical and treatment parameters may better target biological factors relating to or predictive of ECT-related therapeutic response. We have thus formed the Global ECT-MRI Research Collaboration (GEMRIC) that aims to combine longitudinal neuroimaging as well as clinical, behavioral and other physiological data across multiple independent sites. Here, we summarize the ECT sample characteristics from currently participating sites, and the common data-repository and standardized image analysis pipeline developed for this initiative. This includes data harmonization across sites and MRI platforms, and a method for obtaining unbiased estimates of structural change based on longitudinal measurements with serial MRI scans. The optimized analysis pipeline, together with the large and heterogeneous combined GEMRIC dataset, will provide new opportunities to elucidate the mechanisms of ECT response and the factors mediating and predictive of clinical outcomes, which may ultimately lead to more effective personalized treatment approaches.

authors

publication date

  • January 1, 2017