Dataset Information

Neuroimaging in the effect of transcranial magnetic stimulation therapy for patient with depression: a protocol for a coordinate-based meta-analysis

ABSTRACT: Introduction As a prevalent psychiatric disease, depression is a life-threatening mental disorder that may cause work disability and premature death. Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation procedure, which has been reported to have a significant effect on antidepressant treatment in recent years. However, the parameters of TMS for depression that can produce the best clinical benefits remain unknown. In the present study, we will evaluate the effect of TMS treatment for depression from the perspective of functional neuroimaging by performing a meta-analysis based on included studies. Methods and analysis Two independent reviewers will search published studies in the following five databases: PubMed, Web of Science, Embase, China National Knowledge Infrastructure and WANGFANG DATA from inception to 1 June 2020. Then we will select studies according to predesigned inclusion and exclusion criteria. After extracting data from included studies, activation likelihood estimation will be applied to data synthesis. Any disagreement will be checked by the third reviewer who will also make the final decision. Ethics and dissemination This work does not require ethics approval as it will be based on published studies. This review will be published in peer-reviewed journals. PROSPERO registration number CRD42020165436.

SUBMITTER: Deng Y

PROVIDER: S-EPMC7537428 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5-8?weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level-dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre-treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85-95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p?<?.001). These preliminary findings suggest that therapeutic outcome to DLPFC-rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).

Dataset Information

Neuroimaging in the effect of transcranial magnetic stimulation therapy for patient with depression: a protocol for a coordinate-based meta-analysis

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure