NEUROTREND: Neuro fMRI biomarkers for treatment navigation in depression

Project: Research direct

Project Details

Description

Major depressive disorder (MDD), is a mental disorder characterized by at least two weeks of low mood that is present across most situations. Depression is the most prevalent neuropsychiatric disorder, and in 15-20% of cases becomes chronic. The costs of depression (directly and indirectly) amount to 3 billion euros in the Netherlands, with high costs and large impact on quality of life. Most of the costs are generated in the group of patients with chronic depression (about 30% of the patients). Furthermore, in that patient group the highest impact on quality of life is found. Current diagnostic tests are subjective and inaccurate. The diagnosis is based on the person's reported experiences and a mental status examination. There is no laboratory test for major depression. Objective and accurate biomarkers are therefore urgently needed to improve treatment at lower costs.
Research during the last decade identified MR-outcomes as potential powerful biomarkers (i.e. the connectome signatures in fMRI Lui et al., 2011). In our own work, connectivity changed as a consequence of neurostimulation (repetitive TMS) showing a functional reorganisation from a high clustered (dense connected) default mode brain network to a more steady state after neurostimulation only in responders.
The goal of our project is to further develop and validate MRI-based biomarkers for diagnosis and treatment stratification of depression. The project will be embedded in a close collaboration and colocation of researchers, and can leverage strongly on ongoing and future e/MTIC projects (such as the Medicaid project presented to the TKI HTSM). The focus of the project is on patient value and industrial valorization, and scientific excellence as well as industrial relevance are both guaranteed through the TU/e-Philips unique way of cooperating in which all project are jointly supervised by the university, the hospitals and industry.
The technology for diagnosis will land in decision support systems for diagnosis and treatment stratification and the selection of therapies.
Strong involvement of Philips, Hobo Heeze and hospitals ensure the essential embedding of the research in the application environments of the manufacturer and end users. Lastly, the project will ensure open access publishing of widely applicable methods.
Short titleTKI-HTSM/19.0008
StatusActive
Effective start/end date2/01/1830/09/24

Funded in part by

  • TKI-HTSM

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