WP1 Central infrastructure (Leader: CIMH / E Schwarz)
WP2 Diagnostic markers (Leader: RUNMC / B Franke)
WP3 Predictive markers (Leader: UNIBA / A Bertolini)
WP4 Pre-symptomatic and early diagnosis (Leader: KCL / G Schumann)
WP5 Clinical translation (Leader: BI / R Goebel)
WP6 Ethics (Leader: CIMH / M Rietschel)
WP7 Dissemination (Leader: CIMH / A Meyer-Lindenberg)
WP8 Project management (Leader: CIMH / A Meyer-Lindenberg)
WP1 Central infrastructure (Leader: CIMH / E Schwarz)
WP 1 aims at the creation of an extensive database of neuroimaging data linked to relevant biological and clinical markers. IMAGEMEND will assemble a database containing already available data on a total of 12667 subjects including 1493 schizophrenia patients, 1184 patients with bipolar disorder, 400 individuals affected by ADHD and 8554 healthy controls. For the large majority of cases and controls, neuroimaging, genetic and clinical data are already ascertained. In addition, data on 1036 relatives of the aforementioned diagnostic groups and longitudinal data on 1055 subjects will be available. IMAGEMEND project funding will primarily go towards expansion of this database to complement missing imaging, genetic and environmental risk data to allow extensive integrative analyses. Additionally, we will perform clinical and imaging follow-up measurements on a significant subset of patients for predictive and other longitudinal analyses. For each work package, based on the integrative analyses, we will deliver both optimal neuroimaging-based and optimal combined (i.e. adding genetic, clinical and environmental identifiers to the imaging data) classifiers and decision rules.
WP2 Diagnostic markers (Leader: RUNMC / B Franke)
WP2 works on the identification of neuroimaging and multi-modal markers (combining imaging, genetics and environmental risk factors) to facilitate case-control and differential diagnosis between schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder (ADHD) and healthy controls. The integration of genetic data is expected to meaningfully stratify patient populations and lead to classifiers with improved accuracy. Similarly, we anticipate that classifier performance will critically depend on the incorporation of environmental risk factors such as urbanicity and stressful life events. A second major aim of this WP is the identification of trans-diagnostic, neuroimaging and multi-modal disease markers, which index illness-associated biological processes beyond current categorical disease entities.
WP3 Predictive markers (Leader: UNIBA / A Bertolini)
WP3 aims to identify neuroimaging and multi-modal markers linked to response, relapse and side-effect development in naturalistic, large-scale patient populations with follow-up data. Specifically, for 1855 subjects who are part of the IMAGEMEND database, neuroimaging and clinical follow-up data will be provided by project partners. IMAGEMEND funding will go primarily towards extending these follow-up data to allow extensive analysis of predictive markers and their longitudinal change.
WP4 Pre-symptomatic and early diagnosis (Leader: KCL / G Schumann)
WP4 works on the translation of diagnostic and predictive marker panels to the pre-symptomatic and high-risk stage. This work package will investigate marker signatures associated with illness risk in large-scale population based samples. Specifically, for 4500 of such IMAGEMEND probands, symptom severity scores on anxiety, affective and cognitive function, ADHD symptoms or other measures of psychopathology are already available. We will also investigate multi-modal markers of remission and persistence of ADHD in adults.
WP5 Clinical translation (Leader: BI / R Goebel)
WP5 will utilize IMAGEMEND results towards development of automated, clinical tests to aid in diagnosis and treatment selection for psychiatric disorders. Besides performance optimization, specific aims of this work-package are the evaluation of classifier utility regarding measurement stability, robustness, and cost-effectiveness, both for purely imaging-based and combined optimal markers. In addition, clinical real-time fMRI software will be developed to enable the direct imaging-based modification of disease relevant neural circuits in an integrated neurofeedback system. With this, IMAGEMEND will create new products that use, for the first time, clinical MRI scanners for the diagnosis and for the treatment of mental illness, providing a new treatment modality, in addition to the currently available pharmacotherapy and psychotherapy.
WP6 Ethics (Leader: CIMH / M Rietschel)
WP6 will address ethical concerns associated with the development and application of novel predictive biomarkers for mental illness. Additionally, we will assess attitudes and ethical views of patients, relatives, health care professionals, and the general population towards diagnostic and predictive testing and ensure that all ethical implications are appropriately addressed throughout the IMAGMEND project.
WP7 Dissemination (Leader: CIMH / A Meyer-Lindenberg)
WP7 will increase the visibility of IMAGEMEND by reaching out to the scientific community, industry, patient organisations and other interested or potential stakeholders. A communication plan will be implemented. IMAGEMEND findings will be disseminated to the public through high-impact, international research publications, conferences, articles in the laymen press as well as through development of commercially available software for clinical application of decision tools developed during IMAGEMEND.
WP8 Project management (Leader: CIMH / A Meyer-Lindenberg)
Effective project management is a central element of successful research. This particularly applies to large research projects entailing a substantial amount of administrative work. The management WP makes sure that the project achieves its objectives and delivers its milestones and deliverables in time, within budget and with highest quality. It is furthermore concerned with communication, reporting, meeting organisation, financial management and intellectual property rights. The responsibility for project management lies primarily with the coordinator who is supported by concentris.
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