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Abstract Background The German multicenter research consortium BipoLife aims to investigate the mechanisms underlying bipolar disorders. It focuses in particular on people at high risk of developing the disorder and young patients in the early stages of the disease. Functional and structural magnetic resonance imaging (MRI) data was collected in all participating centers. The collection of neuroimaging data in a longitudinal, multicenter study requires the implementation of a comprehensive quality assurance (QA) protocol. Here, we outline this protocol and illustrate its application within the BipoLife consortium. Methods The QA protocol consisted of (1) a training of participating research staff, (2) regular phantom measurements to evaluate the MR scanner performance and its temporal stability across the course of the study, and (3) the assessment of the quality of human MRI data by evaluating a variety of image metrics (e.g., signal-to-noise ratio, ghosting level). In this article, we will provide an overview on these QA procedures and show exemplarily the influence of its application on the results of standard neuroimaging analysis pipelines. Discussion The QA protocol helped to characterize the various MR scanners, to record their performance over the course of the study and to detect possible malfunctions at an early stage. It also assessed the quality of the human MRI data systematically to characterize its influence on various analyses. Furthermore, by setting up and publishing this protocol, we define standards that must be considered when analyzing data from the BipoLife consortium. It further promotes a systematic evaluation of data quality and a definition of subject inclusion criteria. In the long term, it will help to increase the chance of achieving clinically relevant results.

Abstract Background Bipolar disorder is one of the most severe mental disorders. Its chronic course is associated with high rates of morbidity and mortality, a high risk of suicide and poor social and occupational outcomes. Despite the great advances over the last decades in understanding mental disorders, the mechanisms underlying bipolar disorder at the neural network level still remain elusive. This has severe consequences for clinical practice, for instance by inadequate diagnoses or delayed treatments. The German research consortium BipoLife aims to shed light on the mechanisms underlying bipolar disorders. It was established in 2015 and incorporates ten university hospitals across Germany. Its research projects focus in particular on individuals at high risk of bipolar disorder, young patients in the early stages of the disease and patients with an unstable highly relapsing course and/or with acute suicidal ideation. Methods Functional and structural magnetic resonance imaging (MRI) data was acquired across nine sites within three different studies. Obtaining neuroimaging data in a multicenter setting requires among others the harmonization of the acquisition protocol, the standardization of paradigms and the implementation of regular quality control procedures. The present article outlines the MRI imaging protocols, the acquisition parameters, the imaging paradigms, the neuroimaging quality assessment procedures and the number of recruited subjects. Discussion The careful implementation of a MRI study protocol as well as the adherence to well-defined quality assessment procedures is one key benchmark in the evaluation of the overall quality of large-scale multicenter imaging studies. This article contributes to the BipoLife project by outlining the rationale and the design of the MRI study protocol. It helps to set the necessary standards for follow-up analyses and provides the technical details for an in-depth understanding of follow-up publications.

Abstract Background Bipolar disorders (BD) belong to the most severe mental disorders, characterized by an early onset and recurrent, severe episodes or a chronic course with poor psychosocial functioning in a proportion of patients. Many patients with BD experience substantial symptomatology months or even years before full BD manifestation. Adequate diagnosis and treatment is often delayed, which is associated with a worse outcome. This study aims to prospectively evaluate and improve early recognition and intervention strategies for persons at-risk for BD. Methods Early-BipoLife is a prospective-longitudinal cohort study of 1419 participants (aged 15–35 years) with at least five waves of assessment over a period of at least 2 years (baseline, 6, 12, 18 and 24 months). A research consortium of ten university and teaching hospitals across Germany conducts this study. The following risk groups (RGs) were recruited: RG I: help-seeking youth and young adults consulting early recognition centres/facilities presenting ≥ 1 of the proposed risk factors for BD, RG II: in-/outpatients with unipolar depressive syndrome, and RG III: in-/outpatients with attention-deficit/hyperactivity disorder (ADHD). The reference cohort was selected from the German representative IMAGEN cohort. Over the study period, the natural course of risk and resilience factors, early symptoms of BD and changes of symptom severity (including conversion to manifest BD) are observed. Psychometric properties of recently developed, structured instruments on potential risk factors for conversion to BD and subsyndromal symptomatology (Bipolar Prodrome Symptom Scale, Bipolar at-risk criteria, EPIbipolar) and biomarkers that potentially improve prediction are investigated. Moreover, actual treatment recommendations are monitored in the participating specialized services and compared to recently postulated clinical categorization and treatment guidance in the field of early BD. Discussion Findings from this study will contribute to an improved knowledge about the natural course of BD, from the onset of first noticeable symptoms (precursors) to fully developed BD, and about mechanisms of conversion from subthreshold to manifest BD. Moreover, these generated data will provide information for the development of evidence-based guidelines for early-targeted detection and preventive intervention for people at risk for BD.