Abstract

In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures.

Original languageEnglish
Pages (from-to)432-441
Number of pages10
JournalSchizophrenia Bulletin
Volume46
Issue number2
DOIs
StatePublished - 1 Mar 2020

Funding

FundersFunder number
Seventh Framework Programme603196
Seventh Framework Programme

    Keywords

    • MRI
    • PSYSCAN
    • clinical high risk of psychosis
    • first episode of psychosis
    • machine learning
    • neuroimaging
    • prediction
    • psychosis

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