TY - JOUR
T1 - Towards precision medicine in psychosis
T2 - Benefits and challenges of multimodal multicenter studies - PSYSCAN: Translating neuroimaging findings from research into clinical practice
AU - the PSYSCAN Consortium
AU - Tognin, Stefania
AU - Van Hell, Hendrika H.
AU - Merritt, Kate
AU - Winter-Van Rossum, Inge
AU - Bossong, Matthijs G.
AU - Kempton, Matthew J.
AU - Modinos, Gemma
AU - Fusar-Poli, Paolo
AU - Mechelli, Andrea
AU - Dazzan, Paola
AU - Maat, Arija
AU - De Haan, Lieuwe
AU - Crespo-Facorro, Benedicto
AU - Glenthøj, Birte
AU - Lawrie, Stephen M.
AU - McDonald, Colm
AU - Gruber, Oliver
AU - Van Amelsvoort, Therese
AU - Arango, Celso
AU - Kircher, Tilo
AU - Nelson, Barnaby
AU - Galderisi, Silvana
AU - Bressan, Rodrigo
AU - Kwon, Jun Soo
AU - Weiser, Mark
AU - Mizrahi, Romina
AU - Sachs, Gabriele
AU - Maatz, Anke
AU - Kahn, René
AU - McGuire, Phillip
AU - Gifford, George
AU - Petros, Natalia
AU - Antoniades, Mathilde
AU - De Micheli, Andrea
AU - Vieira, Sandra
AU - Spencer, Tom J.
AU - Scarpazza, Cristina
AU - Hird, Emily
AU - Van Hell, Erika
AU - Winter, Inge
AU - Cahn, Wiepke
AU - Schnack, Hugo
AU - Siegmann, DIeuwke
AU - Barkhof, Jana
AU - Hendriks, Lotte
AU - De Wit, Iris
AU - Tordesillas-Gutierrez, DIana
AU - Setien-Suero, Esther
AU - Ayesa-Arriola, Rosa
AU - Lee, Tae Young
N1 - Publisher Copyright:
© The Author(s) 2019.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - 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.
AB - 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.
KW - clinical high risk of psychosis
KW - first episode of psychosis
KW - machine learning
KW - MRI
KW - neuroimaging
KW - prediction
KW - psychosis
KW - PSYSCAN
UR - http://www.scopus.com/inward/record.url?scp=85081165552&partnerID=8YFLogxK
U2 - 10.1093/schbul/sbz067
DO - 10.1093/schbul/sbz067
M3 - Article
C2 - 31424555
AN - SCOPUS:85081165552
SN - 0586-7614
VL - 46
SP - 432
EP - 441
JO - Schizophrenia Bulletin
JF - Schizophrenia Bulletin
IS - 2
ER -