A1 Refereed original research article in a scientific journal
Implementing ABCD study ® MRI sequences for multi-site cohort studies: practical guide to necessary steps, preprocessing methods, and challenges
Authors: Bano, Wajiha; Pulli, Elmo; Cantonas, Lucia; Sorsa, Aino; Hämäläinen, Jarmo; Karlsson, Hasse; Karlsson,
Linnea; Saukko, Ekaterina; Sainio, Teija; Peuna, Arttu; Korja, Riikka; Aro, Mikko; Leppänen, Paavo H.T.; Tuulari, Jetro J.; Merisaari, Harri
Publisher: Elsevier
Publication year: 2024
Journal: MethodsX
Journal name in source: MethodsX
Article number: 102789
Volume: 12
eISSN: 2215-0161
DOI: https://doi.org/10.1016/j.mex.2024.102789
Web address : https://doi.org/10.1016/j.mex.2024.102789
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/454701577
Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)® study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerized preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.
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Funding information in the publication:
The research was funded by The Centre of Excellence for Learning Dynamics and Intervention Research (InterLearn CoE) in the Academy of Finland's Center of Excellence Programme (2022-2029) (grants 346119, 346120, 346121).
