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Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges.
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.
Afiliação
  • Bano W; FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.
  • Pulli E; Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland.
  • Cantonas L; Centre of Excellence in Learning Dynamics and Intervention Research (InterLearn), University of Jyväskylä and University of Turku, Finland.
  • Sorsa A; FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.
  • Hämäläinen J; Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland.
  • Karlsson H; Centre of Excellence in Learning Dynamics and Intervention Research (InterLearn), University of Jyväskylä and University of Turku, Finland.
  • Karlsson L; Department of Psychology and Education, University of Jyväskylä, Finland.
  • Saukko E; Department of Psychology and Education, University of Jyväskylä, Finland.
  • Sainio T; Centre of Excellence in Learning Dynamics and Intervention Research (InterLearn), University of Jyväskylä and University of Turku, Finland.
  • Peuna A; Department of Psychology and Education, University of Jyväskylä, Finland.
  • Korja R; FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland.
  • Aro M; Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland.
  • Leppänen PHT; Centre of Excellence in Learning Dynamics and Intervention Research (InterLearn), University of Jyväskylä and University of Turku, Finland.
  • Tuulari JJ; Department of Clinical Medicine, Unit of Public Health, University of Turku, Finland.
  • Merisaari H; Department of Child Psychiatry, Turku University Hospital, Turku, Finland.
MethodsX ; 12: 102789, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38966716
ABSTRACT
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 containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article