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The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants.
Fitzgibbon, Sean P; Harrison, Samuel J; Jenkinson, Mark; Baxter, Luke; Robinson, Emma C; Bastiani, Matteo; Bozek, Jelena; Karolis, Vyacheslav; Cordero Grande, Lucilio; Price, Anthony N; Hughes, Emer; Makropoulos, Antonios; Passerat-Palmbach, Jonathan; Schuh, Andreas; Gao, Jianliang; Farahibozorg, Seyedeh-Rezvan; O'Muircheartaigh, Jonathan; Ciarrusta, Judit; O'Keeffe, Camilla; Brandon, Jakki; Arichi, Tomoki; Rueckert, Daniel; Hajnal, Joseph V; Edwards, A David; Smith, Stephen M; Duff, Eugene; Andersson, Jesper.
Afiliación
  • Fitzgibbon SP; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK. Electronic address: sean.fitzgibbon@ndcn.ox.ac.uk.
  • Harrison SJ; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Translational Neuromodeling Unit, University of Zurich & ETH Zurich, Switzerland.
  • Jenkinson M; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Baxter L; Paediatric Neuroimaging Group, Department of Paediatrics, University of Oxford, UK.
  • Robinson EC; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Bastiani M; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK; NIHR Biomedical Research Centre, University of Nottingham, UK.
  • Bozek J; Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia.
  • Karolis V; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Cordero Grande L; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Price AN; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Hughes E; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Makropoulos A; Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Passerat-Palmbach J; Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Schuh A; Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Gao J; Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Farahibozorg SR; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • O'Muircheartaigh J; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK; Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; MRC Centre for Neurodevelopmental Disorders, King's
  • Ciarrusta J; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • O'Keeffe C; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Brandon J; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Arichi T; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK; Department of Bioengineering, Imperial College London, UK; Children's Neurosciences, Evelina London Children's Hospital, King's Health Partners, London, UK.
  • Rueckert D; Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Hajnal JV; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Edwards AD; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
  • Smith SM; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Duff E; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Andersson J; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
Neuroimage ; 223: 117303, 2020 12.
Article en En | MEDLINE | ID: mdl-32866666
The developing Human Connectome Project (dHCP) aims to create a detailed 4-dimensional connectome of early life spanning 20-45 weeks post-menstrual age. This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance. The pipeline has been designed to specifically address the challenges that neonatal data presents including low and variable contrast and high levels of head motion. We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration approach, bespoke ICA-based denoising, and an automated QC framework. We assess these components on a large cohort of dHCP subjects and demonstrate that processing refinements integrated into the pipeline provide substantial reduction in movement related distortions, resulting in significant improvements in SNR, and detection of high quality RSNs from neonates.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética / Conectoma Límite: Humans / Infant Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética / Conectoma Límite: Humans / Infant Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos