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Construction and validation of a database of head models for functional imaging of the neonatal brain.
Collins-Jones, Liam H; Arichi, Tomoki; Poppe, Tanya; Billing, Addison; Xiao, Jiaxin; Fabrizi, Lorenzo; Brigadoi, Sabrina; Hebden, Jeremy C; Elwell, Clare E; Cooper, Robert J.
Afiliação
  • Collins-Jones LH; DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
  • Arichi T; Biomedical Optics Research Laboratory, Medical Physics and Biomedical Engineering, University College London, London, UK.
  • Poppe T; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK.
  • Billing A; Department of Bioengineering, Imperial College of Science, Technology, and Medicine, London, UK.
  • Xiao J; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK.
  • Fabrizi L; DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
  • Brigadoi S; Institute for Cognitive Neuroscience, University College London, London, UK.
  • Hebden JC; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK.
  • Elwell CE; Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
  • Cooper RJ; Department of Information Engineering, University of Padova, Padova, Italy.
Hum Brain Mapp ; 42(3): 567-586, 2021 02 15.
Article em En | MEDLINE | ID: mdl-33068482
The neonatal brain undergoes dramatic structural and functional changes over the last trimester of gestation. The accuracy of source localisation of brain activity recorded from the scalp therefore relies on accurate age-specific head models. Although an age-appropriate population-level atlas could be used, detail is lost in the construction of such atlases, in particular with regard to the smoothing of the cortical surface, and so such a model is not representative of anatomy at an individual level. In this work, we describe the construction of a database of individual structural priors of the neonatal head using 215 individual-level datasets at ages 29-44 weeks postmenstrual age from the Developing Human Connectome Project. We have validated a method to segment the extra-cerebral tissue against manual segmentation. We have also conducted a leave-one-out analysis to quantify the expected spatial error incurred with regard to localising functional activation when using a best-matching individual from the database in place of a subject-specific model; the median error was calculated to be 8.3 mm (median absolute deviation 3.8 mm). The database can be applied for any functional neuroimaging modality which requires structural data whereby the physical parameters associated with that modality vary with tissue type and is freely available at www.ucl.ac.uk/dot-hub.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Neuroimagem Tipo de estudo: Prognostic_studies Limite: Humans / Newborn Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Neuroimagem Tipo de estudo: Prognostic_studies Limite: Humans / Newborn Idioma: En Ano de publicação: 2021 Tipo de documento: Article