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Pre- and post-surgery brain tumor multimodal magnetic resonance imaging data optimized for large scale computational modelling.
Aerts, Hannelore; Colenbier, Nigel; Almgren, Hannes; Dhollander, Thijs; Daparte, Javier Rasero; Clauw, Kenzo; Johri, Amogh; Meier, Jil; Palmer, Jessica; Schirner, Michael; Ritter, Petra; Marinazzo, Daniele.
Afiliação
  • Aerts H; Department of Data Analysis, Ghent University, Ghent, Belgium.
  • Colenbier N; Department of Data Analysis, Ghent University, Ghent, Belgium.
  • Almgren H; Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.
  • Dhollander T; IRCSS San Camillo Hospital, Venice, Italy.
  • Daparte JR; Department of Data Analysis, Ghent University, Ghent, Belgium.
  • Clauw K; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.
  • Johri A; Hothckiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Meier J; Murdoch Children's Research Institute | MCRI Research Group for Developmental Imaging, Melbourne, Australia.
  • Palmer J; CoAx Lab, Carnegie Mellon University, Pittsburgh, USA.
  • Schirner M; Department of Data Analysis, Ghent University, Ghent, Belgium.
  • Ritter P; Indraprastha Institute of Information Technology, Delhi, India.
  • Marinazzo D; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
Sci Data ; 9(1): 676, 2022 11 05.
Article em En | MEDLINE | ID: mdl-36335218
ABSTRACT
We present a dataset of magnetic resonance imaging (MRI) data (T1, diffusion, BOLD) acquired in 25 brain tumor patients before the tumor resection surgery, and six months after the surgery, together with the tumor masks, and in 11 controls (recruited among the patients' caregivers). The dataset also contains behavioral and emotional scores obtained with standardized questionnaires. To simulate personalized computational models of the brain, we also provide structural connectivity matrices, necessary to perform whole-brain modelling with tools such as The Virtual Brain. In addition, we provide blood-oxygen-level-dependent imaging time series averaged across regions of interest for comparison with simulation results. An average resting state hemodynamic response function for each region of interest, as well as shape maps for each voxel, are also contributed.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Imageamento por Ressonância Magnética Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Bélgica

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Imageamento por Ressonância Magnética Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Bélgica