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Human brain MRI data of intrathecally injected tracer evolution over 72 hours for data-integrated simulations
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  • Published: 20 January 2026

Human brain MRI data of intrathecally injected tracer evolution over 72 hours for data-integrated simulations

  • Jørgen N. Riseth  ORCID: orcid.org/0000-0002-7923-60101,2,
  • Timo Koch1,2,3,
  • Sofie Lysholm Lian4,
  • Tryggve Holck Storås5,
  • Ludmil T. Zikatanov2,6,
  • Lars Magnus Valnes2,
  • Kaja Nordengen4,5 &
  • …
  • Kent-André Mardal1,2,7 

Scientific Data , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Applied mathematics
  • Brain
  • Data acquisition
  • Image processing
  • Scientific data

Abstract

We present the Gonzo dataset: Brain MRI with processed and derivative data from one healthy male human volunteer ("Gonzo”) before and during the 72 hours after intrathecal injection of the contrast agent gadobutrol into the cerebrospinal fluid (CSF) of the spinal canal. The MRI data records include images highlighting the temporal and spatial evolution of the contrast agent in CSF, brain, and adjacent structures. In addition to raw MRI, we provide derivatives that enable numerical simulations of the transport process under study. Derivatives include T1 maps, tracer concentration maps, diffusion tensor maps, and unstructured triangulated volume meshes of the brain geometry. We also provide brain region markers obtained by image segmentation. A regional statistical analysis of the concentration data complements the image data. The presented data can be used to study the transport behavior and the underlying processes of a tracer in the brain. It is intended to contribute to and inspire new studies on the understanding of tracer transport, method development for image analysis, and simulation of brain fluid transport processes.

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Data availability

All records are available in the Zenodo repository https://zenodo.org/records/1426686753 with https://doi.org/10.5281/zenodo.14266867.

Code availability

The source code for running each step of the described data processing pipeline is split into three repositories. The separation of the source code intends to facilitate the use of the software in future studies involving only parts of the processing pipeline of this dataset.

gonzo: The main repository related to this study. It includes instructions for installing necessary dependencies, running the data processing pipeline, and running scripts for creating plots in this document. The code is publicly available at https://github.com/jorgenriseth/gonzo and as an archived dataset57.

gMRI2FEM: A Python library used for post-processing MRI data. The code is publicly available at https://github.com/jorgenriseth/gMRI2FEM and as an archived dataset58.

dumux-braindiffusion-miniapp: A reuse example code that provides a simulator that uses the provided data set (C++ code, based on the DuMux/DUNE framework59,60,61 and GridFormat62).

The code is publicly available at https://github.com/timokoch/dumux-braindiffusion-miniapp and as an archived dataset63 and may be helpful for users interested in using the provided data in a simulation reuse setup.

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Acknowledgements

The authors thank Geir Ringstadt and Per-Kristian Eide for spearheading the development of glymphatic MRI and for fruitful discussions. The authors are grateful to the anonymous volunteer for participating in the study and giving informed consent to open publication, allowing us to disseminate this unique data set. S.L. and K.N. acknowledge funding from the South Eastern Norway Health Authority (Helse Sør-Øst) within project 2022022 (Clearance pathways in Parkinson’s disease) and the Norwegian Health Association (Nasjonalforeningen for folkehelsen) within projects 25598 and 28398. T.K. acknowledges funding from the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska-Curie Actions Grant agreement No 801133 (Scientia fellows II). T.K. and K.A.M. acknowledge funding by the Research Council of Norway, project 301013 (Alzheimer’s physics). T.K., J.N.R and K.A.M. acknowledge funding by the European Research Council under grant 101141807 (aCleanBrain). K.A.M. and L.M.V acknowledges the funding from the “Computational Hydrology project” a strategic Sustainability initiative at the Faculty of Natural Sciences, UiO. K.A.M. acknowledges funding from the Stiftelsen Kristian Gerhard Jebsen via the K. G. Jebsen Centre for Brain Fluid Research and the national infrastructure for computational science in Norway, Sigma2, via grant NN9279K. The work of L.T.Z. was supported in part by U.S. NSF DMS-220829 and the U.S.-Norway Fulbright Foundation.

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Authors and Affiliations

  1. Scientific Computing and Numerical Analysis (SCAN), Simula Research Laboratory, Oslo, Norway

    Jørgen N. Riseth, Timo Koch & Kent-André Mardal

  2. Department of Mathematics, University of Oslo, Oslo, Norway

    Jørgen N. Riseth, Timo Koch, Ludmil T. Zikatanov, Lars Magnus Valnes & Kent-André Mardal

  3. Department of Hydromechanics and Modelling of Hydrosystems, University of Stuttgart, Stuttgart, Germany

    Timo Koch

  4. Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Sofie Lysholm Lian & Kaja Nordengen

  5. Department of Neurology, Oslo University Hospital, Oslo, Norway

    Tryggve Holck Storås & Kaja Nordengen

  6. Department of Mathematics, The Pennsylvania State University, University Park, USA

    Ludmil T. Zikatanov

  7. KG Jebsen Center for Brain Fluid Research, Oslo, Norway

    Kent-André Mardal

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  1. Jørgen N. Riseth
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  2. Timo Koch
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Contributions

J.R.: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing - original draft; T.K.: Formal analysis, Investigation, Software, Methodology, Supervision, Validation, Visualization, Writing - original draft; S.L.: Data curation, Methodology, Investigation, Writing - review & editing; T.H.S.: Data curation, Formal analysis, Methodology, Writing - review & editing; L.M.V.: Software, Methodology, Writing - review & editing; L.Z.: Conceptualization, Investigation, Writing - review & editing; K.N.: Conceptualization, Funding acquisition, Methodology, Project Administration, Supervision, Writing - review & editing; K.A.M.: Conceptualization, Methodology, Funding acquisition, Project Administration, Supervision, Writing - original draft.

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Correspondence to Kent-André Mardal.

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Riseth, J.N., Koch, T., Lian, S.L. et al. Human brain MRI data of intrathecally injected tracer evolution over 72 hours for data-integrated simulations. Sci Data (2026). https://doi.org/10.1038/s41597-026-06564-1

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  • Received: 04 August 2025

  • Accepted: 06 January 2026

  • Published: 20 January 2026

  • DOI: https://doi.org/10.1038/s41597-026-06564-1

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