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Validation of in vitro probabilistic tractography
Abstract
Diffusion weighted imaging (DWI) and tractography allow the non-invasive study of anatomical brain connectivity. However, a gold standard for validating tractography of complex connections is lacking. Using the porcine brain as a highly gyrated brain model, we quantitatively and qualitatively assessed the anatomical validity and reproducibility of in vitro multi-fiber probabilistic tractography against two invasive tracers: the histochemically detectable biotinylated dextran amine and manganese enhanced magnetic resonance imaging. Post mortem DWI was used to ensure that most of the sources known to degrade the anatomical accuracy of in vivo DWI did not influence the tracking results. We demonstrate that probabilistic tractography reliably detected specific pathways. Moreover, the applied model allowed identification of the limitations that are likely to appear in many of the current tractography methods. Nevertheless, we conclude that DWI tractography can be a precise tool in studying anatomical brain connectivity.
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“Ex vivo imaging and tracing17–23 or physically24–30 and numerically simulated phantoms31–34 allow validation to some extent, and in specific circumstances such as basic fiber configurations.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [17]
In the citing paper
“However, these evaluations cannot validate the accuracy of reconstructions due to the lack of ground truth information17.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [17]
In the citing paper
“However, there is one domain where histological postmortem studies have shown a consistent failure of dMRI, which is in regions of transition between white and gray matter, where orientation errors of as much as 90° have been observed (49, 50).”
From Superior Longitudinal Fasciculus: A Review of the Anatomical Descriptions With Functional Correlates (2022) · cites this paper as [49]
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Metadata
- Authors
- Dyrby, T. B., Søgaard, L. V., Parker, G. J., Alexander, D. C., Lind, N. M., Baaré, W. F. C., Hay-Schmidt, A., Eriksen, N., Pakkenberg, B., Paulson, O. B., & Jelsing, J.
- Affiliations
- Hvidovre Hospital (DK)
- University College London (GB)
- University of Copenhagen (DK)
- Bispebjerg Hospital (DK)
- Corresponding author
- Dyrby, Tim B.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2007-10
- Volume
- 37
- Issue
- 4
- Pages
- 1267-1277
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1979286792
- Cited by
- 236
- References
- 42
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 3 · 2023: 4 · 2022: 5 · 2021: 13 · 2020: 16 · 2019: 13 · 2018: 18 · 2017: 16 · 2016: 11 · 2015: 17 · 2014: 15 · 2013: 18 · 2012: 19
- FWCI
- 7.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Funders
- Velux Stiftung
- Lundbeckfonden
- Engineering and Physical Sciences Research Council
- Biotechnology and Biological Sciences Research Council
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- probabilistic tractography, diffusion-weighted imaging, porcine brain, biotinylated dextran amine, manganese-enhanced MRI
- MeSH terms
- Algorithms, Animals, Biotin, Brain, Cerebral Cortex, Dextrans, Fluorescent Dyes, Male, Manganese, Nerve Fibers, Neural Pathways, Swine, Swine, Miniature, Reproducibility of Results, Models, Statistical, Diffusion Magnetic Resonance Imaging
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