Cited by 127Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications

Validation of tractography: Comparison with manganese tracing

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Knösche, Thomas R., Anwander, Alfred, Liptrot, Matthew, Dyrby, Tim B.·2015·Human Brain Mapping

Abstract

In this study, we used invasive tracing to evaluate white matter tractography methods based on ex vivo diffusion‐weighted magnetic resonance imaging (dwMRI) data. A representative selection of tractography methods were compared to manganese tracing on a voxel‐wise basis, and a more qualitative assessment examined whether, and to what extent, certain fiber tracts and gray matter targets were reached. While the voxel‐wise agreement was very limited, qualitative assessment revealed that tractography is capable of finding the major fiber tracts, although there were some differences between the methods. However, false positive connections were very common and, in particular, we discovered that it is not possible to achieve high sensitivity (i.e., few false negatives) and high specificity (i.e., few false positives) at the same time. Closer inspection of the results led to the conclusion that these problems mainly originate from regions with complex fiber arrangements or high curvature and are not easily resolved by sophisticated local models alone. Instead, the crucial challenge in making tractography a truly useful and reliable tool in brain research and neurology lies in the acquisition of better data. In particular, the increase of spatial resolution, under preservation of the signal‐to‐noise‐ratio, is key. Hum Brain Mapp 36:4116–4134, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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  • Ex vivo imaging and tracing or physically and numerically simulated phantoms allow validation to some extent, and in specific circumstances such as basic fiber configurations.

    “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.”

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References 78 · Cited by 127

Authors
Knösche, T. R., Anwander, A., Liptrot, M., & Dyrby, T. B.
Affiliations
  • Max Planck Institute for Human Cognitive and Brain Sciences (DE)
  • University of Copenhagen (DK)
  • Hvidovre Hospital (DK)
Corresponding author
Dyrby, Tim B.
Venue
Human Brain Mapping
Publisher
Wiley
Published
2015-07-14
Volume
36
Issue
10
Pages
4116-4134
ISSN
  • 1065-9471 (ISSN-L)
  • 1097-0193
OpenAlex
W1951022114
Cited by
127
References
78
Citations by year
2026: 3 · 2025: 7 · 2024: 5 · 2023: 5 · 2022: 7 · 2021: 18 · 2020: 12 · 2019: 15 · 2018: 22 · 2017: 19 · 2016: 10 · 2015: 3 · 2013: 1
FWCI
14.57
Type
journal article
Language
en
Open access
Locations
  • Human Brain Mapping (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Max Planck Digital Library (submittedVersion, other-oa)
  • Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
Funders
  • FP7-ICT-STREP (238292)
  • Lundbeck Foundation (R59-A5399)
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
diffusion-weighted imaging, white matter tracts, sensitivity and specificity, spatial resolution, ex vivo brain tissue
MeSH terms
Algorithms, Animals, Brain, Brain Mapping, Contrast Media, False Negative Reactions, False Positive Reactions, Image Processing, Computer-Assisted, Manganese, Models, Neurological, Motor Cortex, Nerve Fibers, Somatosensory Cortex, Swine, Swine, Miniature, Reproducibility of Results, Prefrontal Cortex, Diffusion Tensor Imaging, Signal-To-Noise Ratio, Gray Matter

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