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Cited by 290Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications

Building connectomes using diffusion MRI: why, how and but

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Sotiropoulos, Stamatios N., Zalesky, Andrew·2019·NMR in Biomedicine
DOI 10.1002/nbm.3752PMC PMC6491971
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Abstract

Why has diffusion MRI become a principal modality for mapping connectomes in vivo ? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI‐based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments.

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  • Because tractography, network analysis, and NODDI each have limitations, caution is required when interpreting NODDI connectomics data.

    “Tractography and network analysis both have their own limitations (Jeurissen et al., 2019;Sotiropoulos and Zalesky, 2019), which, in combination with the limitations of NODDI, means that caution is required when interpreting the data.”

    From NODDI in clinical research (2020) · cites this paper as Sotiropoulos and Zalesky, 2019

  • NOS does not provide a truly quantitative measure of connection strength because of the difference in resolution between the measured dMRI signal and actual axon dimensions.

    “However, because of the difference in resolution between the measured dMRI signal and actual axon dimensions (as described in Section 3.3: “Connection density biases”), many studies have emphasized that NOS does not provide a truly quantitative measure of connection strength (Jones, 2010; Jones et al., 2013; Sotiropoulos and Zalesky, 2019; Yeh et al., 2020).”

    From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Sotiropoulos and Zalesky, 2019

  • The first category of quantitative measures is based on tractography data alone and is often used to define connectivity strength.

    “The first category of quantitative measures are based on the tractography data alone, which are often used to define the connectivity strength (Jones, 2010; Smith et al., 2020a; Sotiropoulos and Zalesky, 2019; Yeh et al., 2020).”

    From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Sotiropoulos and Zalesky, 2019

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Authors
Sotiropoulos, S. N., & Zalesky, A.
Affiliations
  • University of Nottingham (GB)
  • The University of Melbourne (AU)
Corresponding author
Sotiropoulos, Stamatios N.
ORCID
Venue
NMR in Biomedicine
Publisher
Wiley
Published
2017-06-27
Volume
32
Issue
4
Pages
e3752-e3752
ISSN
  • 0952-3480 (ISSN-L)
  • 1099-1492
DOI
10.1002/nbm.3752
PMC
PMC6491971
OpenAlex
W2622948156
Cited by
290
References
36
Citations by year
2026: 23 · 2025: 28 · 2024: 40 · 2023: 30 · 2022: 37 · 2021: 48 · 2020: 35 · 2019: 20 · 2018: 24 · 2017: 5
FWCI
3.48
Type
journal article
Language
en
Open access
Licence
Locations
  • NMR in Biomedicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
Funders
  • National Health and Medical Research Council of Australia (APP1047648)
  • UK Engineering and Physical Sciences Research Council (EP/L023067/1)
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
connectome mapping, diffusion MRI, white matter tractography, image acquisition parameters, connectome reconstruction, microstructural properties, network characteristics
MeSH terms
Animals, Brain, Humans, Myelin Sheath, Reproducibility of Results, Diffusion Magnetic Resonance Imaging, Connectome

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