Cited by 349Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsNMR spectroscopy and applications

SANDI: a compartment‐based model for non‐invasive apparent soma and neurite imaging by diffusion MRI

Open access
Palombo, Marco, Ianus, Andrada, Guerreri, Michele, Nunes, Daniel, Alexander, Daniel C., Shemesh, Noam, Zhang, Hui·2020·NeuroImage

Abstract

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ​≤ ​3,000 ​s/mm2 (or 3 ​ms/μm2), it has been also shown to fail in GM at high b values (b≫3,000 ​s/mm2 or 3 ​ms/μm2). Here we hypothesise that the unmodelled soma compartment (i.e. cell body of any brain cell type: from neuroglia to neurons) may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma of any brain cell type is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax ​= ​40,000 ​s/mm2, or 40 ​ms/μm2) and human (bmax ​= ​10,000 ​s/mm2, or 10 ​ms/μm2) brain. We show that SANDI defines new contrasts representing complementary information on the brain cyto- and myelo-architecture. Indeed, we show maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2020.116835

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 102 · Cited by 349

Research works printed but not linked: 4

  1. Afzali M. Improving neural soma imaging using the power spectrum of the free gradient waveforms Proc. Intl. Soc. Mag. Reson. Med. 2020 204
  2. Bianciardi M. Validation and application of soma and neurite density imaging (SANDI) for in vivo human brainstem nuclei atlasing Proc. Int. Soc. Mag. Reson. Med 2020 3210
  3. Gyori N. Clark C. Dragonu I. Alexander D.C. Kaden E. In-vivo neural soma imaging using B-tensor encoding and deep learning Proc. Intl. Soc. Mag. Reson. Med. 2019 0059
  4. Palombo M. New potential MRI markers of glial scarring and tissue damage in multiple sclerosis spinal cord pathology using diffusion MRI Proc. Intl. Soc. Mag. Reson. Med. 2020 5074

Authors
Palombo, M., Ianus, A., Guerreri, M., Nunes, D., Alexander, D. C., Shemesh, N., & Zhang, H.
Affiliations
University College London (GB)
Corresponding author
Palombo, Marco
Venue
NeuroImage
Publisher
Elsevier BV
Published
2020-07
Volume
215
Pages
116835
ISSN
1053-8119 (ISSN-L)
OpenAlex
W3015618497
Cited by
349
References
102
Citations by year
2026: 67 · 2025: 80 · 2024: 63 · 2023: 42 · 2022: 42 · 2021: 31 · 2020: 23
FWCI
16.80
Type
journal article
Language
en
Update notices
erratum (2021-02-01)
Open access
Locations
  • NeuroImage (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • Horizon 2020 Framework Programme (679058)
  • Engineering and Physical Sciences Research Council (EP/G007748, EP/I027084/01, EP/L022680/1, EP/M020533/1, EP/M507970/1, EP/N018702/1)
  • European Research Council
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
Keywords
diffusion MRI, brain microstructure, restricted diffusion, cytoarchitecture, myeloarchitecture, white matter, gray matter
MeSH terms
Adult, Animals, Brain, Female, Humans, Male, Mice, Inbred C57BL, Models, Neurological, Neurites, Diffusion Magnetic Resonance Imaging, Mice, Cell Body

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review