Evidence map›Paper›PMID 31568873›Full record

ArticleNeuroImage2020

Retrieving neuronal orientations using 3D scanning SAXS and comparison with diffusion MRI.

Marios Georgiadis, Aileen Schroeter, Zirui Gao, Manuel Guizar-Sicairos, Dmitry S Novikov, Els Fieremans, Markus Rudin

Abstract readComparative Study
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
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  3. Article
  4. Article
  5. Review
  6. Article
  7. Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures.Acta crystallographica. Section A, Foundations and advances · 2023
    Article
  8. Article
  9. Article
  10. A multiscale tissue assessment in a rat model of mild traumatic brain injury.Journal of neuropathology and experimental neurology · 2022
    Article
  11. Review
  12. Article
  13. Article
  14. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Marios GeorgiadisInstitute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA; Department of Radiology, Stanford Medicine, USA. Electronic address: mariosg@stanford.edu.
Aileen SchroeterInstitute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland.
Zirui GaoInstitute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Paul Scherrer Institute, Villigen, Switzerland.
Manuel Guizar-SicairosPaul Scherrer Institute, Villigen, Switzerland.
Dmitry S NovikovCenter for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA.
Els FieremansCenter for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA.
Markus RudinInstitute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRIR01NS088040 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2014 to 2023
$5.2M
NIA NIH HHS P30 AG066512NIBIB NIH HHS P41 EB017183NINDS NIH HHS R01 NS088040
6 · The paper itself

Abstract

While diffusion MRI (dMRI) is currently the method of choice to non-invasively probe tissue microstructure and study structural connectivity in the brain, its spatial resolution is limited and its results need structural validation. Current ex vivo methods employed to provide 3D fiber orientations have limitations, including tissue-distorting sample preparation, small field of view or inability to quantify 3D fiber orientation distributions. 3D fiber orientation in tissue sections can be obtained from 3D scanning small-angle X-ray scattering (3D sSAXS) by analyzing the anisotropy of scattering signals. Here we adapt the 3D sSAXS method for use in brain tissue, exploiting the high sensitivity of the SAXS signal to the ordered molecular structure of myelin. We extend the characterization of anisotropy from vectors to tensors, employ the Funk-Radon-Transform for converting scattering information to real space fiber orientations, and demonstrate the feasibility of the method in thin sections of mouse brain with minimal sample preparation. We obtain a second rank tensor representing the fiber orientation distribution function (fODF) for every voxel, thereby generating fODF maps. Finally, we illustrate the potential of 3D sSAXS by comparing the result with diffusion MRI fiber orientations in the same mouse brain. We show a remarkably good correspondence, considering the orthogonality of the two methods, i.e. the different physical processes underlying the two signals. 3D sSAXS can serve as validation method for microstructural MRI, and can provide novel microstructural insights for the nervous system, given the method's orthogonality to dMRI, high sensitivity to myelin sheath's orientation and abundance, and the possibility to extract myelin-specific signal and to perform micrometer-resolution scanning.

Indexed as

AnimalsBrainDiffusion Magnetic Resonance ImagingFeasibility StudiesMiceNerve Fibers, MyelinatedNeuroimagingSensitivity and SpecificityTomography, X-Ray ComputedX-Ray Diffraction3D scanning SAXSBrain X-ray scatteringDiffusion MRIMyelin sheathNeuronal orientationODF validation

Identifiers

PMID31568873
PMCPMC7306056

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.