Evidence map›Paper›PMID 33022844›Full record

ArticleHuman brain mapping2021

Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain.

João P de Almeida Martins, Chantal M W Tax, Alexis Reymbaut, Filip Szczepankiewicz, Maxime Chamberland, Derek K Jones, Daniel Topgaard

Open access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
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

27 citing papers in PubMed, 52 citations in OpenAlex.

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  15. Nonparametric 5D D-RJournal of magnetic resonance (San Diego, Calif. : 1997) · 2022
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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 at 4 institutions in 6 countries.

João P de Almeida MartinsDivision of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.ORCID 0000-0002-3527-4103
Chantal M W TaxCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK.
Alexis ReymbautDivision of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.
Filip SzczepankiewiczDepartment of Clinical Sciences, Lund University, Lund, Sweden.
Maxime ChamberlandCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK.
Derek K JonesCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK.
Daniel TopgaardDivision of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.
Lund University · SECardiff University · GBBrigham and Women's Hospital · USUtrecht University · NL

Funding

Wellcome TrustWellcome Trust 096646/Z/11/ZWellcome Trust 104943/Z/14/ZWellcome Trust 215944/Z/19/Z
6 · The paper itself

Abstract

Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.

Indexed as

AlgorithmsComputer SimulationBrainDatabases, FactualDiffusion Magnetic Resonance ImagingHumansMonte Carlo MethodWhite Matterdiffusion MRIfibre ODFfibre-specific metricspartial volume effectstensor-valued diffusion encodingwhite matter

Identifiers

PMID33022844
PMCPMC7776010
OpenAlexW3092184067

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.