Evidence map›Paper›PMID 27736872›Full record

ArticlePloS one2016

A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants.

Sofya Kulikova, Lucie Hertz-Pannier, Ghislaine Dehaene-Lambertz, Cyril Poupon, Jessica Dubois

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

  1. Field Strength-Dependent White Matter RMagnetic resonance in medicine · 2026
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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

5 authors at 2 institutions in 1 country.

Sofya KulikovaINSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
Lucie Hertz-PannierINSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
Ghislaine Dehaene-LambertzINSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.
Cyril PouponCEA/DRF/I2BM/Neurospin/UNIRS, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.
Jessica DuboisINSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0003-4865-8111
Université Paris-Sud · FRDélégation Paris 5 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The volume fraction of water related to myelin (fmy) is a promising MRI index for in vivo assessment of brain myelination, that can be derived from multi-component analysis of T1 and T2 relaxometry signals. However, existing quantification methods require rather long acquisition and/or post-processing times, making implementation difficult both in research studies on healthy unsedated children and in clinical examinations. The goal of this work was to propose a novel strategy for fmy quantification within acceptable acquisition and post-processing times. Our approach is based on a 3-compartment model (myelin-related water, intra/extra-cellular water and unrestricted water), and uses calibrated values of inherent relaxation times (T1c and T2c) for each compartment c. Calibration was first performed on adult relaxometry datasets (N = 3) acquired with large numbers of inversion times (TI) and echo times (TE), using an original combination of a region contraction approach and a non-negative least-square (NNLS) algorithm. This strategy was compared with voxel-wise fitting, and showed robust estimation of T1c and T2c. The accuracy of fmy calculations depending on multiple factors was investigated using simulated data. In the testing stage, our strategy enabled fast fmy mapping, based on relaxometry datasets acquired with reduced TI and TE numbers (acquisition <6 min), and analyzed with NNLS algorithm (post-processing <5min). In adults (N = 13, mean age 22.4±1.6 years), fmy maps showed variability across white matter regions, in agreement with previous studies. In healthy infants (N = 18, aged 3 to 34 weeks), asynchronous changes in fmy values were demonstrated across bundles, confirming the well-known progression of myelination.

Indexed as

AdultAlgorithmsBrainBrain MappingHumansInfantMagnetic Resonance ImagingMyelin SheathWaterWhite MatterWater

Identifiers

PMID27736872
PMCPMC5063462
OpenAlexW2531380755

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.