Evidence map›Paper›PMID 32281179›Full record

ArticleMagnetic resonance in medicine2020

Myelin water fraction estimation using small-tip fast recovery MRI.

Steven T Whitaker, Gopal Nataraj, Jon-Fredrik Nielsen, Jeffrey A Fessler

Open access · bronzeAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Cramér-Rao Bound Optimized Subspace Reconstruction in Quantitative MRI.IEEE transactions on bio-medical engineering · 2025
    Article
  2. Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
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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

4 authors at 2 institutions in 1 country.

Steven T WhitakerDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-1170-7653
Gopal NatarajDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0002-2847-115X
Jon-Fredrik NielsenDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
Jeffrey A FesslerDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0001-9998-3315
University of Michigan · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Toward robust whole-brain 3D functional MRI at 3T with reduced signal loss artifactsR21AG061839 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NIELSEN, JON-FREDRIK · 2019 to 2020
$408k
NCI NIH HHS P30 CA008748NIA NIH HHS R21 AG061839
6 · The paper itself

Abstract

purposeTo demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain.

methodsWe optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK.

resultsIn simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map.

conclusionsThe optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.

Indexed as

Myelin SheathWhite MatterBrainMagnetic Resonance ImagingWaterWaterkernel ridge regressionmachine learningmyelin water fraction (MWF)scan optimizationsmall-tip fast recovery (STFR)

Identifiers

PMID32281179
PMCPMC7478173
OpenAlexW3015917508

What OpenQuestion holds

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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.