Evidence map›Paper›PMID 31148254›Full record

ArticleMagnetic resonance in medicine2019

Water removal in MR spectroscopic imaging with L2 regularization.

Liangjie Lin, Michal Považan, Adam Berrington, Zhong Chen, Peter B Barker

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. A Digital Phantom for MR Spectroscopy Data Simulation.Magnetic resonance in medicine · 2026
    Article
  3. A data-driven algorithm to determineMagnetic resonance in medicine · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Application of aImaging neuroscience (Cambridge, Mass.) · 2023
    Article
  9. Article
  10. Accelerated J-resolvedMagnetic resonance in medicine · 2021
    Article
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.

Liangjie LinRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Michal PovažanRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Adam BerringtonRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Zhong ChenDepartment of Electronic Science, Xiamen University, Xiamen, China.
Peter B BarkerRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-6410-7793

Funding

TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2012 to 2020
$13.1M
State of the Art 3T Research ScannerS10OD021648 · OD · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2016 to 2016
$2.0M
NIBIB NIH HHS P41 EB015909NIH HHS S10 OD021648
6 · The paper itself

Abstract

purposeAn L2-regularization based postprocessing method is proposed and tested for removal of residual or unsuppressed water signals in proton MR spectroscopic imaging (MRSI) data recorded from the human brain at 3T.

methodsWater signals are removed by implementation of the L2 regularization using a synthesized water-basis matrix that is orthogonal to metabolite signals of interest in the spectral dimension. Simulated spectra with variable water amplitude and in vivo brain MRSI datasets were used to demonstrate the proposed method. Results were compared with two commonly-used postprocessing methods for removing water signals.

resultsThe L2 method yielded metabolite signals that were close to true values for the simulated spectra. Residual/unsuppressed water signals in human brain short- and long-echo time MRSI datasets were efficiently removed by the proposed method allowing good quality metabolite maps to be reconstructed with minimized contamination from water signals. Significant differences of the creatine signal were observed between brain long-echo time MRSI without and with water saturation, attributable to the previously described magnetization transfer effect.

conclusionsWith usage of a synthesized water matrix generated based on reasonable prior knowledge about water and metabolite resonances, the L2 method is shown to be an effective way to remove water signals from MRSI of the human brain.

Indexed as

AdultAlgorithmsBrainCreatineHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleSignal Processing, Computer-AssistedWaterCreatineWaterL2 regularizationmetabolite mapMR spectroscopic imagingwater suppression

Identifiers

PMID31148254
PMCPMC6626566

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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.