Evidence map›Paper›PMID 35754142›Full record

ArticleMagnetic resonance in medicine2022

Phase-based masking for quantitative susceptibility mapping of the human brain at 9.4T.

Gisela E Hagberg, Korbinian Eckstein, Elisa Tuzzi, Jiazheng Zhou, Simon Robinson, Klaus Scheffler

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 2 institutions in 3 countries.

Gisela E HagbergDepartment for Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany.ORCID 0000-0003-2176-7086
Korbinian EcksteinHigh Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-4538-7072
Elisa TuzziDepartment for Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany.
Jiazheng ZhouDepartment for Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany.ORCID 0000-0002-7114-5181
Simon RobinsonDepartment of Neurology, Medical University of Graz, Graz, Austria.
Klaus SchefflerDepartment for Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany.ORCID 0000-0001-6316-8773
Max Planck Institute for Biological Cybernetics · DEThe University of Queensland · AU

Funding

Austrian Science Fund FWF KLI 264
6 · The paper itself

Abstract

purposeTo develop improved tissue masks for QSM.

methodsMasks including voxels at the brain surface were automatically generated from the magnitude alone (MM) or combined with test functions from the first (PG) or second (PB) derivative of the sign of the wrapped phase. Phase images at 3T and 9.4T were simulated at different TEs and used to generate a mask, P

resultsClose to air cavities, phase wraps became denser with increasing field and echo time, yielding increased values of the test functions. Compared with P

conclusionAutomatic, phase-based masking founded on the second derivative of the sign of the wrapped phase, including cortical voxels at the brain surface, was able to mitigate artifacts and restore QSM contrast across cortical and subcortical brain regions.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingAdultAlgorithmsArtifactsBrainBrain MappingHumansMiddle AgedYoung Adultmagnetic resonance imagingmagnetic susceptibilityMRI methodsQSMtissue masking

Identifiers

PMID35754142
PMCPMC7613679
OpenAlexW4283583996

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.