Evidence map›Paper›PMID 28126551›Full record

ArticleNeuroImage2017

Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds.

Matthew J Cronin, Nian Wang, Kyle S Decker, Hongjiang Wei, Wen-Zhen Zhu, Chunlei Liu

Abstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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  14. Asymmetric susceptibility tensor imaging.Magnetic resonance in medicine · 2021
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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

6 authors.

Matthew J CroninDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
Nian WangBrain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
Kyle S DeckerBrain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
Hongjiang WeiDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
Wen-Zhen ZhuDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chunlei LiuDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA. Electronic address: chunlei.liu@berkeley.edu.

Funding

MRI Corticography (MRCoG): Micro-scale Human Cortical ImagingR24MH106096 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEINBERG, DAVID ALAN, LIU, CHUNLEI · 2014 to 2016
$1.4M
Susceptibility MRI as a marker for diagnosis and clinical disability in MSR01NS079653 · NINDS · DUKE UNIVERSITY · PI LIU, CHUNLEI · 2014 to 2015
$460k
NIMH NIH HHS R24 MH106096NINDS NIH HHS R01 NS079653
6 · The paper itself

Abstract

Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al., 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions. In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC. Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship.

Indexed as

AlgorithmsAgedBrainBrain MappingCerebral HemorrhageFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedCerebral microbleedsEcho-time-dependent QSMHollow cylinder modelMRI signal compartmentalizationQuantitative susceptibility mappingTissue microstructure

Identifiers

PMID28126551
PMCPMC5368016

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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.