Evidence map›Paper›PMID 31402519›Full record

ArticleMagnetic resonance in medicine2020

Automated adaptive preconditioner for quantitative susceptibility mapping.

Zhe Liu, Yan Wen, Pascal Spincemaille, Shun Zhang, Yihao Yao, Thanh D Nguyen, Yi Wang

Abstract read
PubMed Full text at PMC Publisher
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  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

7 authors.

Zhe LiuDepartment of Biomedical Engineering, Cornell University, Ithaca, New York.ORCID 0000-0001-7652-5215
Yan WenDepartment of Biomedical Engineering, Cornell University, Ithaca, New York.
Pascal SpincemailleDepartment of Radiology, Weill Cornell Medical College, New York, New York.
Shun ZhangDepartment of Radiology, Weill Cornell Medical College, New York, New York.
Yihao YaoDepartment of Radiology, Weill Cornell Medical College, New York, New York.
Thanh D NguyenDepartment of Radiology, Weill Cornell Medical College, New York, New York.
Yi WangDepartment of Biomedical Engineering, Cornell University, Ithaca, New York.ORCID 0000-0003-1404-8526

Funding

QSM to Guide Iron Chelating Therapy in Transfusional Iron OverloadR01DK116126 · NIDDK · WEILL MEDICAL COLL OF CORNELL UNIV · PI BRITTENHAM, GARY M, SHETH, SUJIT · 2019 to 2023
$3.2M
Quantitative Mapping of Substantia Nigra Iron in Parkinson's DiseaseR01NS095562 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI SHTILBANS, ALEXANDER, WANG, YI · 2016 to 2022
$3.1M
No-Gd MRI for Monitoring Disease Status in Multiple SclerosisR01NS105144 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI GAUTHIER, SUSAN A, GUPTA, AJAY · 2018 to 2022
$2.8M
Multiple Sclerosis Lesion Magnetic Susceptibility ActivityR01NS090464 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2015 to 2020
$2.3M
3.0T Magnetic Resonance Imaging System for Preclinical, Translational and Clinical ResearchS10OD021782 · OD · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2016 to 2016
$2.0M
Compact Representations of Dynamic Liver MRIR01CA181566 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SPINCEMAILLE, PASCAL · 2015 to 2019
$1.9M
Feasibility of challenge-free QSM based quantitative mapping of cerebral metabolic rate of oxygenR21EB024366 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI GOYAL, MANU S, SU, YI · 2017 to 2018
$474k
NCI NIH HHS R01 CA181566NIBIB NIH HHS R21 EB024366NIDDK NIH HHS R01 DK116126NIH HHS S10 OD021782NINDS NIH HHS R01 NS090464NINDS NIH HHS R01 NS095562NINDS NIH HHS R01 NS105144
6 · The paper itself

Abstract

purposeTo develop an automated adaptive preconditioner for QSM reconstruction with improved susceptibility quantification accuracy and increased image quality. THEORY AND

methodsThe total field was used to rapidly produce an approximate susceptibility map, which was then averaged and trended over

resultsAmong evaluated preconditioners, the automated adaptive preconditioner achieved the fastest convergence in reducing the RMSE of the QSM in the simulation, suppressed hemorrhage-associated artifacts while preserving surrounding brain tissue contrasts, and provided cardiac chamber oxygenation values consistent with those reported in the literature.

conclusionAn automated adaptive preconditioner allows high-quality QSM from the total field in imaging various anatomies with dynamic susceptibility ranges.

Indexed as

Magnetic Resonance ImagingAlgorithmsArtifactsBrainBrain MappingCerebral HemorrhageComputer SimulationHeartHumansImage Processing, Computer-AssistedModels, StatisticalNormal DistributionOxygenPattern Recognition, AutomatedPhantoms, ImagingOxygencardiachemorrhagepreconditioningQSMtotal field inversion

Identifiers

PMID31402519
PMCPMC6778703

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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.