Evidence map›Paper›PMID 29472296›Full record

ArticleAJNR. American journal of neuroradiology2018

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

S Soman, Z Liu, G Kim, U Nemec, S J Holdsworth, K Main, B Lee, S Kolakowsky-Hayner, M Selim, A J Furst and 6 more

Open access · hybridAbstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

16 authors at 10 institutions in 7 countries.

S SomanFrom the Departments of Radiology (S.S., G.K., B.L.) sal@alum.mit.edu.ORCID 0000-0002-5887-0717
Z LiuDepartment of Biomedical Engineering (Z.L., Y.W.), Cornell University, New York, New York.ORCID 0000-0001-7652-5215
G KimFrom the Departments of Radiology (S.S., G.K., B.L.).ORCID 0000-0002-3477-9986
U NemecDepartment of Biomedical Imaging and Image-Guided Therapy (U.N.), Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-2804-043X
S J HoldsworthDepartments of Radiology (S.J.H., P.M., M.M.).ORCID 0000-0002-2929-1169
K MainResearch Division, Defense and Veterans Brain Injury Center (K.M.), General Dynamics Health Solutions, Silver Spring, Maryland.ORCID 0000-0002-4929-4447
B LeeFrom the Departments of Radiology (S.S., G.K., B.L.).ORCID 0000-0002-6879-3778
S Kolakowsky-HaynerDepartment of Rehabilitation Medicine (S.K.-H.), Icahn School of Medicine at Mount Sinai, New York, New York.ORCID 0000-0002-6228-9909
M SelimNeurology (M.S.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0002-1936-3173
A J FurstPsychiatry and Behavioral Sciences (A.J.F., J.Y., M.M.A.).ORCID 0000-0003-1750-550X
P MassabandDepartments of Radiology (S.J.H., P.M., M.M.).ORCID 0000-0002-0874-2223
J YesavagePsychiatry and Behavioral Sciences (A.J.F., J.Y., M.M.A.).ORCID 0000-0002-7390-3281
M M AdamsonPsychiatry and Behavioral Sciences (A.J.F., J.Y., M.M.A.).ORCID 0000-0002-1534-4063
P SpincemailleDepartment of Radiology (P.S., Y.W.), Weil Cornell Medical College, New York, New York.ORCID 0000-0002-8821-1341
M MoseleyDepartments of Radiology (S.J.H., P.M., M.M.).ORCID 0000-0002-9163-8741
Y WangDepartment of Biomedical Engineering (Z.L., Y.W.), Cornell University, New York, New York.ORCID 0000-0003-1404-8526
Cornell University · USResearch Institute of Radiology · BYBehavioral Pharma (United States) · USNorwegian Womens Public Health Association · NOBeth Israel Deaconess Medical Center · USGeneral Dynamics (United States) · USIcahn School of Medicine at Mount Sinai · USMedical University of Vienna · ATMyanmar Institute of Theology · MMVA Palo Alto Health Care System · US

Funding

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
Multiple Sclerosis Lesion Magnetic Susceptibility ActivityR01NS090464 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2015 to 2020
$2.3M
Compact Representations of Dynamic Liver MRIR01CA181566 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SPINCEMAILLE, PASCAL · 2015 to 2019
$1.9M
Theranostic nanoparticles for the treatment of RAI refractory thyroid cancerR01CA178007 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI JIN, MOONSOO M., WANG, YI · 2013 to 2017
$1.7M
Analyses of gradient echo MRI dataR01EB013443 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2011 to 2014
$1.5M
NCI NIH HHS R01 CA178007NCI NIH HHS R01 CA181566NIBIB NIH HHS R01 EB013443NINDS NIH HHS R01 NS090464NINDS NIH HHS R01 NS095562
6 · The paper itself

Abstract

background and purposeIdentifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. MATERIALS AND

methodsFifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident.

resultsTen subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping.

conclusionsPreconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury.

Indexed as

AdultBrain Injuries, TraumaticFemaleHumansImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingSkull

Identifiers

PMID29472296
PMCPMC5895509
OpenAlexW2788040941

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.