Evidence map›Paper›PMID 28840613›Full record

ArticleMagnetic resonance in medicine2018

Characterizing and eliminating errors in enhancement and subtraction artifacts in dynamic contrast-enhanced breast MRI: Chemical shift artifact of the third kind.

Jamal J Derakhshan, Elizabeth S McDonald, Evan S Siegelman, Mitchell D Schnall, Felix W Wehrli

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Article in Magnetic resonance in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jamal J DerakhshanDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-4046-4857
Elizabeth S McDonaldDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Evan S SiegelmanDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Mitchell D SchnallDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Felix W WehrliDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Funding

RESEARCH TRACK RADIOLOGY RESIDENCYT32EB004311 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Terence P Gade, Misun Hwang · 2005 to 2026
$4.5M
NIBIB NIH HHS T32 EB004311
6 · The paper itself

Abstract

purposeTo characterize errors in enhancement in breast dynamic contrast-enhanced (DCE) MRI studies as a function of echo time and determine the source of dark band artifacts in clinical subtraction images.

methodsComputer simulations, oil and water substitute (methylene chloride), as well as an American College of Radiology quality control phantom were tested. Routine clinical DCE breast MRI study was bracketed with (accelerated) in-phase DCE acquisitions in five patients.

resultsSimulation results demonstrated up to -160% suppression of the expected enhancement caused by differential enhancement of fat and water. Two-dimensional gradient-recalled echo and fat-suppressed 3D GRE phantom imaging confirmed the simulation results and showed that fat suppression does not eliminate the artifact. In vivo in-phase DCE images showed increased enhancement consistent with predictions and also confirmed increased spatial blurring on in-phase 3D gradient-recalled echo images. Combined multi-dimensional partial Fourier and parallel imaging provided a time-equivalent in-phase DCE MRI acquisition.

conclusionErrors in expected enhancement occur in DCE breast MRI subtraction images because of differential enhancement of fat and water and incomplete fat signal suppression. These errors can lead to artificial suppression of enhancement as well as dark band artifacts on subtraction images. These artifacts can be eliminated with a time-equivalent in-phase fat-suppressed 3D gradient-recalled echo sequence. Understanding chemical shift artifact of the third kind, a unique artifact of artificial enhancement suppression in the presence of intravoxel fat and water signal, will aid DCE breast MRI image interpretation. In-phase acquisitions (combined with simultaneous minimum echo time or opposed-phase echoes) may facilitate qualitative, quantitative and longitudinal analysis of contrast enhancement. Magn Reson Med 79:2277-2289, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Indexed as

Magnetic Resonance ImagingAdipose TissueAdultAgedArtifactsBiopsyBreastComputer SimulationContrast MediaDiagnostic ErrorsFemaleFourier AnalysisHumansImage Interpretation, Computer-AssistedImaging, Three-DimensionalMammographyContrast MediaMethylene Chloridebreast MRIchemical shift artifactdynamic contrast-enhanced (DCE) MRIenhancement errorsparadoxical enhancementsubtraction artifact

Identifiers

PMID28840613
PMCPMC5811365

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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.