Evidence map›Paper›PMID 29193307›Full record

ArticleMagnetic resonance in medicine2018

Approaching ultimate intrinsic specific absorption rate in radiofrequency shimming using high-permittivity materials at 7 Tesla.

Gillian G Haemer, Manushka Vaidya, Christopher M Collins, Daniel K Sodickson, Graham C Wiggins, Riccardo Lattanzi

Abstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  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

6 authors.

Gillian G HaemerCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Manushka VaidyaCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Christopher M CollinsCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Daniel K SodicksonCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Graham C WigginsCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Riccardo LattanziCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
Novel Software Tools for Rational Design and Assessment of MR CoilsR01EB024536 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Riccardo Lattanzi · 2017 to 2026
$5.1M
High-Performance High-Field Parallel MRI.R01EB002568 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI SODICKSON, DANIEL K · 2003 to 2014
$4.8M
RF Technology Innovation for Advancing High Field MR.R01EB011551 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI COLLINS, CHRISTOPHER M · 2011 to 2014
$2.7M
Next-Generation RF Coils with High-Permittivity Material for Improved Performance in MRIR01EB021277 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI COLLINS, CHRISTOPHER M · 2016 to 2019
$2.1M
NIBIB NIH HHS P41 EB017183NIBIB NIH HHS R01 EB002568NIBIB NIH HHS R01 EB011551NIBIB NIH HHS R01 EB021277NIBIB NIH HHS R01 EB024536
6 · The paper itself

Abstract

purposeThe aim of this study was to evaluate the effect of integrated high-permittivity materials (HPMs) on excitation homogeneity and global specific absorption rate (SAR) for transmit arrays at 7T.

methodsA rapid electrodynamic simulation framework was used to calculate L-curves associated with excitation of a uniform 2D profile in a dielectric sphere. We used ultimate intrinsic SAR as an absolute performance reference to compare different transmit arrays in the presence and absence of a layer of HPM. We investigated the optimal permittivity for the HPM as a function of its thickness, the sample size, and the number of array elements.

resultsAdding a layer of HPM can improve the performance of a 24-element array to match that of a 48-element array without HPM, whereas a 48-element array with HPM can perform as well as a 64-element array without HPM. Optimal relative permittivity values changed based on sample and coil geometry, but were always within a range obtainable with readily available materials (ε

conclusionIntegration of HPMs could be a practical method to improve RF shimming performance, alternative to increasing the number of coils. The proposed simulation framework could be used to explore the design of novel transmit arrays for head imaging at ultra-high field strength. Magn Reson Med 80:391-399, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Indexed as

Radio WavesAlgorithmsComputer SimulationEquipment DesignHeadHumansImage EnhancementImage Processing, Computer-AssistedMagnetic FieldsMagnetic Resonance ImagingPhantoms, Imagingglobal SARhigh permittivity materialRF shimmingtransmit arrayUltimate intrinsic SAR

Identifiers

PMID29193307
PMCPMC5876092

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.