Evidence map›Paper›PMID 25800547›Full record

ArticleMagnetic resonance in medicine2016

Gradient-modulated SWIFT.

Jinjin Zhang, Djaudat Idiyatullin, Curtis A Corum, Naoharu Kobayashi, Michael Garwood

Open access · bronzeAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

11 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Silent zero TE MR neuroimaging: Current state-of-the-art and future directions.Progress in nuclear magnetic resonance spectroscopy · 2021
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Advanced MRI Techniques for the Ankle.AJR. American journal of roentgenology · 2017
    Review
  8. Article
  9. Article
  10. Article
  11. Gradient-Modulated PETRA MRI.Tomography (Ann Arbor, Mich.) · 2015
    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

5 authors at 2 institutions in 1 country.

Jinjin ZhangCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Djaudat IdiyatullinCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Curtis A CorumCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Naoharu KobayashiCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Michael GarwoodCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
University of Minnesota · USResonance Research (United States) · US

Funding

NMR Imaging and SpectroscopyP41EB015894 · NIBIB · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2017
$8.4M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)KL2TR000113 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$5.4M
Next Generation Pediatric Neuroimaging (NGPN) DevelopmentR44MH122028 · NIMH · CHAMPAIGN IMAGING, LLC · PI Curtis Andrew Corum · 2024 to 2026
$4.3M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)KL2RR033182 · NCRR · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2011 to 2011
$1.4M
4 Tesla Human MRI/MRS Console UpgradeS10RR023730 · NCRR · UNIVERSITY OF MINNESOTA · PI GARWOOD, MICHAEL G · 2007 to 2007
$500k
High Performance Gradient and Shim System for a 4T Human MR ScannerS10RR027290 · NCRR · UNIVERSITY OF MINNESOTA · PI TKAC, IVAN · 2010 to 2010
$500k
NCATS NIH HHS KL2 TR000113NCATS NIH HHS KL2TR000113NCRR NIH HHS KL2 RR033182NCRR NIH HHS S10RR0027290NCRR NIH HHS S10 RR023730NCRR NIH HHS S10RR023730NCRR NIH HHS S10 RR027290NIBIB NIH HHS P41 EB015894NIBIB NIH HHS P41EB015894NIMH NIH HHS R44 MH122028
6 · The paper itself

Abstract

purposeMethods designed to image fast-relaxing spins, such as sweep imaging with Fourier transformation (SWIFT), often utilize high excitation bandwidth and duty cycle, and in some applications the optimal flip angle cannot be used without exceeding safe specific absorption rate (SAR) levels. The aim is to reduce SAR and increase the flexibility of SWIFT by applying time-varying gradient-modulation (GM). The modified sequence is called GM-SWIFT. THEORY AND

methodsThe method known as gradient-modulated offset independent adiabaticity was used to modulate the radiofrequency (RF) pulse and gradients. An expanded correlation algorithm was developed for GM-SWIFT to correct the phase and scale effects. Simulations and phantom and in vivo human experiments were performed to verify the correlation algorithm and to evaluate imaging performance.

resultsGM-SWIFT reduces SAR, RF amplitude, and acquisition time by up to 90%, 70%, and 45%, respectively, while maintaining image quality. The choice of GM parameter influences the lower limit of short T2 (*) sensitivity, which can be exploited to suppress unwanted image haze from unresolvable ultrashort T2 (*) signals originating from plastic materials in the coil housing and fixatives.

conclusionsGM-SWIFT reduces peak and total RF power requirements and provides additional flexibility for optimizing SAR, RF amplitude, scan time, and image quality.

Indexed as

AlgorithmsAnkleBrainComputer SimulationFourier AnalysisHumansImage EnhancementImage Processing, Computer-AssistedMagnetic Resonance ImagingPhantoms, ImagingToothfast relaxing spinsfrequency sweepGOIAgradient modulationSARSWIFTultrashort T2VERSE

Identifiers

PMID25800547
PMCPMC5466705
OpenAlexW1885828201

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.