Evidence map›Paper›PMID 38651264›Full record

ArticleMagnetic resonance in medicine2024

Practical utilization of nonlinear spatial encoding: Fast field mapping and FRONSAC-wave.

Horace Z Zhang, R Todd Constable, Gigi Galiana

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. 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. Group-Patch Joint Compression: Compressing Dynamic BMagnetic resonance in medicine · 2026
    Article
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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

3 authors.

Horace Z ZhangDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.ORCID 0009-0001-1416-2380
R Todd ConstableDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
Gigi GalianaDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Practical Nonlinear Gradient Encoding for Enhanced Accelerated ImagingR01EB022030 · NIBIB · YALE UNIVERSITY · PI GALIANA, GIGI · 2017 to 2020
$1.5M
NCATS NIH HHS UL1 TR001863NIBIB NIH HHS R01 EB022030NIH HHS R01 EB022030
6 · The paper itself

Abstract

purposeTo study the additional value of FRONSAC encoding in 2D and 3D wave sequences, implementing a simple strategy to trajectory mapping for FRONSAC encoding gradients. THEORY AND

methodsThe nonlinear gradient trajectory for each voxel was estimated by exploiting the sparsity of the point spread function in the frequency domain. Simulations and in-vivo experiments were used to analyze the performance of combinations of wave and FRONSAC encoding.

resultsField mapping using the simplified approach produced similar image quality with much shorter calibration time than the comprehensive mapping schemes utilized in previous work. In-vivo human brain images showed that the addition of FRONSAC encoding could improve wave image quality, particularly at very high undersampling factors and in the context of limited wave amplitudes. These results were further supported by g-factor maps.

conclusionResults show that FRONSAC can be used to improve image quality of wave at very high undersampling rates or in slew-limited acquisitions. Our study illustrates the potential of the proposed fast field mapping approach.

Indexed as

AlgorithmsBrainMagnetic Resonance ImagingComputer SimulationHumansImage EnhancementImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedImaging, Three-DimensionalNonlinear DynamicsPhantoms, ImagingReproducibility of Resultsfield mappingFRONSACg‐factornonlinear spatial encodingwave

Identifiers

PMID38651264
PMCPMC11209788

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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.