Evidence map›Paper›PMID 35468237›Full record

ArticleMagnetic resonance in medicine2022

Tracking of rigid head motion during MRI using an EEG system.

Malte Laustsen, Mads Andersen, Rong Xue, Kristoffer H Madsen, Lars G Hanson

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed, 13 citations in OpenAlex.

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  9. External Hardware and Sensors, for Improved MRI.Journal of magnetic resonance imaging : JMRI · 2023
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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

5 authors at 3 institutions in 3 countries.

Malte LaustsenSection for Magnetic Resonance, DTU Health Tech, Technical University of Denmark, Kgs. Lyngby, Denmark.ORCID 0000-0001-5914-711X
Mads AndersenPhilips Healthcare, Copenhagen, Denmark.ORCID 0000-0002-2702-1640
Rong XueUniversity of Chinese Academic of Sciences, Beijing, China.ORCID 0000-0001-7055-4939
Kristoffer H MadsenDanish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.ORCID 0000-0001-8606-7641
Lars G HansonSection for Magnetic Resonance, DTU Health Tech, Technical University of Denmark, Kgs. Lyngby, Denmark.ORCID 0000-0002-8204-6912
Amager Hospital · DKChinese Academy of Sciences · CNLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients. THEORY AND

methodsGradient switching during simultaneous EEG-fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high-impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators.

resultsHead-pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]-mm translation, [0.30 0.27 0.22]-degree rotation). Retrospective correction of 3D gradient-echo imaging shows an increase of average edge strength of 12%/-0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees).

conclusionMotion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.

Indexed as

ArtifactsMagnetic Resonance ImagingBrainEcho-Planar ImagingElectroencephalographyHead MovementsMotionRetrospective Studiesartifact correctionbrain MRIEEG systemmotion tracking methodprospective motion correction

Identifiers

PMID35468237
PMCPMC9325421
OpenAlexW4224857491

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.