Evidence map›Paper›PMID 30094874›Full record

ArticleMagnetic resonance in medicine2019

Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

Mathias Davids, Bastien Guérin, Axel Vom Endt, Lothar R Schad, Lawrence L Wald

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
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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 4 institutions in 2 countries.

Mathias DavidsComputer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, BW, Germany.
Bastien GuérinMartinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts.
Axel Vom EndtSiemens Healthcare, Erlangen, Germany.
Lothar R SchadComputer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, BW, Germany.
Lawrence L WaldMartinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts.
University Medical Centre Mannheim · DEHarvard–MIT Division of Health Sciences and Technology · USHarvard University · USSiemens Healthcare (Germany) · DE

Funding

MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNERU01EB025162 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEINBERG, DAVID ALAN, LIU, CHUNLEI · 2017 to 2021
$13.4M
A magnetic particle imager (MPI) for functional brain imaging in humansU01EB025121 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI WALD, LAWRENCE L · 2017 to 2022
$6.1M
Magnetic Particle Imaging (MPI) for Functional Brain Imaging in HumansR24MH106053 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI CONOLLY, STEVEN M, GRISWOLD, MARK · 2014 to 2016
$1.5M
Neuroimaging of deep brain stimulation patients using safe MRI excitationsR00EB019482 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI GUERIN, BASTIEN · 2017 to 2019
$747k
Neuroimaging of deep brain stimulation patients using safe MRI excitationsK99EB019482 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI GUERIN, BASTIEN · 2015 to 2016
$188k
NIBIB NIH HHS K99 EB019482NIBIB NIH HHS R00 EB019482NIBIB NIH HHS R00EB019482NIBIB NIH HHS R24MH106053NIBIB NIH HHS U01 EB025121NIBIB NIH HHS U01EB025121NIBIB NIH HHS U01 EB025162NIBIB NIH HHS U01EB025162NIMH NIH HHS R24 MH106053
6 · The paper itself

Abstract

purposeAs gradient performance increases, peripheral nerve stimulation (PNS) is becoming a significant constraint for fast MRI. Despite its impact, PNS is not directly included in the coil design process. Instead, the PNS characteristics of a gradient are assessed on healthy subjects after prototype construction. We attempt to develop a tool to inform coil design by predicting the PNS thresholds and activation locations in the human body using electromagnetic field simulations coupled to a neurodynamic model. We validate the approach by comparing simulated and experimentally determined thresholds for 3 gradient coils.

methodsWe first compute the electric field induced by the switching fields within a detailed electromagnetic body model, which includes a detailed atlas of peripheral nerves. We then calculate potential changes along the nerves and evaluate their response using a neurodynamic model. Both a male and female body model are used to study 2 body gradients and 1 head gradient.

resultsThere was good agreement between the average simulated thresholds of the male and female models with the experimental average (normalized root-mean-square error: <10% and <5% in most cases). The simulation could also interrogate thresholds above those accessible by the experimental setup and allowed identification of the site of stimulation.

conclusionsOur simulation framework allows accurate prediction of gradient coil PNS thresholds and provides detailed information on location and "next nerve" thresholds that are not available experimentally. As such, we hope that PNS simulations can have a potential role in the design phase of high performance MRI gradient coils.

Indexed as

Electric StimulationElectromagnetic FieldsMagnetic Resonance ImagingAlgorithmsComputer SimulationEquipment DesignFemaleHumansMaleModels, AnatomicNeuronsPeripheral NervesPeripheral Nervous SystemReproducibility of Resultselectromagnetic field simulationEM exposure safetymagnetostimulation thresholdsMRI gradient coil switchingneurodynamic modelperipheral nerve stimulation

Identifiers

PMID30094874
PMCPMC6258337
OpenAlexW2885906446

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.