Evidence map›Paper›PMID 31745756›Full record

ArticleMagma (New York, N.Y.)2020

Modeling radiofrequency responses of realistic multi-electrode leads containing helical and straight wires.

Mikhail Kozlov, Marc Horner, Wolfgang Kainz

Abstract read
In one paragraph

Article in Magma (New York, N.Y.), 2020. 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

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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. 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.

Mikhail KozlovMax Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany. kozlov@cbs.mpg.de.ORCID http://orcid.org/0000-0003-1702-4140
Marc HornerANSYS, Inc, Evanston, IL, USA.ORCID https://orcid.org/0000-0002-2483-5796
Wolfgang KainzDivision of Biomedical Physics, Office of Science and Engineering Laboratories, U.S. FDA, CDRH, Silver Spring, MD, USA.ORCID https://orcid.org/0000-0002-9165-4135

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo present a modeling workflow for the evaluation of a lead electromagnetic model (LEM) consisting of a transfer function (TF) and a calibration factor. The LEM represents an analytical relationship between the RF response of a lead and the incident electromagnetic field. The study also highlights the importance of including key geometric details of the lead and the electrode when modeling multi-electrode leads.

methodsThe electrical and thermal responses of multi-electrode leads with helical and straight wires were investigated using 3D electromagnetic (EM) and thermal co-simulations. The net dissipated power (P) around each lead electrode and the net temperature increase at the electrodes (ΔT) were obtained for a set of incident EM fields with different spatial distributions. A reciprocity approach was used to determine a TF for each electrode based on the results of the computational model. The evaluation of the calibration factors and the TF validation were performed using the linear regression of P versus the LEM predictions.

resultsP and ΔT were investigated for four multi-electrode leads and four single-electrode leads containing either helical or straight wires. All electrodes of the multi-electrode lead were found to be points of high power deposition and temperature rise. The LEMs for the individual electrodes varied substantially. A significant dependence of the calibration factors on the surrounding tissue medium was also found. Finally, the model showed that the TF, the calibration factor, P and ΔT for multi-electrode leads differ significantly from those for single-electrode leads.

conclusionThese results highlight the need to evaluate a LEM for each electrode of a multi-electrode lead as well as for each possible surrounding medium. It is also shown that the results derived from simulations based on simplified single-electrode leads can significantly mislead multi-electrode lead analyses.

Indexed as

ElectrodesRadio WavesAlgorithmsAnimalsCalibrationComputer SimulationElectrodes, ImplantedElectromagnetic FieldsHot TemperatureHumansMagnetic Resonance ImagingPattern Recognition, AutomatedTemperatureComputational modelingFinite element method (FEM)Implanted medical deviceRF simulationsTissue heating

Identifiers

PMID31745756
PMCPMC7230065

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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.