Evidence map›Paper›PMID 41041652›Full record

ArticleIEEE access : practical innovations, open solutions2024

RF-induced Heating Estimation of a Stent in a 3T MRI using Transfer Function Approach with a Tabletop E-field Generator.

Hongbae Jeong, Joshua W Guag, Ananda Kumar

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

3 authors.

Hongbae JeongOffice of Science and Engineering Laboratories, Center for Devices Radiological Health, U. S. Food and Drug Administration, Silver Spring, MD 20993 USA.
Joshua W GuagOffice of Science and Engineering Laboratories, Center for Devices Radiological Health, U. S. Food and Drug Administration, Silver Spring, MD 20993 USA.
Ananda KumarOffice of Science and Engineering Laboratories, Center for Devices Radiological Health, U. S. Food and Drug Administration, Silver Spring, MD 20993 USA.

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

The use of a transfer function (TF) method enables a conservative estimation for radio frequency (RF) safety assessment of active implantable devices (AIMDs). The TF approach can be applied to various scan conditions, patient populations, and device trajectories inside the human body, reducing the computational burden of full-wave electromagnetic (EM) simulation. The in vitro TF model validation process is time-consuming, requiring tests in various sample trajectories that collectively exceed eight hours. Here, we demonstrated reducing the burden of the TF approach using a low-power tabletop E-field generator. We measured the TF of the stent via the piecewise excitation method at 128 MHz and validated it by exposing the device under diverse test exposure fields using a tabletop E-field generator that requires less phantom material, lower cost than whole-body coil or MRI scanner, and with reduced experimental safety hazards or shielded room requirements. The TF approach was used to predict radio frequency (RF)-induced power near the stent tip at 128 MHz and predicted values were then compared against measured values. We also used a body transmit coil to compare the conventional in vitro TF model validation approach and tabletop E-field generator. With the tabletop E-field generator, the equivalent absolute normalized error was (0.37 ± 0.31 dB) compared to the body transmit coil tests (0.43 ± 0.15 dB), and the required test time decreased from eight to three hours. In summary, we showed how a low-power compact E-field generator can be used for in vitro TF model validation with reduced testing time and cost without using a shielded room.

Indexed as

implantable device safetyMagnetic resonance imaging (MRI)MITS-TTMR safetyRegulatory science toolsspecific absorption rate (SAR)transfer function model validation

Identifiers

PMID41041652
PMCPMC12486246

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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.