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ZENODO
Software . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2020
License: CC BY
Data sources: ZENODO
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Heating risk evaluation for MRI on patients with hip, knee and shoulder arthroplasty

Authors: Clementi, Valeria; Zanovello, Umberto; Arduino, Alessandro; Ancarani, Cristina; Baruffaldi, Fabio; Bordini, Barbara; Chiampi, Mario; +2 Authors

Heating risk evaluation for MRI on patients with hip, knee and shoulder arthroplasty

Abstract

The script is intended to provide an estimation of the RF and GC exposing conditions following the execution of realistic MR pulse sequences. Starting from electromagnetic simulation results, which can be supplied by the user as described below and involve any generic metallic implant placed in an homogeneous phantom, the script is able to process the input data to provide estimation of SAR and temperature increase following the RF and GC interactions with the implant respectively. Whole-body SAR and 10 g maximum local SAR are averaged both over the MR pulse sequence duration and a reference time (e.g. 6 minutes) to represent RF exposing indicators. Similarly, the temperature increase due to the eddy currents induced within the implant by the switching GCs, is computed at the end of the sequence execution and at steady-state to represent the GC exposing indicator. The whole package is composed of six Python files: main.py, compAlpha90.py, fillXlsFile.py, GC_comp.py, RF_comp.py, RFPulseEnergy.py. Each file performs specific operations which are managed by the main.py module. In addition to the six Python files, the package come along with four directories: RF, GC, Results, Template. These directories are used to collect the RF input data, the GC input data, the results provided by the script and the .xlsx template file respectively.

The results here reported have been developed in the framework of the 17IND01 MIMAS Project. This project has received funding from the EMPIR Programme, co-financed by the Participating States and from the European Union's Horizon 2020 Research and Innovation Programme. Funder ID: 10.13039/100014132

Keywords

Gradient coil heating, MRI safety, Orthopaedic implants, Radiofrequency heating, MRI heating risk

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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