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Record W4393034910 · doi:10.1109/tbme.2024.3379980

An 8-Channel Transceiver Coil for Carotid Artery Imaging at 7T Using an Optimized Shield Design

2024· article· en· W4393034910 on OpenAlexafffund
Pedram Yazdanbakhsh, Marcus J. Couch, Kyle M. Gilbert, Johnny Der Hovagimian, David A. Rudko, Richard D. Hoge

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsWestern UniversitySiemens (Canada)McGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchHealth CanadaSiemens HealthineersCanada First Research Excellence FundFondation Brain Canada
KeywordsShieldTransceiverElectromagnetic coilChannel (broadcasting)Carotid arteriesElectromagnetic interferenceBiomedical engineeringEngineeringElectronic engineeringElectrical engineeringMedicineCMOSSurgeryGeology

Abstract

fetched live from OpenAlex

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective:</i> To design and fabricate a transmit/receive (T/R) radiofrequency (RF) coil array for MRI of the carotid arteries at 7T with optimal shielding to improve transmit performance in parallel transmit (pTx) mode. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methods:</i> The carotid coil included 8 total RF elements, with left and right subarrays, each consisting of 4 overlapping loops with RF shields. Electromagnetic (EM) simulations were performed to optimize and improve the transmit performance of the array by determining the optimal distance between the RF shield and each subarray. EM simulations were further used to calculate local specific absorption rate (SAR) matrices. Based on the SAR matrices, virtual observation points (VOPs) were applied to ensure safety during parallel transmission. The efficacy of the coil design was evaluated by measuring coil performance metrics when imaging a phantom and by acquiring in-vivo images. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results:</i> The optimal distance between the RF shield and each subarray was determined to be 45 mm. This resulted in a maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> efficiency of 1.23 μT/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\surd W$</tex-math></inline-formula> in the carotid arteries and a peak, 10-g-average SAR per Watt of 0.86 kg<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> when transmitting in the nominal CP<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> mode. Optimizing the RF shield resulted in up to 37% improvement in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> efficiency and 14% improvement in SAR efficiency compared to an unshielded design. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion and significance:</i> Optimizing the distance between the RF shield and coil array provided significant improvement in the transmit characteristics of the bilateral carotid coil. The bilateral coil topology provides a compelling platform for imaging the carotid arteries with high field MRI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.307
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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