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Record W2547747083 · doi:10.1002/mrm.26517

Direct SAR mapping by thermoacoustic imaging: A feasibility study

2016· article· en· W2547747083 on OpenAlexfundno aff
Simone Winkler, Paul A. Picot, Michael Thornton, Brian K. Rutt

Bibliographic record

VenueMagnetic Resonance in Medicine · 2016
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNatural Sciences and Engineering Research Council of CanadaGE HealthcareNational Institutes of Health
KeywordsSpecific absorption rateImaging phantomAcousticsTransducerSagittal planeExcitationComputer scienceThermoacousticsPhysicsEnergy (signal processing)Magnetic resonance imagingRadio frequencyOptics

Abstract

fetched live from OpenAlex

Purpose To develop a new method capable of directly measuring specific absorption rate (SAR) deposited in tissue using the thermoacoustic signal induced by short radiofrequency (RF) pulse excitation. Theory A detailed model based on the thermoacoustic wave generation and propagation is presented. Methods We propose a new concept for direct measurement of SAR, to be used as a safety assessment/monitoring tool for MRI. The concept involves the use of short bursts of RF energy and the measurement of the resulting thermoacoustic excitation pattern by an array of ultrasound transducers, followed by image reconstruction to yield the 3D SAR distribution. We developed a simulation framework to model this thermoacoustic SAR mapping concept and verified the concept in vitro. Results Simulations show good agreement between reconstructed and original SAR distributions with an error of 4.2, 7.2, and 8.4% of the mean SAR values in axial, sagittal, and coronal planes and support the feasibility of direct experimental mapping of SAR distributions in vivo. The in vitro experiments show good agreement with theory ( r 2 = 0.52). Conclusions A novel thermoacoustic method for in vivo mapping of local SAR patterns in MRI has been proposed and verified in simulation and in a phantom experiment. Magn Reson Med 78:1599–1606, 2017. © 2016 International Society for Magnetic Resonance in Medicine

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.013
GPT teacher head0.241
Teacher spread0.227 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2016
Admission routes1
Has abstractyes

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