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Record W2053009265 · doi:10.1118/1.4736370

TH-E-BRA-09: Radiation Induced Current Effects on MR Images from an Integrated Linac-MR System

2012· article· en· W2053009265 on OpenAlexaffabout
B Burke, Keith Wachowicz, B. G. Fallone, S Rathee

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLinear particle acceleratorImaging phantomNuclear medicinePhysicsRadiationOpticsSignal-to-noise ratio (imaging)Beam (structure)Medicine

Abstract

fetched live from OpenAlex

Purpose: During the real-time MR image acquisition of an integrated linac/MRI system, the MRI's RF coils is exposed to pulsed radiation resulting in radiation induced currents (RIC). This work will: (a) visualize the RIC signal as artefacts in k-space and determine its effect on MRI's signal-to-noise ratio (SNR), (b) examine the effects of linac repetition rate (MU/minute) and MRI imaging sequence parameter ‘TR’ on the RIC artefact, (c) use post processing methods to remove the unwanted RIC signal from the MR images. Methods: A small test phantom was imaged with no radiation first. Phantom imaging was then repeated concurrently with linac producing radiation at various repetition rates in two scenarios: (1) the radiation beam was incident on the RF coil unobstructed and (2) a lead block attenuated the radiation beam before reaching the RF coil. Scenario (1) was repeated by obtaining images for several values of TR. Finally, a post-processing algorithm was applied to the corrupted MR k-space data to remove the RIC artefact. Results: The RIC artefact presented as near vertical lines in k-space data for integer ratios of TR to linac pulsing period (rate =180 Hz). For non-integer ratios, the artefact lost its regular pattern and became random in appearance. The RIC artefact disappeared from the k-space data when the linac's radiation was blocked. The image SNR decreased with increasing linac repetition rate. The post-processing method was successful in restoring a significant fraction of the lost image SNR. Conclusions: Signal spikes observed in the k-space data are confirmed to result from RIC. The SNR reduction in MRI images, due to the RIC, is directly related to the linac repetition rate. The artefact's appearance depends on the relationship between linac pulse repetition rate and image sequence timing. Our post-processing algorithm allows the recovery of the lost image SNR. The financial support is provided by the Canadian Institute of Health Research operating grant # MOP 93752.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2012
Admission routes2
Has abstractyes

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