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Record W3011347570 · doi:10.1088/1361-6560/ab8148

Alanine dosimetry in strong magnetic fields: use as a transfer standard in MRI-guided radiotherapy

2020· article· en· W3011347570 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysics in Medicine and Biology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRadiation Effects and Dosimetry
Canadian institutionsUniversité de Montréal
FundersCancer Research UK
KeywordsDosimetryDosimeterMagnetic fieldNuclear magnetic resonanceAlanineIrradiationMagnetic resonance imagingIonizing radiationAbsorbed doseMonte Carlo methodMaterials scienceElectron paramagnetic resonancePhysicsNuclear medicineChemistryNuclear physicsMedicineMathematicsRadiologyStatistics

Abstract

fetched live from OpenAlex

Abstract Reference dosimetry in the presence of a strong magnetic field is challenging. Ionisation chambers have shown to be strongly affected by magnetic fields. There is a need for robust and stable detectors in MRI-guided radiotherapy (MRIgRT). This study investigates the behaviour of the alanine dosimeter in magnetic fields and assesses its suitability to act as a reference detector in MRIgRT. Alanine pellets were loaded in a waterproof holder, placed in an electromagnet and irradiated by 60 Co and 6 MV and 8 MV linac beams over a range of magnetic flux densities. Monte Carlo simulations were performed to calculate the absorbed dose, to water and to alanine, with and without magnetic fields. Combining measurements with simulations, the effect of magnetic fields on alanine response was quantified and a correction factor for the presence of magnetic fields on alanine was determined. This study finds that the response of alanine to ionising radiation is modified when the irradiation is in the presence of a magnetic field. The effect is energy independent and may increase the alanine/electron paramagnetic resonance (EPR) signal by 0.2% at 0.35 T and 0.7% at 1.5 T. In alanine dosimetry for MRIgRT, this effect, if left uncorrected, would lead to an overestimate of dose. Accordingly, a correction factor, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>k</mml:mi> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>Q</mml:mi> <mml:mi>B</mml:mi> </mml:msub> </mml:mrow> <mml:mo>,</mml:mo> <mml:mi>Q</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , is defined. Values are obtained for this correction as a function of magnetic flux density, with a standard uncertainty which depends on the magnetic field and is 0.6% or less. The strong magnetic field has a measurable effect on alanine dosimetry. For alanine which is used to measure absorbed dose to water in a strong magnetic field, but which has been calibrated in the absence of a magnetic field, a small correction to the reported dose is required. With the inclusion of this correction, alanine/EPR is a suitable reference dosimeter for measurements in MRIgRT.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.232

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 head0.128
GPT teacher head0.340
Teacher spread0.211 · 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