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Record W2016401035 · doi:10.1118/1.3481513

Effect of longitudinal magnetic fields on a simulated in‐line 6 MV linac

2010· article· en· W2016401035 on OpenAlexafffund
D. M. Santos, S Steciw, B. G. Fallone

Bibliographic record

VenueMedical Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Cancer Foundation
KeywordsLinear particle acceleratorMagnetic fieldPhysicsMonte Carlo methodOpticsField (mathematics)Magnetic resonance imagingNuclear magnetic resonanceComputational physicsBeam (structure)

Abstract

fetched live from OpenAlex

PURPOSE: Linac-magnetic resonance (MR) systems have been proposed in order to achieve realtime image guided radiotherapy. The design of a new linac-MR system with the in-line 6 MV linac generating x-rays along the symmetry axis of an open MR imager is outlined. This new design allows for a greater MR field strength to achieve better quality images while reducing hot and cold spots in treatment planning. An investigation of linac's performance in the longitudinal fringe magnetic fields of the MR imager is given. METHODS: The open MR imager fringe magnetic field was modeled using the analytic solution of the magnetic field generated from current carrying loops. The derived solution was matched to the magnetic fringe field isolines provided for a 0.5 T open MR imager through Monte Carlo optimization. The optimized field solution was then added to the previously validated 6 MV linac simulation to quantify linac's performance in the fringe magnetic field of a 0.5 T MR imager. To further the investigation, linac's performance in large fringe fields expected from other imagers was investigated through the addition of homogeneous longitudinal fields. RESULTS: The Monte Carlo optimization of the analytic current loop solution provided good agreement with the magnetic fringe field isolines supplied by the manufacturer. The range of magnetic fields the linac is expected to experience when coupled to the 0.5 T MR imager was determined to be from 0.0022 to 0.011 T (as calculated at the electron gun cathode). The effect of the longitudinal magnetic field on the electron beam was observed to be only in the electron gun. The longitudinal field changed the electron gun optics, affecting beam characteristics, such as a slight increase in the injection current and beam diameter, and an increasingly nonlaminar transverse phase space. Although the target phase space showed little change in its energy spectrum from the altered injection phase space, a reduction in the target current and spatial distribution peak intensity was observed. Despite these changes, the target phase space had little effect on the depth dose curves or dose profiles calculated for a 40 x 40 cm2 field at 1.5 cm depth. At longitudinal fields larger than 0.012 T, a drastic reduction in the injection current from the electron gun was observed due to a large fraction of electrons striking the anode. This further reduced the target current, which reached a minimum of 28 +/- 2 mA at 0.06 T. A slow increase in the injection and target currents was observed at fields larger than 0.06 T due to greater beam collimation in the anode beam tube. CONCLUSIONS: In an effort to achieve higher quality images and a reduction in hot and cold spots in the treatment plan, a parallel configuration linac-MR system is presented. The longitudinal magnetic fields of the MR imager caused large beam losses within the electron gun. These losses may be eliminated through a redesign of the electron gun optics incorporating a longitudinal magnetic field, or through magnetic shielding, which has already been proven successful for the transverse configuration.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.789

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 integrity0.0000.001
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 head0.005
GPT teacher head0.300
Teacher spread0.295 · 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 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

Citations32
Published2010
Admission routes2
Has abstractyes

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