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Record W2154814927 · doi:10.4103/0971-6203.29194

Magnetic resonance imaging for adaptive cobalt tomotherapy: A proposal

2006· article· en· W2154814927 on OpenAlexaff
Tomas Kron, David Eyles, Jerry Battista

Bibliographic record

VenueJournal of Medical Physics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsTomotherapyMagnetic resonance imagingCobaltNuclear magnetic resonanceMedical physicsMedicineMaterials sciencePhysicsRadiologyRadiation therapy

Abstract

fetched live from OpenAlex

Magnetic resonance imaging (MRI) provides excellent soft tissue contrast for oncology applications. We propose to combine a MRI scanner with a helical tomotherapy (HT) system to enable daily target imaging for improved conformal radiation dose delivery to a patient. HT uses an intensity-modulated fan-beam that revolves around a patient, while the patient slowly advances through the plane of rotation, yielding a helical beam trajectory. Since the use of a linear accelerator to produce radiation may be incompatible with the pulsed radiofrequency and the high and pulsed magnetic fields required for MRI, it is proposed that a radioactive Cobalt-60 ((60)Co) source be used instead to provide the radiation. An open low field (0.25 T) MRI system is proposed where the tomotherapy ring gantry is located between two sets of Helmholtz coils that can generate a sufficiently homogenous main magnetic field.It is shown that the two major challenges with the design, namely acceptable radiation dose rate (and therefore treatment duration) and moving parts in strong magnetic field, can be addressed. The high dose rate desired for helical tomotherapy delivery can be achieved using two radiation sources of 220TBq (6000Ci) each on a ring gantry with a source to axis-of-rotation distance of 75 cm. In addition to this, a dual row multi-leaf collimator (MLC) system with 15 mm leaf width at isocentre and relatively large fan beam widths between 15 and 30 mm per row shall be employed. In this configuration, the unit would be well-suited for most pelvic radiotherapy applications where the soft tissue contrast of MRI will be particularly beneficial. Non-magnetic MRI compatible materials must be used for the rotating gantry. Tungsten, which is non-magnetic, can be used for primary collimation of the fan-beam as well as for the MLC, which allows intensity modulated radiation delivery. We propose to employ a low magnetic Cobalt compound, sycoporite (CoS) for the Cobalt source material itself.Rotational delivery is less susceptible to problems related to the use of a low energy megavoltage photon source while the helical delivery reduces the negative impact of the relatively large penumbra inherent in the use of Cobalt sources for radiotherapy. On the other hand, the use of a (60)Co source ensures constant dose rate with gantry rotation and makes dose calculation in a magnetic field as easy as the range of secondary electrons is limited.The MR-integrated Cobalt tomotherapy unit, dubbed 'MiCoTo,' uses two independent physical principles for image acquisition and treatment delivery. It would offer excellent target definition and will allow following target motion during treatment using fast imaging techniques thus providing the best possible input for adaptive radiotherapy. As an additional bonus, quality assurance of the radiation delivery can be performed in situ using radiation sensitive gels imaged by 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 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.007
GPT teacher head0.282
Teacher spread0.275 · 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 designTheoretical or conceptual
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

Citations34
Published2006
Admission routes1
Has abstractyes

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