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Record W2007071100 · doi:10.1118/1.2722471

Integral test phantom for dosimetric quality assurance of image guided and intensity modulated stereotactic radiotherapy

2007· article· en· W2007071100 on OpenAlexaff
D. Létourneau, H. Keller, Michael B. Sharpe, David A. Jaffray

Bibliographic record

VenueMedical Physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
FundersSun Nuclear Corporation
KeywordsImaging phantomQuality assuranceDosimetryMultileaf collimatorIonization chamberRadiosurgeryLinear particle acceleratorImage qualityCollimatorRadiation treatment planningIntensity modulationNuclear medicineCalibrationReproducibilityMedical physicsMedical imagingOpticsBeam (structure)Radiation therapyPhysicsMedicineComputer scienceRadiologyMathematicsComputer visionImage (mathematics)

Abstract

fetched live from OpenAlex

The objective of this work is to develop a dosimetric phantom quality assurance (QA) of linear accelerators capable of cone-beam CT (CBCT) image guided and intensity-modulated radiotherapy (IG-IMRT). This phantom is to be used in an integral test to quantify in real-time both the performance of the image guidance and the dose delivery systems in terms of dose localization. The prototype IG-IMRT QA phantom consisted of a cylindrical imaging phantom (CatPhan) combined with an array of 11 radiation diodes mounted on a 10 cm diameter disk, oriented perpendicular to the phantom axis. Basic diode response characterization was performed for 6 and 18 MV photons. The diode response was compared to planning system calculations in the open and penumbrae regions of simple and complex beam arrangements. The clinical use of the QA phantom was illustrated in an integral test of an IG-IMRT treatment designed for a clinical spinal radiosurgery case. The sensitivity of the phantom to multileaf collimator (MLC) calibration and setup errors in the clinical setting was assessed by introducing errors in the IMRT plan or by displacing the phantom. The diodes offered good response linearity and long-term reproducibility for both 6 and 18 MV. Axial dosimetry of coplanar beams (in a plane containing the beam axes) was made possible with the nearly isoplanatic response of the diodes over 360 degrees of gantry (usually within +/-1%). For single beam geometry, errors in phantom placement as small as 0.5 mm could be accurately detected (in gradient > or = 1% /mm). In clinical setting, MLC systematic errors of 1 mm on a single MLC bank introduced in the IMRT plan were easily detectable with the QA phantom. The QA phantom demonstrated also sufficient sensitivity for the detection of setup errors as small as 1 mm for the IMRT delivery. These results demonstrated that the prototype can accurately and efficiently verify the entire IG-IMRT process. This tool, in conjunction with image guidance capabilities has the potential to streamline this QA process and improve the level of performance of image guided and intensity modulated radiotherapy.

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)0.002
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.350
Teacher spread0.329 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

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