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Record W1889221772 · doi:10.1118/1.4921020

A generic high-dose rate<sup>192</sup>Ir brachytherapy source for evaluation of model-based dose calculations beyond the TG-43 formalism

2015· article· en· W1889221772 on OpenAlexaff
Facundo Ballester, Åsa Carlsson Tedgren, Domingo Granero, Annette Haworth, Firas Mourtada, Gabriel Paiva Fonseca, K. Zourari, Panagiotis Papagiannis, Mark J. Rivard, Frank‐André Siebert, Ron S. Sloboda, R. L. Smith, Rowan M. Thomson, Frank Verhaegen, J. Vijande, Yunzhi Ma, Luc Beaulieu

Bibliographic record

VenueMedical Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversité LavalCarleton UniversityMcGill University Health CentreUniversity of Alberta
Fundersnot available
KeywordsBrachytherapyImaging phantomDosimetryMonte Carlo methodRadiation treatment planningNuclear medicineTask groupComputer scienceMedical physicsDICOMMedical imagingPhysicsMathematicsRadiation therapyMedicineEngineeringStatisticsArtificial intelligenceRadiology

Abstract

fetched live from OpenAlex

PURPOSE: In order to facilitate a smooth transition for brachytherapy dose calculations from the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) formalism to model-based dose calculation algorithms (MBDCAs), treatment planning systems (TPSs) using a MBDCA require a set of well-defined test case plans characterized by Monte Carlo (MC) methods. This also permits direct dose comparison to TG-43 reference data. Such test case plans should be made available for use in the software commissioning process performed by clinical end users. To this end, a hypothetical, generic high-dose rate (HDR) (192)Ir source and a virtual water phantom were designed, which can be imported into a TPS. METHODS: A hypothetical, generic HDR (192)Ir source was designed based on commercially available sources as well as a virtual, cubic water phantom that can be imported into any TPS in DICOM format. The dose distribution of the generic (192)Ir source when placed at the center of the cubic phantom, and away from the center under altered scatter conditions, was evaluated using two commercial MBDCAs [Oncentra(®) Brachy with advanced collapsed-cone engine (ACE) and BrachyVision ACUROS™ ]. Dose comparisons were performed using state-of-the-art MC codes for radiation transport, including ALGEBRA, BrachyDose, GEANT4, MCNP5, MCNP6, and PENELOPE2008. The methodologies adhered to recommendations in the AAPM TG-229 report on high-energy brachytherapy source dosimetry. TG-43 dosimetry parameters, an along-away dose-rate table, and primary and scatter separated (PSS) data were obtained. The virtual water phantom of (201)(3) voxels (1 mm sides) was used to evaluate the calculated dose distributions. Two test case plans involving a single position of the generic HDR (192)Ir source in this phantom were prepared: (i) source centered in the phantom and (ii) source displaced 7 cm laterally from the center. Datasets were independently produced by different investigators. MC results were then compared against dose calculated using TG-43 and MBDCA methods. RESULTS: TG-43 and PSS datasets were generated for the generic source, the PSS data for use with the ace algorithm. The dose-rate constant values obtained from seven MC simulations, performed independently using different codes, were in excellent agreement, yielding an average of 1.1109 ± 0.0004 cGy/(h U) (k = 1, Type A uncertainty). MC calculated dose-rate distributions for the two plans were also found to be in excellent agreement, with differences within type A uncertainties. Differences between commercial MBDCA and MC results were test, position, and calculation parameter dependent. On average, however, these differences were within 1% for ACUROS and 2% for ace at clinically relevant distances. CONCLUSIONS: A hypothetical, generic HDR (192)Ir source was designed and implemented in two commercially available TPSs employing different MBDCAs. Reference dose distributions for this source were benchmarked and used for the evaluation of MBDCA calculations employing a virtual, cubic water phantom in the form of a CT DICOM image series. The implementation of a generic source of identical design in all TPSs using MBDCAs is an important step toward supporting univocal commissioning procedures and direct comparisons between TPSs.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.036
GPT teacher head0.330
Teacher spread0.293 · 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 designSimulation or modeling
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".

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Citations85
Published2015
Admission routes1
Has abstractyes

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