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Record W2174611429 · doi:10.1120/jacmp.v16i6.5642

Quantification of dose differences between two versions of Acuros XB algorithm compared to Monte Carlo simulations — the effect on clinical patient treatment planning

2015· article· en· W2174611429 on OpenAlexfundno aff
Jarkko Ojala, Mika Kapanen

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsnot available
FundersBC Cancer Agency
KeywordsMonte Carlo methodAlgorithmRadiation treatment planningComputer scienceMedical physicsMathematicsStatisticsMedicineRadiologyRadiation therapy

Abstract

fetched live from OpenAlex

A commercialized implementation of linear Boltzmann transport equation solver, the Acuros XB algorithm (AXB), represents a class of most advanced type 'c' photon radiotherapy dose calculation algorithms. The purpose of the study was to quantify the effects of the modifications implemented in the more recent version 11 of the AXB (AXB11) compared to the first commercial implementation, version 10 of the AXB (AXB10), in various anatomical regions in clinical treatment planning. Both versions of the AXB were part of Varian's Eclipse clinical treatment planning system and treatment plans for 10 patients were created using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc radiotherapy (VMAT). The plans were first created with the AXB10 and then recalculated with the AXB11 and full Monte Carlo (MC) simulations. Considering the full MC simulations as reference, a DVH analysis for gross tumor and planning target volumes (GTV and PTV) and organs at risk was performed, and also 3D gamma agreement index (GAI) values within a 15% isodose region and for the PTV were determined. Although differences up to 12% in DVH analysis were seen between the MC simulations and the AXB, based on the results of this study no general conclusion can be drawn that the modifications made in the AXB11 compared to the AXB10 would imply that the dose calculation accuracy of the AXB10 would be inferior to the AXB11 in the clinical patient treatment planning. The only clear improvement with the AXB11 over the AXB10 is the dose calculation accuracy in air cavities. In general, no large deviations are present in the DVH analysis results between the two versions of the algorithm, and the results of 3D gamma analysis do not favor one or the other. Thus it may be concluded that the results of the comprehensive studies assessing the accuracy of the AXB10 may be extended to the AXB11.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.118
GPT teacher head0.449
Teacher spread0.332 · 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 designOther design
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

Citations25
Published2015
Admission routes1
Has abstractyes

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