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Record W2031570721 · doi:10.1088/0031-9155/55/16/s03

Monte Carlo evaluation of RapidArc™ oropharynx treatment planning strategies for sparing of midline structures

2010· article· en· W2031570721 on OpenAlexaff
K Bush, Sergei Zavgorodni, Isabelle Gagne, R Townson, W. Ansbacher, Wayne Beckham

Bibliographic record

VenuePhysics in Medicine and Biology · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of VictoriaBC Cancer Agency
Fundersnot available
KeywordsNuclear medicineRadiation treatment planningMonte Carlo methodMedicineMathematicsRadiation therapyStatisticsRadiology

Abstract

fetched live from OpenAlex

The aim of the study was to perform the Monte Carlo (MC) evaluation of RapidArc (Varian Medical Systems, Palo Alto, CA) dose calculations for four oropharynx midline sparing planning strategies. Six patients with squamous cell cancer of the oropharynx were each planned with four RapidArc head and neck treatment strategies consisting of single and double photon arcs. In each case, RTOG0522 protocol objectives were used during planning optimization. Dose calculations performed with the analytical anisotropic algorithm (AAA) are compared against BEAMnrc/DOSXYZnrc dose calculations for the 24-plan dataset. Mean dose and dose-to-98%-of-structure-volume (D(98%)) were used as metrics in the evaluation of dose to planning target volumes (PTVs). Mean dose and dose-to-2%-of-structure-volume (D(2%)) were used to evaluate dose differences within organs at risk (OAR). Differences in the conformity index (CI) and the homogeneity index (HI) as well as 3D dose distributions were also observed. AAA calculated PTV mean dose, D(98%), and HIs showed very good agreement with MC dose calculations within the 0.8% MC (statistical) calculation uncertainty. Regional node volume (PTV-80%) mean dose and D(98%) were found to be overestimated (1.3%, sigma = 0.8% and 2.3%, sigma = 0.8%, respectively) by the AAA with respect to MC calculations. Mean dose and D(2%) to OAR were also observed to be consistently overestimated by the AAA. Increasing dose calculation differences were found in planning strategies exhibiting a higher overall fluence modulation. From the plan dataset, the largest local dose differences were observed in heavily shielded regions and within the esophageal and sinus cavities. AAA dose calculations as implemented in RapidArc demonstrate excellent agreement with MC calculations in unshielded regions containing moderate inhomogeneities. Acceptable agreement is achieved in regions of increased MLC shielding. Differences in dose are attributed to inaccuracies in the AAA-modulated fluence modeling, modeling of material inhomogeneities and dose deposition within low-density materials. The use of MC dose calculations leads to the same general conclusion as using AAA that a two arc delivery with limited collimator opening can provide the greatest amount of midline sparing compared to the other techniques investigated.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.205
GPT teacher head0.463
Teacher spread0.258 · 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 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".

Quick stats

Citations15
Published2010
Admission routes1
Has abstractyes

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