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Record W1727354557 · doi:10.1120/jacmp.v11i1.3114

Analysis of RapidArc optimization strategies using objective function values and dose‐volume histograms

2009· article· en· W1727354557 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsVolume (thermodynamics)Nuclear medicineDose-volume histogramHistogramMedical physicsMedicineMathematicsComputer scienceRadiologyRadiation therapyPhysicsRadiation treatment planningArtificial intelligence

Abstract

fetched live from OpenAlex

RapidArc is a novel treatment planning and delivery system that has recently been made available for clinical use. Included within the Eclipse treatment planning system are a number of different optimization strategies that can be employed to improve the quality of the final treatment plan. The purpose of this study is to systematically assess three categories of strategies for four phantoms, and then apply proven strategies to clinical head and neck cases. Four phantoms were created within Eclipse with varying shapes and locations for the planning target volumes and organs at risk. A baseline optimization consisting of a single 359.8 degrees arc with collimator at 45 degrees was applied to all phantoms. Three categories of strategies were assessed and compared to the baseline strategy. They include changing the initialization parameters, increasing the total number of control points, and increasing the total optimization time. Optimization log files were extracted from the treatment planning system along with final dose-volume histograms for plan assessment. Treatment plans were also generated for four head and neck patients to determine whether the results for phantom plans can be extended to clinical plans. The strategies that resulted in a significant difference from baseline were: changing the maximum leaf speed prior to optimization ( p < 0.05), increasing the total number of segments by adding an arc ( p < 0.05), and increasing the total optimization time by either continuing the optimization ( p < 0.01) or adding time to the optimization by pausing the optimization ( p < 0.01). The reductions in objective function values correlated with improvements in the dose-volume histogram (DVH). The addition of arcs and pausing strategies were applied to head and neck cancer cases, which demonstrated similar benefits with respect to the final objective function value and DVH. Analysis of the optimization log files is a useful way to intercompare treatment plans that have the same dose-volume objectives and importance values. The results for clinical head and neck plans were consistent with phantom plans.

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.

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: none
Teacher disagreement score0.862
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.021
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