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Record W2035641976 · doi:10.1118/1.4889645

TH‐C‐12A‐09: Planning and Delivery of the Fully Dynamic Trajectory Modulated Arc Therapy: Application to Accelerated Partial Breast Irradiation

2014· article· en· W2035641976 on OpenAlexaff
J. Liang, Todd Atwood, B Fahimian, E Chin, Karl F. Otto, Dimitre Hristov

Bibliographic record

VenueMedical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceTrajectoryNuclear medicineRadiation therapyRadiation treatment planningContouringIrradiationMedicinePhysicsSurgeryComputer graphics (images)

Abstract

fetched live from OpenAlex

Purpose: A novel trajectory modulated arc therapy (TMAT) system was developed that uses source motion trajectory involving synchronized gantry rotation with translational and rotational couch movement. MLC motion and dose rate were fully optimized for dynamic beam delivery. This work presents a platform for planning deliverable TMAT on a collision free coronal trajectory and evaluates its benefit for accelerated partial breast irradiation (APBI) in a prone position. Methods: The TMAT algorithm was built on VMAT with modifications (physical properties on couch movement were defined) and enhancements (pencil beam dose calculation engine to support extended SSDs) to make it feasible for TMAT delivery. A Matlab software environment for TMAT optimization and dose calculation was created to allow any user specified motion axis. TMAT delivery was implemented on Varian TrueBeamTM STx via XML scripts. 10 prone breast irradiation cases were evaluated in VMAT and compared with a 6‐ field non‐coplanar IMRT plan. Patient selection/exclusion criteria and structure contouring followed the guidelines of NSABP B‐39/RTOG 0413 protocol. Results: TMAT delivery time was ∼4.5 minutes. 251.5°±7.88° of non‐isocentric couch arc was achieved by the optimized trajectory with 180– 210 control points at 1°–2° couch increments. The improved dose distribution by TMAT was most clearly observed by the marked reduction in the volume of irradiated normal breast tissue in the high dose region. The ratios of the normal breast tissue volume receiving more than 50%, 80% and 100% of the prescription dose for TMAT versus IMRT were: V50%(TMAT/IMRT) = 78.38%±13.03%, V80%(TMAT/IMRT) = 44.19%±9.04% and V100% (TMAT/IMRT) = 9.96%±7.55%, all p≤0.01. Conclusion: The study is the first demonstration of planning and delivery implementation of a fully dynamic APBI TMAT system with continuous couch motion. TMAT achieved significantly improved dosimetry over noncoplanar IMRT on dose volume parameters correlated with toxicity and cosmetic outcome of APBI. This project was supported by Varian Research Grant.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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
GenreMethods

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

Citations0
Published2014
Admission routes1
Has abstractyes

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