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Record W2559920876 · doi:10.1002/mp.12036

A simple and robust trajectory‐based stereotactic radiosurgery treatment

2017· article· en· W2559920876 on OpenAlexafffund
Byron Wilson, Karl F. Otto, Ermias Gete

Bibliographic record

VenueMedical Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersBC Cancer AgencyVarian Medical Systems
KeywordsRadiosurgeryCollimatorTrajectoryLinear particle acceleratorMultileaf collimatorNuclear medicineIsocenterDosimetryArc (geometry)Radiation treatment planningPhysicsBeam (structure)Computer scienceOpticsRadiation therapyMathematicsImaging phantomMedicineRadiologyGeometry

Abstract

fetched live from OpenAlex

INTRODUCTION: We present a Trajectory-based Volumetric Modulated Arc Therapy (TVMAT) technique for Stereotactic Radiosurgery (SRS) that takes advantage of a modern linacs ability to modulate dose rate and move the couch dynamically. In addition, we investigate the quality of the developed TVMAT method and the dosimetric accuracy of the technique. METHODS: The main feature of the TVMAT technique is a standard beam trajectory formed by dynamic motion of the treatment couch and the linac gantry. The couch rotates slowly through 180 degrees while the gantry delivers radiation through continuous sweeps of the gantry. The number of partial arcs that constitute the trajectory can be varied between two and eight and as the number of partial arcs increases, the trajectory more finely samples 4π geometry. Along these trajectories, the multi-leaf collimator (MLC) and dose rate are optimized through an inverse planning framework. The TVMAT method was tested on ten cranial SRS patients who were previously treated with the Dynamic Conformal Arc (DCA) technique. The plans were compared with the DCA and a four- arc VMAT technique with regards to dose to the OAR, dose falloff, V12Gy, and V4Gy. Validation measurements were performed using ion-chamber and Gafchromic film. In addition, the trajectory-log files were analyzed and compared with the treatment plan beam data. RESULTS: The TVMAT treatment plans were successfully delivered with a treatment time between 3-8 min which mostly depended on total cumulated dose. Ion chamber measurements had an average measured error of 1.1 ± 0.6% and a maximum value of 2.2% of the delivered dose. The 2%, 2 mm gamma pass rates for the film measurements were 96% or greater. In a preliminary comparison of ten patients who underwent SRS treatments with the DCA technique, the TVMAT and VMAT techniques were able to produce plans with comparable dose falloff and OAR doses, while achieving better dose conformality, V4Gy and V12Gy when compared to the original DCA plans. The improvement of the TVMAT plans were as follows (mean % improvement ± standard err): Conformity (10 ± 2%), V4 (20 ± 20%), V12 (27 ± 10%), volume weighted mean dose to organs at risk (13 ± 13%), homogeneity index (2 ± 2%) and falloff (4 ± 2%). CONCLUSION: We have developed and validated a trajectory-based dose delivery method which has dose distribution improvements while having a treatment time of 3-8 min. In addition, it has the potential for a simpler planning experience while maintaining an accurate delivery on the Varian Truebeam Linac.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.008

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 head0.026
GPT teacher head0.302
Teacher spread0.276 · 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 designNot applicable
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".

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Citations22
Published2017
Admission routes2
Has abstractyes

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