Monte Carlo calculation of helical tomotherapy dose delivery
Bibliographic record
Abstract
Helical tomotherapy delivers intensity modulated radiation therapy using a binary multileaf collimator (MLC) to modulate a fan beam of radiation. This delivery occurs while the linac gantry and treatment couch are both in constant motion, so the beam describes, from a patient/phantom perspective, a spiral or helix of dose. The planning system models this continuous delivery as a large number (51) of discrete gantry positions per rotation, and given the small jaw/fan width setting typically used (1 or 2.5 cm) and the number of overlapping rotations used to cover the target (pitch often <0.5), the treatment planning system (TPS) potentially employs a very large number of static beam directions and leaf opening configurations to model the modulated fields. All dose calculations performed by the system employ a convolution/superposition model. In this work the authors perform a full Monte Carlo (MC) dose calculation of tomotherapy deliveries to phantom computed tomography (CT) data sets to verify the TPS calculations. All MC calculations are performed with the EGSnrc-based MC simulation codes, BEAMnrc and DOSXYZnrc. Simulations are performed by taking the sinogram (leaf opening versus time) of the treatment plan and decomposing it into 51 different projections per rotation, as does the TPS, each of which is segmented further into multiple MLC opening configurations, each with different weights that correspond to leaf opening times. Then the projection is simulated by the summing of all of the opening configurations, and the overall rotational treatment is simulated by the summing of all of the projection simulations. Commissioning of the source model was verified by comparing measured and simulated values for the percent depth dose and beam profiles shapes for various jaw settings. The accuracy of the MLC leaf width and tongue and groove spacing were verified by comparing measured and simulated values for the MLC leakage and a picket fence pattern. The validated source and MLC configuration were then used to simulate a complex modulated delivery from fixed gantry angle. Further, a preliminary rotational treatment plan to a delivery quality assurance phantom (the "cheese" phantom) CT data set was simulated. Simulations were compared with measured results taken with an A1SL ionization chamber or EDR2 film measurements in a water tank or in a solid water phantom, respectively. The source and MLC MC simulations agree with the film measurements, with an acceptable number of pixels passing the 2%/1 mm gamma criterion. 99.8% of voxels of the MC calculation in the planning target volume (PTV) of the preliminary plan passed the 2%/2 mm gamma value test. 87.0% and 66.2% of the voxels in two organs at risk (OARs) passed the 2%/2 mm tests. For a 3%/3 mm criterion, the PTV and OARs show 100%, 93.2%, and 86.6% agreement, respectively. All voxels passed the gamma value test with a criterion of 5%/3 mm. The Tomo-Therapy TPS showed comparable results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".