Investigation of dose homogeneity for loose helical tomotherapy delivery in the context of breath-hold radiation therapy
Bibliographic record
Abstract
Loose helical delivery is a potential solution to account for respiration-driven tumour motion in helical tomotherapy (HT). In this approach, a treatment is divided into a set of interlaced 'loose' helices commencing at different gantry angles. Each loose helix covers the entire target length in one gantry rotation during a single breath-hold. The dosimetric characteristics of loose helical delivery were investigated by delivering a 6 MV photon beam in a HT-like manner. Multiple scenarios of conventional 'tight' HT and loose helical deliveries were modelled in treatment planning software, and carried out experimentally with Kodak EDR2 film. The advantage of loose helical delivery lies in its ability to produce a more homogeneous dose distribution by eliminating the 'thread' effect-an inherent characteristic of HT, which results in dose modulations away from the axis of gantry rotation. However, loose helical delivery was also subjected to undesirable dose modulations in the direction of couch motion (termed 'beating' effect), when the ratio between the number of beam projections per gantry rotation (n) and pitch factor (p) was a non-integer. The magnitude of dose modulations decreased with an increasing n/p ratio. The results suggest that for the current HT unit (n = 51), dose modulations could be kept under 5% by selecting a pitch factor smaller than 7. A pitch factor of this magnitude should be able to treat a target up to 30 cm in length. Loose helical delivery should increase the total session time only by a factor of 2, while the planning time should stay the same since the total number of beam projections remains unchanged. Considering its dosimetric advantage and clinical practicality, loose helical delivery is a promising solution for the future HT treatments of respiration-driven targets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".