Sci—Wed PM: Delivery—01: Clinically Viable Treatment Times with Dual‐slice Co‐60 Tomotherapy
Bibliographic record
Abstract
In the present study, we attempt to estimate clinical treatment times that might be achieved with dual‐slice Co‐60 tomotherapy delivery through an investigation of the advantages gained by reduced thread effect and pitch. The helical thread effect (off‐axis ripple), was simulated using a 30 wide cylindrical phantom in our PinnacleTM treatment planning system for various slice widths and pitch values. A cylindrical Co‐60 source of 2 cm diameter was studied along with a typical linac source for both single‐ and dual‐slice delivery. Treatment times were estimated based on a clinical Hi‐ARTTM tomotherapy head and neck treatment but with consideration of reduced output from the Co‐60 source, dual slice collimator and variation in slice width. We determine that dual‐slice tomotherapy delivery provides not only a reduction in treatment time due to an increase in the number of slices but also a reduction in the thread effect and effective pitch which may lead to improved modulation in the S‐I direction with larger slice widths. The net effect is a clinically viable treatment time that may be comparable with linac‐based IMRT with a conventional MLC. This initial study provides the impetus to support further investigations of plan quality and treatment times using dual‐slice Co‐60 tomotherapy.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".