Poster — Wed Eve—34: Design of a Primary Collimator for Cone Beam CT Imaging
Bibliographic record
Abstract
Intensity Modulated Radiation Therapy (IMRT) is becoming the standard of care for a number of cancer sites. Our research work has focused on developing Co‐60 based IMRT as an alternative for those areas in the world with limited infrastructure for supporting LINAC based systems. We have, to date, considered Co‐60 IMRT based on the tomotherapy approach because the full rotational delivery properties of tomotherapy helps to overcome the problems associated with the limited penetration of Co‐60 beams. However, with the recent introduction of arc based broad beam IMRT technology such as RapidArc (Varian Medical Systems, Palo Alto, CA), there is a potential for Co‐60 to be used in this approach. One potential advantage of broad beam versus fan beam Co‐60 IMRT delivery would be a reduction in the beam‐on time; a feature particularly important for a source that decays. Cone beam CT (CBCT) imaging is widely used for image guidance of broad‐beam IMRT and could likely play a role in a Co‐60 based broad beam IMRT system. The simplest and least complex design for such a system would consist of a single Co‐60 source for therapy and CBCT imaging. In this report we describe and analyze a new multileaf variable aperture primary collimator that permits a single Co‐60 source to be “switched” from therapy to a lower dose rate imaging mode. Monte carlo simulations of this design show that with a combination of altered aperture shape and an attenuator, an acceptable imaging dose rate without loss of spatial resolution is achieved.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".