Bibliographic record
Abstract
PURPOSE: The authors investigate the plan quality and treatment times that may be achieved with Co-60 tomotherapy delivery for clinical IMRT cases. METHODS: A research version of PINNACLE treatment planning system software (V9.1) enabled the authors to specify custom source profiles for modeling of cylindrical Co-60 sources. The calculated profiles were validated against measurements for simulated MLC leaf openings. The reduction in dose due to a partially obscured source was analyzed. The thread effect was investigated for a source of typical linac spot dimensions and 2.0 and 2.8 cm diameter cylindrical Co-60 sources. Co-60 tomotherapy plans for three clinical treatment sites--prostate, brain, and head-and-neck--were generated for the Co-60 sources and compared to linac-based segmental IMRT plans in terms of the DVHs produced. Treatment times were also determined. RESULTS: The custom source profile utility allowed the authors to obtain good agreement between calculated and measured profiles for simulated MLC leaf openings with the commercial Co-60 source. It was found that the thread effect is significantly reduced for Co-60 sources and is not a clinical concern even for the large slice width (4.8 cm) and pitch value (0.5) studied. Co-60 tomotherapy plans for three clinical treatment sites compared favorably to the original segmental IMRT plans in terms of the DVHs produced. Treatment times, comparable to the actual segmental IMRT treatment times, may be achieved for a high activity Co-60 source and dual-slice delivery may reduce these times further. CONCLUSIONS: It may be possible to achieve clinically viable treatment times with Co-60 tomo-therapy delivery without unacceptable loss of plan quality in terms of the DVHs produced.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".