A Novel Fluence Modified Base Plan IMRT forSecond-irradiation Planning Technique
Bibliographic record
Abstract
Purpose/Objective: Some patients with head and neck cancer are treated with intensity modulated radiation therapy (IMRT). We designated this as “firstirradiation”. If they later develop disease, “second-irradiation” therapy would be challenging. We have developed a technique that limits the cumulative dose to the spinal cord and brainstem while maximizing coverage of a new planning target volume (PTV) in the new treatment region. Materials and methods: Three patients who previously received IMRT and later developed a recurrence were selected to demonstrate this technique. A CT simulation scan was performed and then the original plan was applied. Fluence from outside of the spinal cord and brainstem with a 1.0 cm margin (SCBM) was removed. This modified plan was then used as a base plan for optimization. The original plan was summed with a new second-irradiation plan to evaluate the cumulative dose received by the spinal cord and brainstem. The second-irradiation plan alone was used to evaluate for coverage of the new PTV. Results: For all patients, the maximum cumulative doses to the spinal cord with 0.5 cm margin (SCM) and brainstem with 0.5 cm margin (BSM) met the National Cancer Institute of Canada Clinical Trials Group head and neck clinical protocol dose limitations. For the second-irradiation plan alone, 100% of the prescribed dose covered 95% of PTV. Conclusion: The use of a fluence modified IMRT plan as base plan is an effective planning technique that accounts for the cumulative dose to the spinal cord and brainstem while allowing coverage of a new PTV.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".