A two isocenter IMRT technique with a controlled junction dose for long volume targets
Bibliographic record
Abstract
Most IMRT techniques have been designed to treat targets smaller than the field size of conventional linac accelerators. In order to overcome the field size restrictions in applying IMRT, we developed a two isocenter IMRT technique to treat long volume targets. The technique exploits an extended dose gradient throughout a junction region of 4-6 cm to minimize the impact of field match errors on a junction dose and manipulates the inverse planning and IMRT segments to fill in the dose gradient and achieve dose uniformity. Techniques for abutting both conventional fields with IMRT ('Static + IMRT') and IMRT fields ('IMRT + IMRT') using two separate isocenters have been developed. Five long volume sarcoma cases have been planned in Pinnacle (Philips, Madison, USA) using Elekta Synergy and Varian 2100EX linacs; two of the cases were clinically treated with this technique. Advantages were demonstrated with well-controlled junction target uniformity and tolerance to setup uncertainties. The junction target dose heterogeneity was controlled at a level of +/-5%; for 3 mm setup errors at the field edges, the junction target dose changed less than 5% and the dose sparing to organs at risk (OARs) was maintained. Film measurements confirmed the treatment planning results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".