Poster — Wed Eve—42: IMRT Dosimetry for Prostate, Breast and Head‐and‐Neck: Comparing Biologically Based Step‐and‐Shoot IMRT with Dynamic Helical Tomotherapy
Bibliographic record
Abstract
We have dosimetrically compared two treatment planning systems used in our clinic to create intensity‐modulated radiation therapy (IMRT) plans. A new commercial inverse treatment planning system (Monaco, CMS, Inc, St. Louis, Missouri) allowing Monte‐Carlo calculations, aperture based optimization, and biological cost functions was compared to the TomoTherapy Hi‐ART (Tomo‐Therapy, Madison, WI) planning system. Six clinical test cases (head and neck, prostate, and breast) were planned and compared using DVHs and dosimetric parameters (maximum dose, mean dose, conformity and homogeneity indexes). Both treatment planning systems provided adequate deliverable plans. Overall, tomotherapy plans provided a better conformality and dose homogeneity in most of the clinical cases also with improved sparing of major organs at risk. The dosimetric analysis shows that although the treatment planning systems have differences, they are each capable of producing substantially equivalent treatment plans in term of target coverage and normal tissue sparing.
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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) | 0.000 | 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) | 0.017 | 0.002 |
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".