Dosimetric evaluation of breast radiotherapy in a dynamic phantom
Bibliographic record
Abstract
This phantom study quantifies changes in delivered dose due to respiratory motion for four breast radiotherapy planning techniques: three intensity-modulated techniques (forward-planned, surface-compensated and hybrid intensity-modulated radiation therapy (IMRT)); using a combination of open fields and inverse planned IMRT) and a 2D conventional technique. The plans were created on CT images of a wax breast phantom with a cork lung insert, and dose distributions were measured using films inserted through slits in the axial and sagittal planes. Films were irradiated according to each plan under a static (modeling breathhold) and three dynamic conditions--isocenter set at mid-respiratory cycle with motion amplitudes of 1 and 2 cm and at end-cycle with 2 cm motion amplitude (modeling end-exhale). Differences between static and moving deliveries were most pronounced for the more complex planning techniques with hot spots of up to 107% appearing in the anterior portion of all three IMRT plans at the largest motion at the end-exhale set-up. The delivered dose to the moving phantom was within 5% of that to the static phantom for all cases, while measurement accuracy was ±3%. The homogeneity index was significantly decreased only for the 2 cm motion end-exhale set-up; however, this same motion increased the equivalent uniform dose because of improved posterior breast coverage. Overall, the study demonstrates that the effect of respiratory motion is negligible for all planning techniques except in occasional instances of large motion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".