SU-F-T-380: Comparing the Effect of Respiration On Dose Distribution Between Conventional Tangent Pair and IMRT Techniques for Adjuvant Radiotherapy in Early Stage Breast Cancer
Bibliographic record
Abstract
Purpose: In this project, we compared the conventional tangent pair technique to IMRT technique by analyzing the dose distribution. We also investigated the effect of respiration on planning target volume (PTV) dose coverage in both techniques. Methods: In order to implement IMRT technique a template based planning protocol, dose constrains and treatment process was developed. Two open fields with optimized field weights were combined with two beamlet optimization fields in IMRT plans. We compared the dose distribution between standard tangential pair and IMRT. The improvement in dose distribution was measured by parameters such as conformity index, homogeneity index and coverage index. Another end point was the IMRT technique will reduce the planning time for staff. The effect of patient's respiration on dose distribution was also estimated. The four dimensional computed tomography (4DCT) for different phase of breathing cycle was used to evaluate the effect of respiration on IMRT planned dose distribution. Results: We have accumulated 10 patients that acquired 4DCT and planned by both techniques. Based on the preliminary analysis, the dose distribution in IMRT technique was better than conventional tangent pair technique. Furthermore, the effect of respiration in IMRT plan was not significant as evident from the 95% isodose line coverage of PTV drawn on all phases of 4DCT. Conclusion: Based on the 4DCT images, the breathing effect on dose distribution was smaller than what we expected. We suspect that there are two reasons. First, the PTV movement due to respiration was not significant. It might be because we used a tilted breast board to setup patients. Second, the open fields with optimized field weights in IMRT technique might reduce the breathing effect on dose distribution. A further investigation is necessary.
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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 | 0.000 |
| 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) | 0.001 | 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".