SU‐E‐T‐521: Dosimetric Effect on Variation of Patient Size in Prostate Volumetric Modulated Arc Therapy
Bibliographic record
Abstract
PURPOSE: To evaluate dosimetric variations of planning target volume (PTV) on critical organs such as rectal wall, bladder and femoral head, when the patient size changes due to weight loss in prostate volumetric modulated arc therapy (VMAT). METHODS: ) prostate, selected from a group of 30 were planned for prostate VMAT using the 6 MV photon beam. Patient size reduction due to weight loss was modeled by contracting the external body contour with reduced depths (0.5 - 2 cm) in the anterior and both lateral directions. Original normal tissue excluded from the contracted body contour was replaced by air. Dose calculation was repeated with the same planned beam geometry and dose prescription. Dose-volume histograms, dose-volume points of the PTV, clinical target volume (CTV) and critical organs were calculated with variations of reduced depth. RESULTS: D99% of the PTV and CTV were found to have increased 2.65 ± 0.03% per cm and 2.75 ± 0.15% per cm of reduced depth in the range of 0.5 and 2 cm. D30% of the rectal wall and bladder increased 2.29 ± 0.12% per cm and 2.31 ± 0.83% per cm, respectively. D5% of the femoral head increased by 3.30 ± 0.11% per cm of reduced depth. Moreover, there was more than 5% increase of minimum, maximum and means doses for the PTV, CTV and critical organs when the reduced depth reached 2 cm. CONCLUSIONS: This study provided estimated results of dosimetric changes due to variation of patient size in prostate VMAT. The dosimetric information should help radiation oncology staff to justify changes of dose distribution, when patient weight loss occurs during prostate VMAT. Dose variations of more than 5% were found when the patient's reduced depth was equal to 2 cm. Actual or potential conflicts of interest do not exist.
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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".