SU‐E‐T‐625: Dosimetric Dependence On Patient Size Reduction Between Prostate IMRT a1 nd VMAT2
Bibliographic record
Abstract
Purpose: This study compared the dosimetric impact between prostate intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) when patient weight loss occurs, which resulted in a reduction of external contour in the course of treatment. Methods: Six prostate patients were planned by the 7‐beam IMRT and VMAT technique using the same set of target and critical organ dose‐volume criteria and prescription dose per fraction (79 Gy per 39 fractions). Based on the original plan, doses in IMRT and VMAT plans were recalculated with the external contour of the patient reduced by 0.5–2 cm anteriorly and laterally to mimic the patient size reduction. Dose coverage and dose‐volume points of the targets and critical organs (rectum, bladder and femoral heads) were compared between IMRT and VMAT. Results: It is found in IMRT plans that increases of the D99% (target volume having 99% of the prescription dose) in PTV and CTV were 4.0 +/− 0.1% per cm of the reduced depth, which were higher than those in VMAT plans (2.7 +/−0.24% per cm). For increases of the D30% in rectum and bladder, 4.0 +/− 0.2% per cm and 3.5 +/− 0.5% per cm were found in IMRT plans, which were higher than those of VMAT (2.2 +/− 0.2% per cm and 2.0 +/−0.6% per cm), respectively. The increase of the D5% in right femoral head for IMRT (3.7 +/− 0.1% per cm) was also found higher than VMAT (3.3 +/− 0.1% per cm). Conclusion: For increases of dose‐volume criteria of critical organs in IMRT plans, it is concluded that VMAT would be preferred to IMRT in prostate radiotherapy, when a patient has potentials to have weight loss in the treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".