Variation of PTV dose distribution on patient size in prostate VMAT and IMRT: a dosimetric evaluation using the PTV dose–volume factor
Bibliographic record
Abstract
Abstract Background We propose to use the PTV dose–volume factor (PDVF) to evaluate treatment plans of prostate volumetric modulated arc therapy (VMAT) and intensity modulated radiotherapy (IMRT). Purpose PDVF was used to compare the variation of planning target volume (PTV) coverage between VMAT and IMRT because of weight loss of patient. Materials and methods VMAT and IMRT plans of five patients (prostate volume = 32–86·5 cm 3 ) using the 6 MV photon beams were created with the external contour reduced by depths of 0·5–2 cm to reflect the weight loss. Moreover, integral doses (volume integral of the patient dose) and prostate tumour control probability (TCP) were calculated. Results We found that reduced depth resulted in PDVF decreasing 0·03 ± 4·7 × 10 −4 (VMAT) and 0·04 ± 9·7 × 10 −3 (IMRT) per cm for patients. The decrease of PDVF or degradation of PTV coverage was found more significant in IMRT plans than VMAT with patient size reduction. The integral dose did not change significantly between VMAT and IMRT, while the prostate TCP increased with an increase of reduced depth. Conclusion We concluded that PDVF can be successfully used to evaluate the variation of PTV coverage because of weight loss of patient in prostate VMAT and IMRT. Degradation of PTV coverage in prostate VMAT is less significant than IMRT regarding patient size reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".