Impact of high dose volumetric CT on PTV margin reduction in VMAT prostate radiotherapy
Bibliographic record
Abstract
The aim of the study is to determine PTV margin for inter-observer variability in the volumetric modulated arc therapy (VMAT) prostate radiotherapy with high-dose volumetric CT (HDVCT) and conventional helical CT (CCT) for planning. Secondly to investigate the impact of geometric (PTV expansion) and dosimetric (conformity) imperfection of planning process on the PTV margin analysis. Prostate gland of ten patients were scanned with CCT and HDVCT techniques consecutively on a 320 slice volumetric CT scanner with wide field detector of 16 cm. Five radiation oncologists delineated CTV of the prostate. VMAT plans were developed with PTV margin of 4 mm and 6 mm (totaling 200 plans) and target coverage of each plan was evaluated on the target volume in agreement determined by shared voxels with three or more from 5 observers. Dosimetry on 200 VMAT plans showed that PTV margin for inter-observer variability were 6 mm and 4 mm for CCT and HDVCT techniques, respectively. It is about 3 mm smaller than our estimation from the previous study (8.8 mm and 7.3 mm) based on the inter-observer variability. This difference is mainly due to the accuracy of PTV volume expansion and limited dose conformity to guarantee target coverage. PTVs were measured 2 mm larger on average than the assigned margin. Planning iso-dose volume was found to be 2 mm larger than PTV. Regardless these limitations, enhanced image quality of HDVCT reduces PTV margin by 2 mm compared to CCT. PTV reduction of 2 mm potentially leads to 15% reduction in D30% of rectal and bladder wall maintaining the same target coverage. Inter-observer variability remains a source of systematic uncertainty. HDVCT for treatment planning demonstrated reduction of the uncertainty and the PTV margin by 2 mm. It is important to consider the over-expanded PTV volume and generous iso-dose volume after optimization in the process of radiotherapy planning in the determination of PTV margin.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".