Poster — Thur Eve — 36: Lung SBRT: Dosimetric Evaluation of 4DCT Based Treatment Planning in Presence of Respiratory Motion
Bibliographic record
Abstract
The respiratory related dosimetric uncertainties in the 4DCT based lung stereotactic body radiotherapy (SBRT) treatment planning and treatment delivery are evaluated by performing density assignment correction (DAC) in the ITV. Siemens 40‐slice CT scanner was used to acquire 8 phases of 4DCT images and a free breathing CT scan using a CIRS Dynamic Thorax Phantom. The ITV was created from 4DCT scan and treatment planning was done in free breathing CT scan. The ITV dose coverage was measured by CIRS phantom with ionization chamber moving together with the tumor during the beam delivery under free breathing treatment, which considers the time and positional averaged distribution of tissue heterogeneities within the ITV. The measured results are compared with the treatment planning with and without DAC in the ITV. The ITV dose coverage from the measurement is 1.9% higher than the planned ITV mean dose. The ITV received adequate dose due to the presence of effective density of the tumor within the ITV when the treatment is delivered under free breathing. The plan accounting for respiratory motion by assigning an average tumor density into the treatment planning had better uniform dose than the plan without DAC. By incorporating the ITV tumor density override into treatment planning dose calculation, the ITV dose coverage becomes more uniform and the mean dose of ITV increases and more closely matches the measured values than the plan without DAC in the ITV.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".