Lack of influence of intravenous contrast on head and neck IMRT dose distributions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Intravenous (i.v.) contrast at the time of CT-Simulation facilitates radiotherapy contouring, but may introduce a discrepancy between planned and delivered dose due to density variation in blood vessels. Here, the effect of physiologic and non-physiologic extremes of i.v. contrast densities on intensity modulated radiotherapy (IMRT) plans for patients with head and neck cancer was investigated. METHODS AND MATERIALS: This planning study was conducted using i.v. contrast CT scans of ten patients with squamous cell cancer of the head and neck treated with IMRT. The target volumes and normal tissues, including the blood vessels of the head and neck, were contoured and IMRT plans were created according to RTOG Protocol 0022. The density within the blood vessels was then virtually altered to mimic non-contrast and extreme (bone and air) densities. The dose was then recalculated using the same IMRT plan. Plans obtained with and without density overrides were then compared. RESULTS: The change in planning target volume (PTV) coverage for plans with and without i.v. contrast was minimal. The volume of the PTVs covered by the 93% and 100% isodoses changed on average by 0.57%. The minimum dose to PTVs varied by a maximum of 0.17 Gy. The maximum point dose to critical organs changed by a maximum of 0.12 Gy (brainstem). Non-physiologic extremes of density within blood vessels also resulted in minimal changes in tumor or normal tissue dosimetry. CONCLUSION: The use of i.v. contrast at time of CT-simulation does not significantly affect dose calculation in head and neck IMRT plans.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it