Po‐Thur Eve General‐03: The Use of Megavoltage Computed Tomography (MVCT) in Treatment Planning
Bibliographic record
Abstract
In modern radiotherapy treatment planning, the information in diagnostic CT images is used for two purposes: to delineate tumour and surrounding critical structures and to provide an electron density map of the patient that is used to calculate the dose distribution resulting from exposure to a certain beam arrangement. In pelvic cancer patients with hip prostheses, the metal implants produce artifacts in the diagnostic CT images such that both the location of the tumour and accurate electron densities are either difficult or impossible to obtain. We have used megavoltage CT (MVCT) images for treatment planning in an attempt to quantify the impact of metal artifacts and overcome the problems they introduce. This has been done in three different sets of experiments. The first was a calibration of the megavoltage CT number‐to‐electron density curve using a CIRS phantom. This also allowed for measurements of the impact of metal artifacts on apparent relative electron density in both kVCT and MVCT images. The second was the comparison of treatment plans generated for patients with metal implants using both diagnostic and megavoltage CT studies. This allowed for quantitative measurements of the calculated dosimetric effect of metal artifacts. The final set of experiments compared MVCT and kVCT treatment plans of a water tank containing a stainless steel 316L rod. Dose measurements were taken at various points and compared to the doses calculated using both MVCT and kVCT studies.
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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 | 0.000 | 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 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".