Sci-Thurs PM: Delivery-12: Correction and calibration of megavoltage cone-beam CT images for the calculation of the dose of the day
Bibliographic record
Abstract
PURPOSE: To show that accurate dose calculations can be achieved with megavoltage cone-beam CT (MVCBCT) images of head-and-neck (H&N) and prostate sites, allowing the verification of the daily dose distribution received by these patients. METHOD AND MATERIALS: Corrections for the cupping and missing data artifacts seen on MVCBCT images were developed for both H&N and pelvic imaging. MVCBCT images of six H&N and two prostate patients were acquired weekly during the course of their treatment. Several regions of interest were contoured including: the prostate and rectum and the spinal cord and parotids. Dose calculation was performed with the MVCBCT images using the plan beams. Variations from treatment plan dosimetric endpoints were analyzed. RESULTS: Dose calculations with kVCT and corrected MVCBCT images of the H&N (pelvic) regions show standard deviations of 1.9% (0.6%). The mean dose to the right parotid of H&N patients had an average increase of 18% during treatment. The maximum dose to 1% of the spinal cord went up by 2% on average. For prostate patients on one fraction the dose received by 95% of the prostate diminished by 3%. One patient had an average increase of 3.6% of the maximum dose received by 1% of the rectum. CONCLUSION: MVCBCT can be used to verify daily dose distributions for H&N and prostate patients. An increase in the mean dose to normal tissues was observed during H&N treatment. Underdosage of the prostate and the dosimetric consequences of volume changes in rectum and bladder were observed. Research supported by Siemens.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".