Optimization of tomotherapy treatment planning for patients with bilateral hip prostheses
Bibliographic record
Abstract
BACKGROUND: To determine the effect of different imaging options and the most efficient imaging strategy for treatment planning of patients with hip prostheses. METHODS: The planning kilovoltage CT (kVCT) and daily megavoltage CT (MVCT) studies for three prostate cancer patients with bilateral hip prostheses were used for creating hybrid kVCT/MVCT image sets. Treatment plans were created for kVCT images alone, hybrid kVCT/MVCT images, and MVCT images alone using the same dose prescription and planning parameters. The resulting dose volume histograms were compared. The orthopedic metal artifact reduction (O-MAR) reconstruction tool for kVCT images and different MVCT options were investigated with a water tank fit with double hip prostheses. Treatment plans were created for all imaging options and calculated dose was compared with the one measured by a pin-point ion chamber. RESULTS: On average for three patients, the D35% for the bladder was 8% higher in plans based on MVCT images and 7% higher in plans based on hybrid images, compared to the plans based on kVCT images alone. Likewise, the D35% for the rectum was 3% higher than the kVCT based plan for both hybrid and MVCT plans. The average difference in planned D99% in the PTV compared to kVCT plans was 0.9% and 0.1% for MVCT and hybrid plans, respectively. For the water tank with hip prostheses phantom, the kVCT plan with O-MAR correction applied showed better agreement between the measured and calculated dose than the original image set, with a difference of -1.9% compared to 3.3%. The measured doses for the MVCT plans were lower than the calculated dose due to image size limitations. The best agreement was for the kVCT/MVCT hybrid plans with the difference between calculated and measured dose around 1%. CONCLUSION: MVCT image provides better visualization of patient anatomy and hybrid kVCT/MVCT study enables more accurate calculations using updated MVCT relative electron density calibration.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".