<i>In vivo</i> Portal Imaging Dosimetry Identifies Delivery Errors in Rectal Cancer Radiotherapy on the Belly Board Device
Bibliographic record
Abstract
PURPOSE: dosimetry that uses the electronic portal imaging device to detect dose delivery discrepancies. We applied our method on patients with rectal cancer treated on a belly board device. METHODS: dosimetry was performed on 10 patients with rectal cancer treated prone on the belly board with a 4-field box arrangement. Portal images were acquired approximately once per week from each treatment beam. Our dosimetry method used these images along with the planning CT to reconstruct patient planar dose at isocenter depth. RESULTS: Our algorithm proved sensitive to dose discrepancies and detected discordances in 7 patients. The majority of these were due to soft tissue differences between planning and treatment, present despite matching to bony anatomy. As a result of this work, quality assurance procedures have been implemented for our immobilization devices. CONCLUSION: dosimetry is a powerful quality assurance tool that can detect delivery discrepancies, including changes in patient setup and position. The added information on actual dose delivery may be used to evaluate equipment and process quality and to guide for adaptive radiotherapy.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".