Dose-guided radiation therapy with megavoltage cone-beam CT
Bibliographic record
Abstract
Recent advances in fractionated external beam radiation therapy have increased our ability to deliver radiation doses that conform more tightly to the tumour volume. The steeper dose gradients delivered in these treatments make it increasingly important to set precisely the positions of the patient and the internal organs. For this reason, considerable research now focuses on methods using three-dimensional images of the patient on the treatment table to adapt either the patient position or the treatment plan, to account for variable organ locations. In this article, we briefly review the different adaptive methods being explored and discuss a proposed dose-guided radiation therapy strategy that adapts the treatment for future fractions to compensate for dosimetric errors from past fractions. The main component of this strategy is a procedure to reconstruct the dose delivered to the patient based on treatment-time portal images and pre-treatment megavoltage cone-beam computed tomography (MV CBCT) images of the patient. We describe the work to date performed to develop our dose reconstruction procedure, including the implementation of a MV CBCT system for clinical use, experiments performed to calibrate MV CBCT for electron density and to use the calibrated MV CBCT for dose calculations, and the dosimetric calibration of the portal imager. We also present an example of a reconstructed patient dose using a preliminary reconstruction program and discuss the technical challenges that remain to full implementation of dose reconstruction and dose-guided therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".