Modulated electron radiation therapy: an investigation on fast beam models and radiation-tolerant solutions for automated motion control of a few leaf electron collimator
Bibliographic record
Abstract
The purpose of this study was to address two specific issues related with the clinical application of Modulated Electron Radiation Therapy (MERT). The first was to investigate radiation-tolerant solutions for automated motion control of a Few Leaf Electron Collimator. Secondly, we implemented a fast, Monte Carlo-based, parameterized beam model for characterization of the electron beam in modulated deliveries.Two approaches were investigated for the implementation of a radiation-tolerant position feedback system: (i) the use of CMOS-based optical encoders protected by a prototype shield and (ii) the use of an analog device, such as a potentiometer, whose radiation tolerance is significantly higher. The two approaches were implemented and their performance tested. Results indicated that the optical encoders could not be safely used under radiation even with the presence of a shield. The analog position feedback system showed to be a viable solution. Future work will be focused towards the direction of implementing an analog position feedback system suitable for clinical use.The MC-based, parameterized beam model is based on the idea of deriving the scattered electron beam characteristics directly on the exit plane of the linear accelerator by the use of source scatter fluence kernels. Primary beam characteristics are derived by fast Monte Carlo simulations. The novelty of the method is that arbitrary rectangular fields can be recreated fast by superposition of the appropriate source kernels directly on the output plane. Depth, profile dose distributions and dose output, were derived for three field sizes (8 x 8, 2 x 2 and 2 x 8 cm^2) and energies of 6 MeV and 20 MeV electron beams by the beam model and compared with full Monte Carlo simulations. The primary beam showed excellent agreement in all cases. Scattered particles agreed well for the larger field sizes of 8 x 8 and 2 x 8 cm^2, while discrepancies were encountered for scattered particles for the smaller field size of 2 x 2 cm^2. Sources of errors were identified and future work will focus on the improvement of the beam model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".