Performance of a clinical gridded electron gun in magnetic fields: Implications for MRI‐linac therapy
Bibliographic record
Abstract
PURPOSE: MRI-linac therapy is a rapidly growing field, and requires that conventional linear accelerators are operated with the fringe field of MRI magnets. One of the most sensitive accelerator components is the electron gun, which serves as the source of the beam. The purpose of this work was to develop a validated finite element model (FEM) model of a clinical triode (or gridded) electron gun, based on accurate geometric and electrical measurements, and to characterize the performance of this gun in magnetic fields. METHODS: The geometry of a Varian electron gun was measured using 3D laser scanning and digital calipers. The electric potentials and emission current of these guns were measured directly from six dose matched true beam linacs for the 6X, 10X, and 15X modes of operation. Based on these measurements, a finite element model (FEM) of the gun was developed using the commercial software opera/scala. The performance of the FEM model in magnetic fields was characterized using parallel fields ranging from 0 to 200 G in the in-line direction, and 0-35 G in the perpendicular direction. RESULTS: The FEM model matched the average measured emission current to within 5% across all three modes of operation. Different high voltage settings are used for the different modes; the 6X, 10X, and 15X modes have an average high voltage setting of 15, 10, and 11 kV. Due to these differences, different operating modes show different sensitivities in magnetic fields. For in line fields, the first current loss occurs at 40, 20, and 30 G for each mode. This is a much greater sensitivity than has previously been observed. For perpendicular fields, first beam loss occurred at 8, 5, and 5 G and total beam loss at 27, 22, and 20 G. CONCLUSIONS: A validated FEM model of a clinical triode electron gun has been developed based on accurate geometric and electrical measurements. Three different operating modes were simulated, with a maximum mean error of 5%. This gun shows greater sensitivity to in-line magnetic fields than previously presented models, and different operating modes show different sensitivity.
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 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 | 0.002 |
| 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) | 0.001 | 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 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".