A non-axial superconducting magnet design for optimized patient access and minimal SAD for use in a Linac-MR hybrid: proof of concept
Bibliographic record
Abstract
Abstract A prototype rotating hybrid magnetic resonance imaging system and linac has been developed to allow for simultaneous imaging and radiation delivery parallel to B 0 . However, the design of a compact magnet capable of rotation in a small vault with sufficient patient access and a typical clinical source-to-axis distance (SAD) is challenging. This work presents a novel superconducting magnet design as a proof of concept that allows for a reduced SAD and ample patient access by moving the superconducting coils to the side of the yoke. The yoke and pole-plate structures are shaped to direct the magnetic flux appropriately. The outer surface of the pole plate is optimized subject to the minimization of a cost function, which evaluates the uniformity of the magnetic field over an ellipsoid. The magnetic field calculations required in this work are performed with the 3D finite element method software package Opera-3D. Each tentative design strategy is virtually modeled in this software package, which is externally controlled by MATLAB, with its key geometries defined as variables. The optimization variables are the thickness of the pole plate at control points distributed over the pole plate surface. A novel design concept as a superconducting non-axial magnet is introduced, which could create a large uniform B 0 magnetic field with fewer geometric restriction. This non-axial 0.5 T superconducting magnet has a moderately reduced SAD of 123 cm and a vertical patient opening of 68 cm. This work is presented as a proof of principle to investigate the feasibility of a non-axial magnet with the coils located around the yoke, and the results encourage future design optimizations to maximize the benefits of this non-axial design.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".