Characterizing magnetic field interactions between an in‐room MRI‐on‐rails and a radiotherapy linac: A comprehensive simulation and experimental study
Notice bibliographique
Résumé
BACKGROUND: In recent years, magnetic resonance imaging (MRI)-guided radiotherapy (RT) has experienced a notable increase in utilization due to technological advancements that leverage MRI's superior soft-tissue contrast and its non-invasive, non-ionizing imaging mechanism. Integrating MRI scanners with linac systems comes with several technical challenges, including the complex interactions between the linac components and the magnetic field of the MRI scanner. PURPOSE: This study presents a comprehensive in silico finite element method (FEM)-based model for a proximity-type MRI-guided RT system consisting of an MRI-on-rail and a C-arm linac. The methodology enables the precise characterization of the MRI magnet's fringe field both in free space and when interacting with the ferromagnetic structure of the linac system. METHODS: A comprehensive in silico FEM-based model was developed to simulate the MRI magnet and linac configuration. The magnet coil configuration was generated using linear programming based on the manufacturer's specifications for the 5 G line. The linac structure was modeled from technical schematics and coupled with the simulated magnet to construct the simulation environment. Fringe field measurements were conducted in a controlled environment to validate the simulation results. The measurements were taken at various distances from the MRI isocenter and in different directions to assess the spatial distribution of the fringe field. RESULTS: Simulations showed good agreement with experimental measurements, with a maximum difference of 1 G observed between simulated and measured fringe fields within the 3 to 5 m range from the MR isocenter, consistent with the 1 G Hall probe measurement tolerance. The linac's ferromagnetic structure significantly perturbed the magnetic fringe field, locally increasing field values to 40 G from an initial range of 0-23 G, and inducing local field differences of up to 30 G at its closest proximity to the magnet. Conversely, a local decrease of up to 2 G was observed near the linac isocenter. Furthermore, the room environment influenced the fringe field's spatial distribution, evidenced by deviations of approximately 6 and 4.2 G from the Espree reference field at 2.5 and 3 m, respectively. Despite these environmental effects, the overall agreement between simulations and experimental values, including measurements at the linac head (maximum difference less than 2 G), was highly satisfactory, confirming axial field symmetry and minimal impact from room layout variations. CONCLUSIONS: This study developed and validated a comprehensive FEM-based simulation methodology to accurately characterize magnetic field interactions in a proximity-type MRI-guided RT system. The methodology mapped the MRI magnet's fringe field in both free space and as perturbed by the linac's ferromagnetic structure, with experimental data also supporting these findings. This robust framework offers a reliable tool for guiding engineering activities and defining safety bounds for system design.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».