Challenges in modeling the Agility multileaf collimator in treatment planning systems and current needs for improvement
Notice bibliographique
Résumé
BACKGROUND: The Agility multileaf collimator (MLC) mounted in Elekta linear accelerators features some unique design characteristics, such as large leaf thickness, eccentric curvature at the leaf tip, and defocused leaf sides ('tilting'). These characteristics offer several advantages but modeling them in treatment planning systems (TPSs) is challenging. PURPOSE: The goals of this study were to investigate the challenges faced when modeling the Agility in two commercial TPSs (Monaco and RayStation) and to explore how the implemented MLC models could be improved in the future. METHODS: Four linear accelerators equipped with the Agility, located at different centers, were used for the study. Three centers use the RayStation TPS and the other one uses Monaco. For comparison purposes, data from four Varian linear accelerators with the Millennium 120 MLC were also included. Average doses measured with asynchronous sweeping gap tests were used to characterize and compare the characteristics of the Millennium and the Agility MLCs and to assess the MLC model in the TPSs. The FOURL test included in the ExpressQA package, provided by Elekta, was also used to evaluate the tongue-and-groove with radiochromic films. Finally, raytracing was used to investigate the impact of the MLC geometry and to understand the results obtained for each MLC. RESULTS: The geometry of the Agility produces dosimetric effects associated with the rounded leaf end up to a distance 20 mm away from the leaf tip end measured at the isocenter plane. This affects the tongue-and-groove shadowing, which progressively increases along the distance to the tip end. The RayStation and Monaco TPSs did not account for this effect, which made trade-offs in the MLC parameters necessary and greatly varied the final MLC parameters used by different centers. Raytracing showed that these challenging leaf tip effects were directly related to the MLC geometry and that the characteristics mainly responsible for the large leaf tip effects of the Agility were its tilting design and its small source-to-collimator distance. CONCLUSIONS: The MLC models implemented in RayStation and Monaco could not accurately reproduce the leaf tip effects for the Agility. Therefore, trade-offs are needed and the optimal MLC parameters are dependent on the specific characteristics of treatment plans. Refining the MLC models for the Agility to better approximate the measured leaf tip and tongue-and-groove effects would extend the validity of the MLC model, reduce the variability in the MLC parameters used by the community, and facilitate the standardization of the MLC configuration process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,008 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».