Evaluating small field dosimetry with the Acuros XB (AXB) and analytical anisotropic algorithm (AAA) dose calculation algorithms in the eclipse treatment planning system
Notice bibliographique
Résumé
Abstract Background: An increasing number of external beam treatment modalities including intensity modulated radiation therapy, volumetric modulated arc therapy (VMAT) and stereotactic radiosurgery uses very small fields for treatment planning and delivery. However, there are major challenges in small photon field dosimetry, due to the partial occlusion of the direct photon beam source’s view from the measurement point, lack of lateral charged particle equilibrium, steep dose-rate gradient and volume averaging effect of the detector response and variation of the energy fluence in the lateral direction of the beam. Therefore, experimental measurements of dosimetric parameters such as percent depth doses (PDDs), beam profiles and relative output factors (ROFs) for small fields continue to be a challenge. Materials and Methods: In this study, we used a homogeneous water phantom and the heterogeneous anthropomorphic stereotactic end-to-end verification (STEEV) head phantom for all dose measurements and calculations. PDDs, lateral dose profiles and ROFs were calculated in the Eclipse Treatment Planning System version 13·6 using the Acuros XB (AXB) and the analytical anisotropic algorithms (AAAs) in a homogenous water phantom. Monte Carlo (MC) simulations and measurements using the Exradin W1 Scintillator were also accomplished for four photon energies: 6 MV, 6FFF, 10 MV and 10FFF. Two VMAT treatment plans were generated for two different targets: one located in the brain and the other in the neck (close to the trachea) in the head phantom (CIRS, Norfolk, VA, USA). A Varian Truebeam linear accelerator (Varian, Palo Alto, CA, USA) was used for all treatment deliveries. Calculated results with AXB and AAA were compared with MC simulations and measurements. Results: The average difference of PDDs between W1 Exradin Scintillator measurements and MC simulations, AAA and AXB algorithm calculations were 1·2, 2·4 and 3·2%, respectively, for all field sizes and energies. AXB and AAA showed differences in ROF of about 0·3 and 2·9%, respectively, compared with W1 Exradin Scintillator measured values. For the target located in the brain in the head phantom, the average dose difference between W1 Exradin Scintillator and the MC simulations, AAA and AXB were 0·2, 3·2 and 2·7%, respectively, for all field sizes. Similarly, for the target located in the neck, the respective dose differences were 3·8, 5·7 and 3·5%. Conclusion: In this study, we compared dosimetric parameters such as PDD, beam profile and ROFs in water phantom and isocenter point dose measurements in an anthropomorphic head phantom representing a patient. We observed that measurements using the W1 Exradin scintillator agreed well with MC simulations and can be used efficiently for dosimetric parameters such as PDDs and dose profiles and patient-specific quality assurance measurements for small fields. In both homogenous and heterogeneous media, the AXB algorithm dose prediction agrees well with MC and measurements and was found to be superior to the AAA algorithm.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».