Secondary neutrons around clinical electron and proton beams
Notice bibliographique
Résumé
As is the case for high-energy photon beam therapy (> 10 MV), secondary neutrons are produced during electron and proton therapy. These neutrons, which extend in energy up to the maximum energy of the primary beam, result in a whole-body radiation dose to the patient that presents a risk for a second, radiation-induced, cancer. To account for the second-cancer risk, it is necessary to understand the spectra of the neutrons involved.In this research project, the spectra of secondary neutrons arising from clinical electron and proton beams were measured. The neutron spectra around electron beams were measured for a Varian linear accelerator with maximum electron energy of 20 MeV. The neutron spectra around proton beams were measured in a treatment room with a gantry and a dedicated nozzle at the Skandion proton therapy clinic in Uppsala, Sweden. The proton beams were generated by the compact IBA Proteus Plus cyclotron, which has a maximum proton energy of 230 MeV.Measurements were performed using the Nested Neutron Spectrometer (NNS™, Detec Inc, Gatineau Quebec). The NNS™ comprises a central He-3 detector (active neutron detection) with seven high density polyethylene shells that may be arranged around the detector in Russian doll fashion. The neutron spectra arising from proton beams were measured using a modified version of the NNS™ incorporating a brass moderator shell to provide an extended energy range (EER) for the detection of high-energy neutrons. The raw neutron data were unfolded using the Maximum a Posteriori (MAP) method (custom-written in C++) and the vendor-supplied moderator response functions for the NNS™. Note that the MAP is a modified version of the Maximum Likelihood Estimation Method (MLEM) that penalizes any high noise component. To plot the secondary neutron fluence as a function of energy, the ROOT data analysis library from CERN was used. Additionally, the ICRP conversion coefficients were used to calculate the neutron ambient dose equivalent rates around the electron and proton beams.The effect of several parameters on the neutron fluence rate and on the neutron dose equivalent rate were studied for each primary beam situation. For the electron beams, it was observed that as the energy of the primary electron beam increases, the neutron fluence rate and dose equivalent rate increase. In addition, the presence of a solid water phantom in the primary electron beam does not affect the neutron spectra. However, when closing the jaws in the treatment head, the neutron fluence rate and dose equivalent rate increase significantly which means that the main production of secondary neutrons around electron beams lies in the treatment head of the linear accelerator.For the proton beams, it was observed that as the energy of the primary proton beam increases, the neutron fluence rate and dose equivalent rate increase. The presence of a water phantom in the primary beam significantly enhances the direct and evaporation peaks of the neutron spectra which indicates that an important production of secondary neutrons around proton beams happens in the patient body. The evaporation and direct peaks of the neutron spectrum dominate the thermal peak when measuring on the couch (close to the neutron source), while the thermal peak dominates when measuring in the maze-room junction (far from the neutron source).
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».