Investigating the impacts of intrafraction motion on dosimetric outcomes when treating small targets with virtual cones
Notice bibliographique
Résumé
Abstract Purpose Intrafraction patient motion is a well‐documented phenomenon in radiation therapy. In stereotactic radiosurgery applications in which target sizes can be very small and dose gradients very steep, patient motion can significantly impact the magnitude and positional accuracy of the delivered dose. This work investigates the impact of intrafraction motion on dose metrics for small targets when treated with a virtual cone. Materials and Methods Monte Carlo simulations were performed to calculate dose kernels for treatment apertures ranging from 1 × 2.5 mm 2 to 10 × 10 mm 2 . The phantom was an 8.2‐cm diameter sphere and isotropic voxels had lengths of 0.25 mm. Simulated treatments consisted of 3 arcs: 1 axial arc (360° gantry rotation, couch angle 0°) and 2 oblique arcs (180° gantry rotation, couch angle ±45°). Dose distributions were calculated via superposition of the rotated kernels. Two different collimator orientations were considered to create a virtual cone: (a) each treatment arc was delivered twice, once each with a static collimator angle of ±45°, and (b) each treatment arc was delivered once, with dynamic collimator rotation throughout the arc. Two different intrafraction motion patterns were considered: (a) constant linear motion and (b) sudden, persistent motion. The impact of motion on dose distributions for target sizes ranging from 1 to 10 mm diameter spheres was quantified as a function of the aperture size used to treat the lesions. Results The impact of motion on both the target and the surrounding tissue was a function of both aperture shape and target size. When a 0.5‐mm linear drift along each dimension occurred during treatment, targets ≥5 mm saw less than a 10% decrease in coverage by the prescription dose. Smaller apertures accrued larger penalties with respect to dosimetric hotspots seen in the tissues surrounding the target volume during intrafraction motion. For example, treating a 4‐mm‐sized target that undergoes 2.60 mm (3D vector) of continuous linear motion, the D 5 in the concentric shells that extend 1, 2, and 3 mm from the surface of the target was 39%, 24%, and 14% smaller, respectively when comparing the delivery of a larger aperture (6 × 10 mm 2 ) to a smaller aperture (2 × 5 mm 2 ). Using a static collimator for shaping a virtual cone during treatment minimized the dosimetric impact of motion in the majority of cases. For example, the volume that is covered by 70% or more of the prescription dose is smaller in 60.4% of cases when using the static collimator. The volume covered by 50, and 30% or more of the prescription dose is also smaller when treating with a static collimator, but the clinical significance of this finding is unknown. Conclusions In this work, the dosimetric trade‐offs between aperture size and target size when irradiating with virtual cones has been demonstrated. These findings provide information about the tradeoffs between target coverage and normal tissue sparing that may help inform clinical decision making when treating smaller targets with virtual cones.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».