Harmonization of dose prescription for lung stereotactic radiotherapy.
Phys Imaging Radiat Oncol
; 24: 65-70, 2022 Oct.
Article
em En
| MEDLINE
| ID: mdl-36213173
Background and purpose: Pulmonary stereotactic treatments can be performed using dedicated linear accelerators as well as robotic-assisted units, and different strategies can be used for dose prescription. This study aimed to compare the doses received by the tumor with a gross tumor volume (GTV)-based prescription on D98%GTV using a robotic-assisted unit (method A) and planning target volume (PTV)-based prescription on D95%PTV using a dedicated linac (method B). Material & methods: Plans of 32 patients were collected for method A, and a dose of 3 × 18 Gy was prescribed using type A algorithm and recalculated using a Monte-Carlo (MC) algorithm. The plans were normalized to match D98%GTV with the mean D 98 % G T V ¯ of the cohort. The plans of 23 patients were collected for method B, and a dose of 3 × 18 Gy was prescribed to D95%PTV using a MC algorithm. A 4D-sum method was developed to estimate doses for PTV and GTV. For validation, all plans were recalculated using an independent MC double-check software. A dose harmonization on D98% GTV was determined for both methods. Results: For method A, mean doses were D2%GTV = 59.9 ± 2.1 Gy, D50%GTV = 55.6 ± 1.2 Gy, D98%GTV = 49.5 ± 0.0 Gy. For method B, the reported doses were D2%GTV = 64.6 ± 2.1 Gy, D50%GTV = 62.8 ± 1.7 Gy, and D98%GTV = 60.0 ± 1.7 Gy. The dose trade-off of D98%GTV = 55 Gy was obtained for both methods. For method A, it corresponded to a dose prescription of 3 × 20 Gy using type A algorithm, followed by rescaling to obtain D98%GTV = 55 Gy. For method B, it corresponded to a dose prescription of D95%PTV = 3 × 16.5 Gy using the MC algorithm. Conclusions: This study determined similar near-minimum doses D98% GTV of approximately 3 × 18.3 Gy (55 Gy) using a GTV-based prescription on a robotic-assisted unit (method A) and a PTV-based prescription on a dedicated linac (method B).
Texto completo:
1
Base de dados:
MEDLINE
Idioma:
En
Revista:
Phys Imaging Radiat Oncol
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
França