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Empirical planning target volume modeling for high precision MRI guided intracranial radiotherapy.
Stewart, James; Sahgal, Arjun; Zadeh, Mahtab M; Moazen, Bahareh; Jabehdar Maralani, Pejman; Breen, Stephen; Lau, Angus; Binda, Shawn; Keller, Brian; Husain, Zain; Myrehaug, Sten; Detsky, Jay; Soliman, Hany; Tseng, Chia-Lin; Ruschin, Mark.
Afiliação
  • Stewart J; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Sahgal A; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Zadeh MM; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Moazen B; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
  • Jabehdar Maralani P; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
  • Breen S; Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Lau A; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Binda S; Department of Medical Physics, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Keller B; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
  • Husain Z; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Myrehaug S; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Detsky J; Department of Medical Physics, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Soliman H; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Canada.
  • Tseng CL; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Ruschin M; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Canada.
Clin Transl Radiat Oncol ; 39: 100582, 2023 Mar.
Article em En | MEDLINE | ID: mdl-36699195
ABSTRACT

Purpose:

Magnetic resonance image-guided radiotherapy for intracranial indications is a promising advance; however, uncertainties remain for both target localization after translation-only MR setup and intrafraction motion. This investigation quantified these uncertainties and developed a population-based planning target volume (PTV) model to explore target and organ-at-risk (OAR) volumetric coverage tradeoffs.

Methods:

Sixty-six patients, 49 with a primary brain tumor and 17 with a post-surgical resection cavity, treated on a 1.5T-based MR-linac across 1329 fractions were included. At each fraction, patients were setup by translation-only fusion of the online T1 MRI to the planning image. Each fusion was independently repeated offline accounting for rotations. The six degree-of-freedom difference between fusions was applied to transform the planning CTV at each fraction (CTVfx). A PTV model parameterized by volumetric CTVfx coverage, proportion of fractions, and proportion of patients was developed. Intrafraction motion was quantified in a 412 fraction subset as the fusion difference between post- and pre-irradiation T1 MRIs.

Results:

For the left-right/anterior-posterior/superior-inferior axes, mean ± SD of the rotational fusion differences were 0.1 ± 0.8/0.1 ± 0.8/-0.2 ± 0.9°. Covering 98 % of the CTVfx in 95 % of fractions in 95 % of patients required a 3 mm PTV margin. Margin reduction decreased PTV-OAR overlap; for example, the proportion of optic chiasm overlapped by the PTV was reduced up to 23.5 % by margin reduction from 4 mm to 3 mm.

Conclusions:

An evidence-based PTV model was developed for brain cancer patients treated on the MR-linac. Informed by this model, we have clinically adopted a 3 mm PTV margin for conventionally fractionated intracranial patients.
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Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tratamento / Radioterapia Base de dados: MEDLINE Idioma: En Revista: Clin Transl Radiat Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tratamento / Radioterapia Base de dados: MEDLINE Idioma: En Revista: Clin Transl Radiat Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá