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Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling.

Kraan AC - Front Oncol (2015)

Bottom Line: Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality.We include research studies and clinically applied methods.For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, National Institute for Nuclear Physics (INFN), University of Pisa , Pisa , Italy.

ABSTRACT
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including β (+) emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.

No MeSH data available.


Top left: colourwash overlays of the planning CT image (TP-CT) in the coronal view with the RBE-weighted dose distributions as obtained from the TP system (TP dose). Top center: the simulated activity pattern overlaid on the PET-CT image (Sim). Top right: the measured PET image (PET) overlaid on the PET-CT image. The solid green line marks the planning target volume. Bottom: the profile plot of the simulated and the measured activity (solid) as well as the corresponding CT image values (dashed) along the yellow line in panels Sim and PET in beam direction. Reproduced from Bauer et al. (125), with permission.
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Figure 11: Top left: colourwash overlays of the planning CT image (TP-CT) in the coronal view with the RBE-weighted dose distributions as obtained from the TP system (TP dose). Top center: the simulated activity pattern overlaid on the PET-CT image (Sim). Top right: the measured PET image (PET) overlaid on the PET-CT image. The solid green line marks the planning target volume. Bottom: the profile plot of the simulated and the measured activity (solid) as well as the corresponding CT image values (dashed) along the yellow line in panels Sim and PET in beam direction. Reproduced from Bauer et al. (125), with permission.

Mentions: Following the improvements of the internal nuclear models in FLUKA, Sommerer et al. (138) assessed the performance of FLUKA by comparing measured and simulated activity profiles in homogeneous target irradiated with carbon and oxygen beams. The code was extensively benchmarked with data and has been used for offline-treatment verification after carbon ion therapy of patients at HIT (125, 139). Figure 11 shows an example of a measured and MC predicted activity profile along the beam-axis for a glioblastoma patient treated at HIT.


Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling.

Kraan AC - Front Oncol (2015)

Top left: colourwash overlays of the planning CT image (TP-CT) in the coronal view with the RBE-weighted dose distributions as obtained from the TP system (TP dose). Top center: the simulated activity pattern overlaid on the PET-CT image (Sim). Top right: the measured PET image (PET) overlaid on the PET-CT image. The solid green line marks the planning target volume. Bottom: the profile plot of the simulated and the measured activity (solid) as well as the corresponding CT image values (dashed) along the yellow line in panels Sim and PET in beam direction. Reproduced from Bauer et al. (125), with permission.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493660&req=5

Figure 11: Top left: colourwash overlays of the planning CT image (TP-CT) in the coronal view with the RBE-weighted dose distributions as obtained from the TP system (TP dose). Top center: the simulated activity pattern overlaid on the PET-CT image (Sim). Top right: the measured PET image (PET) overlaid on the PET-CT image. The solid green line marks the planning target volume. Bottom: the profile plot of the simulated and the measured activity (solid) as well as the corresponding CT image values (dashed) along the yellow line in panels Sim and PET in beam direction. Reproduced from Bauer et al. (125), with permission.
Mentions: Following the improvements of the internal nuclear models in FLUKA, Sommerer et al. (138) assessed the performance of FLUKA by comparing measured and simulated activity profiles in homogeneous target irradiated with carbon and oxygen beams. The code was extensively benchmarked with data and has been used for offline-treatment verification after carbon ion therapy of patients at HIT (125, 139). Figure 11 shows an example of a measured and MC predicted activity profile along the beam-axis for a glioblastoma patient treated at HIT.

Bottom Line: Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality.We include research studies and clinically applied methods.For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, National Institute for Nuclear Physics (INFN), University of Pisa , Pisa , Italy.

ABSTRACT
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including β (+) emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.

No MeSH data available.