Characterizing a proton beam scanning system for Monte Carlo dose calculation in patients

Abstract

The presented work has two goals. First, to demonstrate the feasibility of accurately characterizing a proton radiation field at treatment head exit for Monte Carlo dose calculation of active scanning patient treatments. Second, to show that this characterization can be done based on measured depth dose curves and spot size alone, without consideration of the exact treatment head delivery system. This is demonstrated through calibration of a Monte Carlo code to the specific beam lines of two institutions, Massachusetts General Hospital (MGH) and Paul Scherrer Institute (PSI). Comparison of simulations modeling the full treatment head at MGH to ones employing a parameterized phase space of protons at treatment head exit reveals the adequacy of the method for patient simulations. The secondary particle production in the treatment head is typically below 0.2% of primary fluence, except for low–energy electrons (<0.6MeV for 230MeV protons), whose contribution to skin dose is negligible. However, there is significant difference between the two methods in the low-dose penumbra, making full treatment head simulations necessary to study out-of field effects such as secondary cancer induction. To calibrate the Monte Carlo code to measurements in a water phantom, we use an analytical Bragg peak model to extract the range-dependent energy spread at the two institutions, as this quantity is usually not available through measurements. Comparison of the measured with the simulated depth dose curves demonstrates agreement within 0.5mm over the entire energy range. Subsequently, we simulate three patient treatments with varying anatomical complexity (liver, head and neck and lung) to give an example how this approach can be employed to investigate site-specific discrepancies between treatment planning system and Monte Carlo simulations.

Intensity modulated proton therapy

“…see also Grassberger et al38 ) shows fields in three example patients (liver, base of skull and lung) and demonstrates how the discrepancy between MC simulation and PBA increases with increasing geometrical complexity.Schuemann et al 28 discuss the need for site-specific range margins (albeit applied to SOBP fields) based on a comparison of the distal dose surfaces achieved by a PBA (in-house implementation based on Hong et al 37 ) and MC (TOPAS 39 ) where each calculation produced the identical SOBP in water. They observe deviations (MC-PBA), for head and neck fields, for example, in the order of 22 mm (or 21.…”

“…The PBA modelling of the increasingly complex topology of heterogeneities causes an increase differential with the more able MC. Adapted from Grassberger et al 38 can be managed through daily volumetric imaging to reduce the uncertainty to its minimum and to allow for pertreatment reoptimization of the treatment plan. Thus, sitespecific analysis should identify the inherent robustness of the nominal treatment approach as quantified by dosimetric quality indicators and as quantified by the biological response variation.…”

Validation and clinical implementation of an accurate Monte Carlo code for pencil beam scanning proton therapy

“…Several papers9, 10, 11 have reported how to develop such beam source model by deriving source parameters through a set of simple measurements for individual beam lines. The major advantage is that this does not require knowledge of beam line or nozzle components and material compositions, and hence significantly reduces computing time without the need to model the nozzle.…”

Treatment planning aspects and Monte Carlo methods in proton therapy

“…These kinds of beam models are either based on full MC simulations of the treatment head as described above, on dose measurements or on a combination of both. 63,70,71 However, due to the complexity of the treatment head construction for scattered proton beams and the aperture and compensator as highly patient specific components, the generation of a beam model is much more difficult. 6 Although MC is able to accurately simulate the proton beam characteristics, there are several uncertainties associated with the radiation transport using MC: uncertainties regarding shape, position and material of the treatment head components, uncertainties of the initial beam parameters, uncertainties in the synchronization of dynamic components and uncertainties of the physical models used for the simulation of the radiation transport.…”

“…7, is a lung case for which treatment plans using scanned proton beams were created using either a pencil beam algorithm or MC. 63 Differences up to 30% are reported at the distal end of the field due to the described shortcomings of the pencil beam algorithm in situations where inhomogeneities and large density variations are present. 63 In this case, the lowdensity lung tissue amplifies the differences in range estimation.…”