Range uncertainties in proton therapy and the role of Monte Carlo simulations

Abstract

The main advantages of proton therapy are the reduced total energy deposited in the patient as compared to photon techniques and the finite range of the proton beam. The latter adds an additional degree of freedom to treatment planning. The range in tissue is associated with considerable uncertainties caused by imaging, patient setup, beam delivery and dose calculation. Reducing the uncertainties would allow a reduction of the treatment volume and thus allow a better utilization of the advantages of protons. This paper summarizes the role of Monte Carlo simulations when aiming at a reduction of range uncertainties in proton therapy. Differences in dose calculation when comparing Monte Carlo with analytical algorithms are analyzed as well as range uncertainties due to material constants and CT conversion. Range uncertainties due to biological effects and the role of Monte Carlo for in vivo range verification are discussed. Furthermore, the current range uncertainty recipes used at several proton therapy facilities are revisited. We conclude that a significant impact of Monte Carlo dose calculation can be expected in complex geometries where local range uncertainties due to multiple Coulomb scattering will reduce the accuracy of analytical algorithms. In these cases Monte Carlo techniques might reduce the range uncertainty by several mm.

Figures

Figure 1

Range of a proton beam in water based on the continuous slowing down approximation as a function of proton energy.

Figure 2

Left: Distal falloff of a Bragg peak from a 220 MeV proton beam after penetrating different inhomogeneities shown on the right. The inlet shows the doses without normalization to the maximum. Adapted from (Sawakuchi et al., 2008), with permission.

Figure 3

Axial views of dose distributions calculated using a commercial planning system based on a pencil-beam algorithm (XiO (Computerized Medical Systems); left) and a Monte Carlo system (right). The red arrow indicates the range difference due to a density interface parallel to the beam path. Adapted from (Paganetti et al., 2008), with permission.

Figure 4

Measured (circles) and Monte Carlo simulated (line) lateral dose profile. The experimental setup shown on the left consisted of a beam impinging on a half-block of bone equivalent material (black) into a water phantom (grey). The dashed line indicates the position of the measured profile. Adapted from (Paganetti et al., 2008), with permission.

Figure 5

Monte Carlo (MC) and analytically (TPS) generated dose distributions in a small field delivered to a head and neck patient. (a): depth dose distributions along the beam central axis; (b): transverse dose profiles; (c): axes used for figures a) and b). From (Bednarz et al., 2010), with permission.

Figure 6

Depth dose curves in water for a 122 MeV proton beam assuming mean excitation energies of 67 eV, 75 eV, and 80 eV, respectively. From (Andreo, 2009), with permission.

Figure 7

Monte Carlo model of one of the treatment heads at the Francis H Burr Proton Therapy Center at Massachusetts General Hospital. The simulation was done with the TOPAS Monte Carlo system based on the Geant4 Monte Carlo code (Perl et al., 2011).

Figure 8

Left: Image of an inflated swine lung. The CT image was edited to introduce a 4 cm thick water-equivalent entrance wall and a 2×2×2 cm3 tumor. A 5 mm CTV expansion is shown in red. Right: Subsection of the CT image showing the transvere and coronal view of the structures for different voxel sizes. Adapted from (Espana and Paganetti, 2011), with permission.

Figure 9

Left: Physical dose and biological dose (physical dose times RBE; line with circles) simulated for one particular endpoint and dose. Right: SOBP and the underlying proton energy distributions at four different depths causing an increasing LET with depth. Adapted from (Paganetti and Goitein, 2000) and (Paganetti, 1998), with permission.

Figure 10

Two dose distributions (left; in %) and the corresponding dose averaged LET distributions, LETd, (right; in keV/µm) illustrating that clinically equivalent dose distributions can be achieved with quite different LET distributions steering dose falloffs away from critical structures in intensity modulated proton therapy. Based on (Grassberger et al., 2011).

Figure 11

Measured and Monte Carlo simulated depth activity profiles (activity concentration in Bq/ml) obtained for a gel consisting of 11.03% H, 1.04% C, 0.32% N, and 87.6% O. The scan was taken immediately after irradiation with a scan time of 5 minutes. Adapted from (Espana et al., 2011), with permission.

Figure 12

Dotted lines: Typically applied range uncertainty margins in proton therapy treatment planning as currently typically applied at the Massachusetts General Hospital (3.5% + 1mm), the MD Anderson Proton Therapy Center in Houston (3.5% + 3mm), the Loma Linda University Medical Center (3.5% + 3mm), the Roberts Proton Therapy Center at the University of Pennsylvania (3.5% + 3mm), and the University of Florida Proton Therapy Institute (2.5% + 1.5mm). Note that these centers may apply bigger margins in specific treatment scenarios. Dashed line: estimated uncertainty without the use of Monte Carlo dose calculation. Solid line: estimated uncertainty for complex geometries without the use of Monte Carlo dose calculation. Dashed-dotted line: estimated uncertainty with the use of Monte Carlo dose calculation.