“Monte Carlo simulations for commissioning, quality assurance, absolute dosimetry and treatment
planning at the Northeast Proton Therapy Center.”
H. Paganetti
I. Introduction
Protons, because of the physical characteristics of the Bragg curve, offer distinct dosimetric
advantages compared to conventional techniques. These advantages include reduced integral dose,
due to the absence of exit dose, and improved target volume coverage, due to the improved
geometric control of both lateral and distal fall-off in a single treatment field. This accuracy brings
new challenges since small changes can have a large impact on treatment outcome. Accurate
imaging, patient set-up, quality assurance, and dose calculation are needed. Consequently, it is in
proton therapy where Monte Carlo methods can make the biggest impact.
A detailed simulation of the gantry treatment heads (nozzles) at the Northeast Proton Therapy
Center (NPTC) was done (1). The nozzles (see figure 1) consist of various components for beam
monitoring and beam shaping. Ionization chambers detect deviations in beam position, measure the
total beam current and check the beam scattering radius and uniformity. A double scattering system
is used to ensure a uniform, flat, lateral dose profile. The double scattering system contains a first
scatterer, placed upstream near the nozzle entrance, and a second gaussian-shaped scatterer placed
further downstream. Key element for broad beam energy modulation is the absorbers of variable
thickness. Each absorber contributes an individual pristine Bragg peak curve to the composite
SOBP. Additional parts are a patient specific aperture to confine the dose in lateral direction and a
patient field specific compensator to adjust the distal edge of the dose distribution.
Monte Carlo simulation of the nozzles was and is used for commissioning, quality assurance, and
for supporting routine operations. Although measurements are the main part of commissioning of a
new facility, mainly because of safety issues and the need for benchmarking treatment planning
software, Monte Carlo simulations were of great value. In clinical routine operations Monte Carlo
simulations support dosimetry efforts in helping to define safety tolerances and to design quality
assurance procedures. Furthermore, absolute dosimetry based on Monte Carlo is useful to reduce
the burden of patient specific calibration measurements.
To allow the use of Monte Carlo in treatment planning our code is able to read CT data and to
import treatment parameters directly from the treatment planning software. The introduction of
dynamic 4D Monte Carlo is used for research on organ motion effects.
II. Methods and Materials
The Monte Carlo code GEANT4 exploits advanced software-engineering techniques and objectoriented technology to achieve transparency (2). GEANT4 is not a stand-alone executable but an
object-oriented toolkit of libraries based on the programming language C++. All aspects of a
simulation process are included in the toolkit and can be organized in different functions for
efficient use with the C++ class structure. To build a specific application the user constructs standalone applications by implementing user action classes.
All nozzle elements were simulated with sub-millimeter accuracy based on original drawings from
Ion Beam Applications Inc. A special solution had to be found to simulate the range modulator
wheels. A modulator wheel combines absorbers in circular rotating tracks resulting in a temporal
variation of the beam energy. The modulator wheels are made of a low-Z material and a high-Z
1
material. Each step segment of the wheel covers a solid angle that represents the weighting of the
individual pristine Bragg curves. Each of the steps on a track was modeled as a tube segment.
During a simulation the rotational position of the wheel has to be changed with time. Taking
advantage of the object oriented design of GEANT4 we came up with a novel solution where the
wheel is actually “rotating” during a simulation. In this four-dimensional Monte Carlo technique the
wheel geometry is defined in a concrete C++ class and the rotation vector of the physical volume is
updated during the simulation (3).
Jaws (X and Y)
(& Range Verifier)
Magnet 2
Range Modulator
Wheels
IC1
Snout retraction area
Water Phantom
Snout
First
Magnet 1
Scatterers
Second Scatterers
IC2 and IC3
Figure 1: Treatment nozzle at one of the gantries at the NPTC as modeled within GEANT4. The
beam is entering from the right. Beam monitoring devices three segmented ionization chambers
(IC1, IC2 and IC3) and a range verifier (multi-layer Faraday cup implemented in one of the variable
collimators). The beam shaping devices are the double scattering system (the first scatterer system
consisting of 9 scattering foils, which can be moved in and out of the beam; 3 different second
scatterers mounted on a carousel), the range modulator wheel (3 wheels mounted on a carousel; 3
tracks per wheel), variable collimators (jaws) in x and y direction, and the snout (3 different snouts
are available). In addition, there are two magnets for wobbling. Not shown are the patient specific
collimator and compensator to be mounted on the snout.
Dose calculation based on patient geometry requires the import of CT data into the GEANT4 code.
CT images provide the material properties based on Hounsfield units (HUs) on a voxel by voxel
basis. For Monte Carlo dose calculation HUs have to be converted to materials with explicit
element composition and density. Since there is no unique relationship we converted the CT number
based volume definition into the definition of different tissues. We divided the space of HUs into 24
groups. In each group, element composition is preserved, but the mass density varies with the CT
number. The function of mass density versus HU is described with five linear fits. Further, each CT
voxel has a unique descriptor (i.e., an index number) based upon dose will be collected during the
dose calculation process independent of a fixed coordinate system.
2
To run a simulation the standalone Monte Carlo executable takes its input parameters directly from
a commercial treatment planning program. A LINUX cluster containing 38 CPUs is available for
fast Monte Carlo calculations.
III. Results
1. Commissioning
The NPTC snouts were designed to minimize the scattered radiation from proton interactions at the
inner side of the snout tubes and to shield the beam outside the treatment field. According to
energy/range tables the needed thickness of Brass to shield the primary proton beam can easily be
calculated. However, in order to minimize the weight of the proton shielding, it is useful to explore
the probability of nuclear interactions of protons. Using the results of calculations, it was possible to
reduce the proton leakage, while minimizing the weight of the assembly. Interestingly, as long as
the primary proton beam is stopped within the shielding assembly, the thickness of the brass
shielding has almost no influence on the secondary neutron radiation since the number of generated
neutrons is almost independent of the amount of material. Most generated neutrons penetrate and
pass through the shielding, predominantly in forward direction.
In a separate study the neutron background was investigated in terms of dose contribution outside a
treatment volume. The doses generated by secondary radiation from the patient and generated by
secondary radiation from the beam delivery system were considered separately. The simulations
show the neutron dose outside the treatment field to be on the order of 0.01% (at 20 cm lateral to
the treatment field). This was compared with measurements using radiographic film of a proton
beam through an aperture. The sensitivity of this measurement is better than 0.1% and showed no
response to dose outside the aperture.
2. Quality assurance
The agreement between measured and simulated depth-dose curves turned out to be within a
millimeter in beam range and SOBP width. With this accuracy Monte Carlo simulations can be used
to assist in quality assurance. Measurements are the key for quality assurance but they are of only
limited use to define tolerances for action based on sensitivities of beam characteristics and
alignment of hardware components. This is because most error conditions cannot be ‘created’
easily. By simulating depth-dose curves, tolerance levels for beam parameters (energy, energy
spread, spot size, angular spread) were characterized. It turned out that the influence of the varying
energy spread is significant whereas the dose distribution is quite insensitive to the size of the beam
spot and the angular spread (if varied in realistic boundaries). This can be expected in a doublescattering system.
An extensive study dealt with the alignment sensitivity of the beam to devices in the nozzle. If the
beam is misaligned with respect to any physical apertures in the nozzle, the dose distribution will be
affected. To understand the effect, and to determine the allowed tolerances, several realistic beam
setups used for patient treatment were considered. Calculations showed that depending upon the
amount of material in the beam path, the pristine Bragg peak could be affected by either a low
energy tail, which might be difficult to observe, or even by a secondary Bragg peak at a different
depth.
Another example of a sensitivity analysis is a study on the influence of the alignment of the second
scatterer. Here we studied not only translational misalignment but also a tilt of the scatterer by up to
10 degrees. One might expected this disturbance in the double-scattering system to be very critical
3
in terms of the beam flatness because of the contoured shape of the second scatterer. However, it
became evident from the simulations that beam profile measurements are less suited to detect such
an effect than depth-dose measurements.
The range modulation system at the NPTC includes not only hardware but is also software
controlled due to a beam current modulation that switches the beam on or off for specific segments
of the modulator wheel track. We performed calculations where we simulated situations where the
rotation of the wheel is no longer synchronized with the beam current modulation. The results show
that the beam delivery is very sensitive to the wheel/current synchronization and that this has to be
part of routine daily quality assurance measurements.
3. Absolute dosimetry
For patient treatment, the proton fluence needed to deliver the prescribed dose is prescribed in
machine monitor units (MU). This unit corresponds to a fixed amount of charge collected in one of
the segmented transmission ionization chambers. The chambers have an area set-up for dosimetry
output. The so-called output factor is the number of MUs that deliver 1 cGy to a point in the patient,
i.e. a point in the water phantom for pre-treatment calibration. Currently the output factor is
determined either experimentally or predicted by analytical calculations (4). The agreement
between theses calculations and the measured output factors is quite good, i.e. 2.9% for all treated
fields so far. Despite the predictive power, the analytical method is limited by the ability to account
for beam shaping devices in the beam path, e.g. for aperture scattering.
By modeling the proton beam delivery nozzle with high accuracy, including areas used for
dosimetry, we can use Monte Carlo simulations for absolute dosimetry. We simulate directly the
charge that would be collected in the ionization chamber determined by the particle fluence. The
agreement between the Monte Carlo simulations and measurements is excellent. In addition,
absolute doses as a function of machine monitor units were calculated for CT based patient
geometry.
4. Treatment planning
After implementing CT data readability into the GEANT4 package we compared the Monte Carlo
dose calculation with our treatment planning program FOCUS (Computerized Medical Systems,
Inc.) based on a pencil-beam dose calculation algorithm. From the treatment planning program the
gantry and nozzle parameters (beam energies, treatment angles etc.) were extracted and used as
input parameters into the Monte Carlo code. The simulations are not based on pre-calculated phase
space distributions and include the whole treatment nozzle. Re-calculation of proton therapy
treatment plans takes only a few hours on our LINUX cluster. This efficiency was reached by
modifying some of the geometry and tracking functions in the original GEANT4 source code but
without compromising physics accuracy. The relative dose distributions generated by the FOCUS
pencil beam algorithm and the ones generated by the GEANT4 Monte Carlo are in very good
agreement. Figure 2 illustrates the dose distributions for each of the three treatment fields for one
lung patient.
By adopting the 4D Monte Carlo technique used for the modulator wheel rotation we implemented
motion effects into the CT-data geometry. Doing so we introduced a technique, i.e. 4D Monte
Carlo, which is presumably the most accurate method to study organ motion effects with high
temporal resolution (5). The Monte Carlo geometry can follow, nearly continuously, a patient’s
breathing pattern. The technique can be applied assuming artificial motion kernels or using patient
specific 4D CT information (4D CT data are available at our institution (6)). Using deformable
4
image registration within the Monte Carlo run allows dose calculations to be based on the exact
patient’s breathing pattern independent of the number of distinct breathing phases extracted during
4D CT. The local dose is calculated as a function of well-defined sub-volumes (voxel descriptors)
and not as a function of position in a fixed coordinate system. Motion effects were analyzed using
dose-volume histograms (5).
Figure 2: Dose distribution shown for one CT slice for a three-field proton therapy plan for a lung
cancer patient. The first row shows the result, per field, of the FOCUS treatment planning program,
the second row shows the Monte Carlo results obtained with GEANT4. The unusual display for the
individual fields in terms of the dose ranges for the isodose lines and color codes is used to
demonstrate the agreement of the calculations with respect to the beam penumbra. The isodose
colors for the total dose distribution correspond to 99% prescription dose (red), 95% (green), 90%
(blue), 80% (yellow), 70% (cyan), 60% (magenta), 50% (orange), 30% (purple), 10% (brown). The
figures at the bottom give the total distributions obtained by FOCUS and the Monte Carlo
simulation.
IV. Conclusion
We demonstrated various applications of Monte Carlo simulations in proton radiation therapy.
Simulations are very helpful for designing a new facility, for quality assurance, and for supporting
every day operation. In particular we were able to determine the descriptors of the depth dose
distribution that we are able to deliver, as well as calculate tolerances on the appropriate operational
parameters for beam delivery to design quality assurance procedures. The GEANT4 Monte Carlo
package can be applied for precise beam simulations in proton therapy if the treatment head is
modeled down to millimeter accuracy. For Monte Carlo dose calculation using patient geometry a
detailed simulation of the treatment head is mandatory.
5
In efforts towards Monte Carlo treatment planning for protons we accomplished the implementation
of CT data information into the GEANT4 package to re-calculate treatment plans. The efficiency of
the GEANT4 package was improved and novel solutions to define patient geometries were found.
By using the 4D Monte Carlo technique, organ motion effects were studied.
V. References
(1) H. Paganetti, H. Jiang, S.-Y. Lee, H. Kooy, “Accurate Monte Carlo for nozzle design,
commissioning, and quality assurance in proton therapy.” Med. Phys. submitted, December
2003.
(2) S. Agostinelli, J. Allison, K. Amako, J. Apostolakis, H. Araujo, et al., “GEANT4 - a simulation
toolkit,” Nucl. Inst. Methds. Phys. Res. A 506, 250-303 (2003).
(3) H. Paganetti, “Four-dimensional Monte Carlo simulation of time dependent geometries,” Phys.
Med. Biol., (2004) in press.
(4) H. Kooy, M. Schaefer, S. Rosenthal, T. Bortfeld, “Monitor unit calculations for rangemodulated spread-out Bragg peak fields.” Phys. Med. Biol. 48, 2797-2808 (2003).
(5) H. Paganetti, H. Jiang, E. Rietzel, J.A. Adams, G.T.Y. Chen, “The potential of four-dimensional
Monte Carlo dose calculation for investigating organ motion effects with high temporal
resolution.” Int. J. Radiat. Oncol. Biol. Phys., submitted, February 2004.
(6) E. Rietzel, T. Pan, G.T.Y. Chen, “4D Computed Tomography: image formation and clinical
protocol.” Med. Phys., submitted, February 2004.
6