11 research outputs found
Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport
Monte Carlo simulation is the most accurate method for absorbed dose
calculations in radiotherapy. Its efficiency still requires improvement for
routine clinical applications, especially for online adaptive radiotherapy. In
this paper, we report our recent development on a GPU-based Monte Carlo dose
calculation code for coupled electron-photon transport. We have implemented the
Dose Planning Method (DPM) Monte Carlo dose calculation package (Sempau et al,
Phys. Med. Biol., 45(2000)2263-2291) on GPU architecture under CUDA platform.
The implementation has been tested with respect to the original sequential DPM
code on CPU in phantoms with water-lung-water or water-bone-water slab
geometry. A 20 MeV mono-energetic electron point source or a 6 MV photon point
source is used in our validation. The results demonstrate adequate accuracy of
our GPU implementation for both electron and photon beams in radiotherapy
energy range. Speed up factors of about 5.0 ~ 6.6 times have been observed,
using an NVIDIA Tesla C1060 GPU card against a 2.27GHz Intel Xeon CPU
processor.Comment: 13 pages, 3 figures, and 1 table. Paper revised. Figures update
GPU-based fast Monte Carlo simulation for radiotherapy dose calculation
Monte Carlo (MC) simulation is commonly considered to be the most accurate
dose calculation method in radiotherapy. However, its efficiency still requires
improvement for many routine clinical applications. In this paper, we present
our recent progress towards the development a GPU-based MC dose calculation
package, gDPM v2.0. It utilizes the parallel computation ability of a GPU to
achieve high efficiency, while maintaining the same particle transport physics
as in the original DPM code and hence the same level of simulation accuracy. In
GPU computing, divergence of execution paths between threads can considerably
reduce the efficiency. Since photons and electrons undergo different physics
and hence attain different execution paths, we use a simulation scheme where
photon transport and electron transport are separated to partially relieve the
thread divergence issue. High performance random number generator and hardware
linear interpolation are also utilized. We have also developed various
components to handle fluence map and linac geometry, so that gDPM can be used
to compute dose distributions for realistic IMRT or VMAT treatment plans. Our
gDPM package is tested for its accuracy and efficiency in both phantoms and
realistic patient cases. In all cases, the average relative uncertainties are
less than 1%. A statistical t-test is performed and the dose difference between
the CPU and the GPU results is found not statistically significant in over 96%
of the high dose region and over 97% of the entire region. Speed up factors of
69.1 ~ 87.2 have been observed using an NVIDIA Tesla C2050 GPU card against a
2.27GHz Intel Xeon CPU processor. For realistic IMRT and VMAT plans, MC dose
calculation can be completed with less than 1% standard deviation in 36.1~39.6
sec using gDPM.Comment: 18 pages, 5 figures, and 3 table
Comparison of nanodosimetric parameters of track structure calculated by the Monte Carlo codes Geant4-DNA and PTra
DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations
A new Monte Carlo (MC) algorithm, the `dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high-accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 1283 voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a `mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The δ-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48969/2/m00815.pd