Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT (CBCT) scans has become a serious concern. Patient-specific imaging dose calculation has been proposed for the purpose of dose management. While Monte Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers from low computational efficiency. In response to this problem, we have successfully developed a MC dose calculation package, gCTD, on GPU architecture under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray imaging dose received by a patient during a CT or CBCT scan. Techniques have been developed particularly for the GPU architecture to achieve high computational efficiency. Dose calculations using CBCT scanning geometry in a homogeneous water phantom and a heterogeneous Zubal head phantom have shown good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In terms of improved efficiency, it is found that gCTD attains a speed-up of ~400 times in the homogeneous water phantom and ~76.6 times in the Zubal phantom compared to EGSnrc. As for absolute computation time, imaging dose calculation for the Zubal phantom can be accomplished in ~17 sec with the average relative standard deviation of 0.4%. Though our gCTD code has been developed and tested in the context of CBCT scans, with simple modification of geometry it can be used for assessing imaging dose in CT scans as well.Comment: 18 pages, 7 figures, and 1 tabl

Prospects for SIMPLE 2000: A large-mass, low-background Superheated Droplet Detector for WIMP searches

SIMPLE 2000 (Superheated Instrument for Massive ParticLE searches) will consist of an array of eight to sixteen large active mass ($\sim15$ g) Superheated Droplet Detectors(SDDs) to be installed in the new underground laboratory of Rustrel-Pays d'Apt. Several factors make of SDDs an attractive approach for the detection of Weakly Interacting Massive Particles (WIMPs), namely their intrinsic insensitivity to minimum ionizing particles, high fluorine content, low cost and operation near ambient pressure and temperature. We comment here on the fabrication, calibration and already-competitive first limits from SIMPLE prototype SDDs, as well as on the expected immediate increase in sensitivity of the program, which aims at an exposure of $>$25 kg-day during the year 2000. The ability of modest-mass fluorine-rich detectors to explore regions of neutralino parameter space beyond the reach of the most ambitious cryogenic projects is pointed out.Comment: 19 pages, 10 figures included. New Journal of Physics, in pres

Large-Mass Ultra-Low Noise Germanium Detectors: Performance and Applications in Neutrino and Astroparticle Physics

A new type of radiation detector, a p-type modified electrode germanium diode, is presented. The prototype displays, for the first time, a combination of features (mass, energy threshold and background expectation) required for a measurement of coherent neutrino-nucleus scattering in a nuclear reactor experiment. The device hybridizes the mass and energy resolution of a conventional HPGe coaxial gamma spectrometer with the low electronic noise and threshold of a small x-ray semiconductor detector, also displaying an intrinsic ability to distinguish multiple from single-site particle interactions. The present performance of the prototype and possible further improvements are discussed, as well as other applications for this new type of device in neutrino and astroparticle physics (double-beta decay, neutrino magnetic moment and WIMP searches).Comment: submitted to Phys. Rev.

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

GATE : a simulation toolkit for PET and SPECT

Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/

Validation of a small-animal PET simulation using GAMOS: a Geant4-based framework

onte Carlo-based modelling is a powerful tool to help in the design and optimization of positron emission tomography (PET) systems. The performance of these systems depends on several parameters, such as detector physical characteristics, shielding or electronics, whose effects can be studied on the basis of realistic simulated data. The aim of this paper is to validate a comprehensive study of the Raytest ClearPET small-animal PET scanner using a new Monte Carlo simulation platform which has been developed at CIEMAT (Madrid, Spain), called GAMOS (GEANT4-based Architecture for Medicine-Oriented Simulations). This toolkit, based on the GEANT4 code, was originally designed to cover multiple applications in the field of medical physics from radiotherapy to nuclear medicine, but has since been applied by some of its users in other fields of physics, such as neutron shielding, space physics, high energy physics, etc. Our simulation model includes the relevant characteristics of the ClearPET system, namely, the double layer of scintillator crystals in phoswich configuration, the rotating gantry, the presence of intrinsic radioactivity in the crystals or the storage of single events for an off-line coincidence sorting. Simulated results are contrasted with experimental acquisitions including studies of spatial resolution, sensitivity, scatter fraction and count rates in accordance with the National Electrical Manufacturers Association (NEMA) NU 4-2008 protocol. Spatial resolution results showed a discrepancy between simulated and measured values equal to 8.4% (with a maximum FWHM difference over all measurement directions of 0.5 mm). Sensitivity results differ less than 1% for a 250–750 keV energy window. Simulated and measured count rates agree well within a wide range of activities, including under electronic saturation of the system (the measured peak of total coincidences, for the mouse-sized phantom, was 250.8 kcps reached at 0.95 MBq mL−1 and the simulated peak was 247.1 kcps at 0.87 MBq mL−1). Agreement better than 3% was obtained in the scatter fraction comparison study. We also measured and simulated a mini-Derenzo phantom obtaining images with similar quality using iterative reconstruction methods. We concluded that the overall performance of the simulation showed good agreement with the measured results and validates the GAMOS package for PET applications. Furthermore, its ease of use and flexibility recommends it as an excellent tool to optimize design features or image reconstruction techniques

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