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

Effect of Statistical Fluctuation in Monte Carlo Based Photon Beam Dose Calculation on Gamma Index Evaluation

The gamma-index test has been commonly adopted to quantify the degree of agreement between a reference dose distribution and an evaluation dose distribution. Monte Carlo (MC) simulation has been widely used for the radiotherapy dose calculation for both clinical and research purposes. The goal of this work is to investigate both theoretically and experimentally the impact of the MC statistical fluctuation on the gamma-index test when the fluctuation exists in the reference, the evaluation, or both dose distributions. To the first order approximation, we theoretically demonstrated in a simplified model that the statistical fluctuation tends to overestimate gamma-index values when existing in the reference dose distribution and underestimate gamma-index values when existing in the evaluation dose distribution given the original gamma-index is relatively large for the statistical fluctuation. Our numerical experiments using clinical photon radiation therapy cases have shown that 1) when performing a gamma-index test between an MC reference dose and a non-MC evaluation dose, the average gamma-index is overestimated and the passing rate decreases with the increase of the noise level in the reference dose; 2) when performing a gamma-index test between a non-MC reference dose and an MC evaluation dose, the average gamma-index is underestimated when they are within the clinically relevant range and the passing rate increases with the increase of the noise level in the evaluation dose; 3) when performing a gamma-index test between an MC reference dose and an MC evaluation dose, the passing rate is overestimated due to the noise in the evaluation dose and underestimated due to the noise in the reference dose. We conclude that the gamma-index test should be used with caution when comparing dose distributions computed with Monte Carlo simulation

Detailed Analysis of Scatter Contribution from Different Simulated Geometries of X-ray Detectors.

Scattering is one of the main issues left in planar mammography examinations, as it degrades the quality of the image and complicates the diagnostic process. Although widely used, anti-scatter grids have been found to be inefficient, increasing the dose delivered, the equipment price and not eliminating all the scattered radiation. Alternative scattering reduction methods, based on postprocessing algorithms using Monte Carlo (MC) simulations, are being developed to substitute anti-scatter grids. Idealized detectors are commonly used in the simulations for the purpose of simplification. In this study, the scatter distribution of three detector geometries is analyzed and compared: Case 1 makes use of idealized detector geometry, Case 2 uses a scintillator plate and Case 3 uses a more realistic detector simulation, based on the structure of an indirect mammography X-ray detector. This paper demonstrates that common configuration simplifications may introduce up to 14% of underestimation of the scatter in simulation results

Thyroid Carcinoma Metastasis to Skull with Infringement of Brain: Treatment with Radioiodine

Background: Infringement by differentiated thyroid carcinoma on the brain is rare but, when suspected, the patient deserves special attention. A patient with an enlarging metastasis of thyroid carcinoma to the skull that was impinging on the brain illustrates diagnostic and therapeutic strategies applicable to the treatment of metastatic carcinoma. Methods: A case study was performed. Computed tomography (CT) and magnetic resonance imaging (MRI) were done, serum thyroglobulin was measured, and tumor responses to thyroxine and 131I treatments were monitored. Tumor dosimetry, enabled by scintigraphy with 131I employing single photon emission tomography fused with CT (SPECT-CT), was performed. Results: The metastasis was from a follicular variant of papillary thyroid carcinoma. During thyrotropin stimulation the tumor enlarged. The tumor decreased in volume after each of two 131I therapies. Dosimetry indicated delivery of 1970 and 2870cGy to the tumor and 35 and 42cGy to the brain, respectively, in the two treatments. The patient has survived for more than 11 years since diagnosis. Conclusions: A metastasis from a follicular variant of papillary carcinoma increased in volume during hypothyroidism producing more infringement on the brain. Beyond the effects of thyroxine therapy, 131I treatments induced recession of tumor volume. In patients with metastases that concentrate 131I, dosimetry with SPECT-CT can predict absorbed doses of radiation to the tumor and to the adjacent organs and thus lay a basis for data-based decisions on 131I therapies. Therapy may induce prolonged survival in patients with metastases infringing on the brain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78102/1/thy.2008.0426.pd

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

Photon beam relative dose validation of the DPM Monte Carlo code in lung‐equivalent media

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134925/1/mp5671.pd

Benchmarking of the Dose Planning Method (DPM) Monte Carlo code using electron beams from a racetrack microtron

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135135/1/mp1512.pd

A fluence convolution method to account for respiratory motion in three‐dimensional dose calculations of the liver: A Monte Carlo study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134815/1/mp1412.pd

Accounting for center‐of‐mass target motion using convolution methods in Monte Carlo‐based dose calculations of the lung

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134807/1/mp9083.pd