Virtual particle based Monte Carlo dose calculation for charged particle therapy treatment planning
AssigneeMayo Foundation for Medical Education and Research
InventorsWei Liu, Jie Shan
Life of this patent
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Abstract
Radiation treatment planning for charged particle therapy systems, such as proton therapy systems, includes calculating dose distribution(s) using a virtual particle Monte Carlo (“VPMC”) dose calculation engine that utilizes virtual particles. Virtual particles inherit the physical properties from realistic particles, but are conceptually designed for parallel computing in graphics processing units (“GPUs”) by avoiding the simulation of secondary particles. Simulation of virtual particles instead of realistic particles takes full advantage of the GPU hardware architecture (e.g., by avoiding thread divergence and racing conditions).
Claims18
A treatment planning system for use with a charged particle therapy system, comprising:
- a memory having stored thereon:
- a pre-calculated continuous-slowing-down-approximation (CSDA) model comprising probability distribution functions (PDFs) of physics parameters associated with soft particle interactions of virtual particles;
- a pre-calculated ionization model comprising PDFs of physics parameters associated with ionization of virtual particles;
- and
- a pre-calculated large angle scattering event (LAE) model comprising PDFs of physics parameters associated with hard particle interactions of virtual particles;
- a graphics processing unit (GPU) configured to:
- load the CSDA model, the ionization model, and the LAE model into a shared memory of the GPU;
- simulate virtual particles using the CSDA model, the ionization model, and the LAE model, wherein the virtual particles are simulated by simulating both primary charged particles and secondary particles as virtual particles that start at a same starting location of a primary charged particle;
- and
- calculate a dose distribution of the primary charged particles and the secondary particles based on the simulated virtual particles;
- wherein the GPU is configured to simulate virtual particles by:
- assigning each virtual particle to a thread of the GPU thereby minimizing thread divergence and racing conditions in the GPU;
- and
- in each of a plurality of steps:
- calculating a phase space for each virtual particle based on at least one of the CSDA model, the ionization model, or the LAE model;
- and
- updating each virtual particle based on the calculated phase space.
A method for generating treatment plan data for use with a charged particle therapy system, the method comprising:
- (a) loading to a shared memory of a graphics processing unit (GPU):
- a pre-calculated continuous-slowing-down-approximation (CSDA) model comprising probability distribution functions (PDFs) of physics parameters associated with soft particle interactions of virtual particles;
- a pre-calculated ionization model comprising PDFs of physics parameters associated with ionization of virtual particles;
- and
- a pre-calculated large angle scattering event (LAE) model comprising PDFs of physics parameters associated with hard particle interactions of virtual particles;
- (b) simulating virtual particles using the GPU, wherein simulating the virtual particles comprises simulating both primary charged particles and secondary particles as virtual particles that start at a same starting location of a primary charged particle by assigning each virtual particle to a thread of the GPU thereby minimizing thread divergence and racing conditions in the GPU, and in each of a plurality of steps:
- calculating a phase space for each virtual particle based on at least one of the CSDA model, the ionization model, or the LAE model;
- and
- updating each virtual particle based on its calculated phase space;
- (c) generating dose distribution data based on dose scoring the simulated virtual particles using a computer system;
- and
- (d) storing the dose distribution data as part of treatment plan data for use with a charged particle therapy system.
Dependencies are inferred from the claim text.