Towards efficient and accurate particle transport simulation in medical applications
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1 Towards efficient and accurate particle transport simulation in medical applications L. Grzanka1,2, M. Kłodowska1, N. Mojżeszek1, N. Bassler3 1 Cyclotron Centre Bronowice, Institute of Nuclear Physics (IFJ PAN), Kraków, Poland, 2 AGH University of Science and Technology, Kraków, Poland, 3 Stockholm University, Stockholm, Sweden Leszek.Grzanka@ifj.edu.pl
2 Cancer and radiotherapy New and innovative technique Long history Rare (1 center in Poland) Popular (~120 accelerators) <200 patients per year ~70000 patients per year Proton beam generated by cyclotron - large facility Beam of X-rays, compact linear No exit-beam, more healthy tissue spared More complexity in physics of the beam accelerator in use Simpler physics involved
3 Proton therapy is booming
4 Cyclotron Center Bronowice in Krakow proton therapy plans CCB project starts first patients with eye tumors new cyclotron and building first patient treated on gantry Robotic gantry rotates around the patient Cyclotron delivers beam of protons with max energy 230 MeV (~30 cm range in water) CCB: patient treatments, experimental physics research, applied physics
5 Monte Carlo Simulation of a proton beam Aim: simulate proton beam: - dose spatial distribution - complex (patient) geometry Tools: Monte Carlo transport codes: Fluka Geant4.96 Time consuming simulation of particle interactions with matter (Embarrassingly) parallelization - procedure
6 Proton microbeam radiotherapy New concept: broad beam filtered by slits. Close to skin damage in narrow channels - benefit from dose-volume effect. Beam scattering with depth. FLUKA MC code: 100 μm proton beam with active pencil-beam scanning mode MeV, 1-8 mm beam spacing 10^5 protons/spot in 10 runs ( spots / energy)
7 Proton spatially fractionated radiotherapy 5*10^8 particles simulated (SHIELD-HIT12A code) 500 parallel jobs, each 6hours of CPU time Simulation of dose distribution delivered by beam available in CCB (IFJ PAN Krakow), filtered by 1mm slit collimator. Geometry represents setup used in radiobiology experiment.
8 Verification of a proton pencil beam model in the treatment planning system (TPS) Parameters like position, energy and weight of each proton pencil beam are calculated in the treatment planning system (TPS) and optimized to achieve uniform dose distribution in the tumour while sparing healthy organs in close region to the irradiated volume. Fig. Pencil beam scanning technique. Dose distribution calculated in the TPS TPS - analytical algorithms based on simplified physical models (gaussian scattering in water and air). Some disagreement with measurement is observed. Fig. Dose distribution calculated treatment planning system. in the
9 Verification of a proton pencil beam model in the treatment planning system (TPS) Treatment planning system Monte Carlo transport code 2*10^8 particles in 25 runs Fig. Lateral beam profiles in water at depth of 200 mm of a single pencil beam of energy MeV calculated in FLUKA Monte Carlo code and in Eclipse treatment planning system.
10 Towards Monte-Carlo based treatment planning Simulations of particle interaction in geometries based on patient CT scans. Novel algorithm implemented in SHIELD-HIT12A MC transport code. Time and memory consuming calculations: - ~ 10GB RAM per node - 10^8 particles - 3h of CPU time on 100 nodes Dose distribution Proton fluence Neutron fluence
11 Ecosystem of tools, codes and projects Monte Carlo particle transport codes: Tools and toolkits essential for users
12 Simplifying embarassing parallelization Development: L. Grzanka, A. Rudnicka generatemc -j 100 -p beam.conf Input file Single-file executable (no external deps) No of jobs Particles per job
13 Minimizing total computing time How to parallelize? 10^6 protons on 1000 nodes, or 10^7 protons on 100 nodes, or 10^8 protons on 10 nodes? Concept from Implementation in mcpartools - in progress (P. Ociepka) T(n) - total computing time n - number of nodes p - number of particles α - calc. time per particle β*n - initialization and merging results time (linear) γ - initialization time (fixed)
14 Thank you for attention!
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