Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80-90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400-800 respectively compared to corresponding GATE simulations.

International audienceCharged product multiplicities and Z distributions were measured for single multifragmenting sources produced in collisions between Full-size image (<1 K) and Full-size image (<1 K) at the same available energy per nucleon. Z distributions are found identical for both reactions while fragment multiplicities scale as the charge of the total systems. A complete dynamical simulation, in which multifragmentation originates in the spinodal decomposition of a finite piece of nuclear matter resulting from an incomplete fusion of projectile and target, well accounts for this experimental observation

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