2/28/2023 0 Comments Simpleauthority![]() Ideally, for clinical implementation, the MC simulations are to be accomplished in minutes or seconds. Many proton trajectories are simulated in order to obtain small random statistical variations in radiation dose predictions in the patient. In the MC-based RTP process, complex microscopic interactions between protons and the tumor medium are randomly sampled. The MC approach is particularly powerful when the tumor is surrounded by healthy critical organs that must be spared from radiation exposure and traditional analytical approaches are not sufficiently accurate. 6 through 10) once the obstacle of long computation times is overcome. 5 Several studies suggested that the MC technique will become possible for routine RTP (Refs. However, some cases call for dose predictions using the Monte Carlo (MC) method, 2 which provides superior accuracy 3 and additional capabilities, such as absolute dosimetry 4 and predictions of doses from stray and leakage radiation. Dose calculations for proton RTP are usually performed with analytical methods 1 because of these methods’ high computational speed and adequate accuracy. Extrapolation of our results indicates that about 10 3 processor cores of the class used here would reduce the MC simulation runtime from 18.3 days to ~1 h.Įxternal-beam radiotherapy treatment planning (RTP) is a process in which radiation fields are custom designed to maximize dose to the tumor while minimizing dose to surrounding healthy tissues. The results indicate that ~3 × 10 5 to 5 × 10 5 proton events with processor core would result in 65 to 83% efficiency. The simulation speedup was approximately linear deviations were attributed to the spectrum of parallel runtimes and communication overhead due to Medical Grid computing. Preliminary computational experiments were carried out in the GEANT4 simulation environment for transport of 25 ×10 6 200 MeV protons in a prostate cancer treatment plan. As proof of concept we created the Medical Grid between Texas Tech University and Rice University. The objective of this work was to extend a Monte Carlo (MC) transport code used for proton radiotherapy to utilize grid computing techniques and demonstrate its promise in reducing runtime from days to minutes. The grid approach is especially important for computationally intensive problems that are not tractable with a single computer or even with a small cluster of computers, e.g., radiation transport calculations for cancer therapy. Grid computing is an emerging technology that enables computational tasks to be accomplished in a collaborative approach by using a distributed network of computers.
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