Title:
Design and development of a new micro-beam treatment planning system: effectiveness of algorithms of optimization and dose calculations and potential of micro-beam treatment.

Abstract:
A new treatment planning system (TPS) was designed and developed for a new treatment system, which consisted of a micro-beam-enabled linac with robotics and a real-time tracking system. We also evaluated the effectiveness of the implemented algorithms of optimization and dose calculations in the TPS for the new treatment system. In the TPS, the optimization procedure consisted of the pseudo Beam's-Eye-View method for finding the optimized beam directions and the steepest-descent method for determination of beam intensities. We used the superposition-/convolution-based (SC-based) algorithm and Monte Carlo-based (MC-based) algorithm to calculate dose distributions using CT image data sets. In the SC-based algorithm, dose density scaling was applied for the calculation of inhomogeneous corrections. The MC-based algorithm was implemented with Geant4 toolkit and a phase-based approach using a network-parallel computing. From the evaluation of the TPS, the system can optimize the direction and intensity of individual beams. The accuracy of the dose calculated by the SC-based algorithm was less than 1% on average with the calculation time of 15 s for one beam. However, the MC-based algorithm needed 72 min for one beam using the phase-based approach, even though the MC-based algorithm with the parallel computing could decrease multiple beam calculations and had 18.4 times faster calculation speed using the parallel computing. The SC-based algorithm could be practically acceptable for the dose calculation in terms of the accuracy and computation time. Additionally, we have found a dosimetric advantage of proton Bragg peak-like dose distribution in micro-beam treatment.