title: Monte Carlo-based inverse treatment planning.
abstract: A Monte Carlo based inverse treatment planning system (MCI) has been developed which combines arguably the most accurate dose calculation method (Monte Carlo particle transport) with a 'guaranteed' optimization method (simulated annealing). A distribution of photons is specified in the tumour volume; they are transported using an adjoint calculation method to outside the patient surface to build up an intensity distribution. This intensity distribution is used as the initial input into an optimization algorithm. The dose distribution from each beam element from a number of fields is pre-calculated using Monte Carlo transport. Simulated annealing optimization is then used to find the weighting of each beam element, to yield the optimal dose distribution for the given criteria and constraints. MCI plans have been generated in various theoretical phantoms and patient geometries. These plans show conformation of the dose to the target volume and avoidance of critical structures. To verify the code, an experiment was performed on an anthropomorphic phantom.
authors.affiliation: Reactor Physics Division, Jozef Stefan Institute, Ljubljana, Slovenia. robert.jeraj@ijs.si
authors.forename: R
authors.initials: R
authors.lastname: Jeraj
authors.forename: P
authors.initials: P
authors.lastname: Keall
mesh_terms: D000465:Algorithms; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D008962:Models, Theoretical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods