Departmental Oral Examination (Thesis Title: “A Monte Carlo inverse treatment planning algorithm for trajectory-based VMAT with simultaneous couch and gantry rotation”)

Abstract:
The main objective of this thesis is to present a non-hybrid Monte Carlo (MC) based inverse treatment planning for trajectory-based volumetric modulated arc therapy (TVMAT). With the use of continuous and simultaneous gantry and couch rotation, a higher dosimetric plan quality can be achieved. However, commercial treatment planning systems do not provide such a capability. It has been shown that a full MC based optimization greatly reduces the optimization convergence errors. Previously published approaches to MC based optimization have not been clinically implemented, and none has been proposed for VMAT or TVMAT so far. In this work, the author has developed a method that reflects the dynamic multi-leaf collimator (MLC) and gantry-couch trajectory of the actual beam delivery at all stages of the optimization. Dose optimization is performed in a single MC simulation, thereby greatly reducing calculation time. The author selects the initial trajectory (i.e. the range of the gantry, collimator and couch angles) and the initial set of leaf positions, corresponding to a dynamic beam conformal to the target. The MC simulation starts from a phase space scored at the top of the MLC module and uses ‘source 20’ of DOSXYZnrc. The author modifies DOSXYZnrc in order to generate a four-dimensional dose file that scores individual, time-stamped, energy deposition events in the voxels of the planning target volume (PTV) and organs at risk (OAR). Consequently, a relation is established between the space and time (i.e. MU index) coordinates of source particles in the phase space and their contribution to energy deposition. A direct-aperture optimization, with a dose-volume histogram based quadratic objective function, is performed using an in-house code, taking rigorously into account the continuous movement of the MLC, gantry and couch between adjacent control points. Clinically acceptable PTV coverage and OAR sparing have been achieved with this trajectory-based MC optimization..