“A Monte Carlo inverse treatment planning algorithm for trajectory-based volumetric modulated arc therapy with applications in stereotactic radiosurgery, total body irradiation and patient-specific quality assurance”

Final PhD Oral Examination

Abstract:
The main objective of this thesis is to present a full Monte Carlo (MC)-based inverse treatment planning method for trajectory-based volumetric modulated arc therapy (TVMAT). TVMAT uses continuous and simultaneous gantry and couch rotation to avoid organs at risk (OARs) in the path of beam delivery, and thus it reduces the radiation exposure of normal tissues. However, commercial treatment planning systems do not provide dose calculation of such a beam trajectory. 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, we 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 was performed in a single MC simulation, thereby greatly reducing computation time. We select 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 a beam source that allows simulations of complex continuous beam delivery.

We modified a general-purpose MC code system in order to generate four-dimensional dose files that score individual, time-stamped, energy deposition events in the voxels of the planning target volume and OARs.

Consequently, a relation is established between the space and time coordinates of source particles in the phase space and their contribution to energy deposition. A MC-based direct aperture optimization, with a dose-volume constraint based quadratic objective function, is performed using an in-house code, taking into account the continuous movement of the MLC, gantry and couch between adjacent control points. This method is also applicable to beam delivery with either fixed couch position for VMAT or couch translation for long-field treatments. It is shown that this novel treatment planning algorithm is capable of generating plans that are generally of higher quality than those generated by standard planning systems.