Analysis and convergence of the iterative convolution/superposition dose reconstruction technique for multiple treatment beams and tomotherapy

An iterative convolution/superposition (C/S) algorithm has been created to reconstruct dose distributions in patients from exit dose measurements during a radiotherapy treatment. The method is based on an extended phantom which includes the patient CT representation and an electronic portal imaging device (EPID). The patient CT is assumed to be a true and rigid representation of the patient at the time of treatment. The C/S method computes the dose throughout the extended phantom which allows the exit dose to be predicted in the EPID. The process is then reversed to take the exit dose measurement and infer what the dose distribution must have been to produce the measured exit dose. The dose distribution is modeled without knowledge of the incident intensity distribution, and includes the effects of scatter in the computation. The iterative method begins by assuming that the exit primary energy fluence (PEF) is equal to the exit dose, the PEF is then backprojected through the extended phantom and superposed with the dose deposition kernel to determine a new prediction of the exit dose. The ratio of the computed PEF to exit dose is then multiplied by the measured exit dose image to produce a better representation of the exit PEF. Successive iterations then converge to the exit PEF image that would produce the measured exit dose image. Once convergence is established, the dose distribution is determined by backprojecting the exit PEF followed by superposition with the dose deposition kernel. The method is used to reconstruct the dose from a simulated dynamic wedge and verified with film. Convergence and termination of the algorithm is then investigated with no noise and in the presence of noise. The method is then expanded to handle multiple treatment beams by separating the representation of the EPID from the patient or phantom representation in the computation process. Investigation of the effects of noise during the process of iterative dose reconstruction is necessary to understand the capabilities of the algorithm using exit dose images that may contain significant amounts of noise. The capability of the algorithm is evaluated for multiple field treatments to a cube phantom and a prostate patient CT representation in the presence of noise. The method is then used to simulate the dose reconstruction process for tomotherapy using 72 intensity-modulated fan beams. Dose reconstruction is shown to be capable of verifying the dose distributions in patients including multiple beams and dynamic collimation, provided the patient CT is known at the time of treatment.