Abstract

Four-dimensional (4D) treatment planning requires more man hours as compared to 3D treatment planning. The implementation of automated solutions that complete time consuming tasks is critical for the successful implementation of 4D treatment planning. Currently, a platform specially designed for clinical integration of 4D planning is not readily available. This dissertation presents an effort to develop an Automatic Post-processing Tool for 4D treatment planning (APT4D) that enables the user to perform the necessary procedures related to 4D treatment planning. The basic workflow of 4D planning involves automated image registration, automatic propagation of regions of interest, dose distribution transformation, and generation of deliverable 4D intensity pattern that can be executed by the user's treatment modality. The graphic user interface of APT4D was developed using Matlab 6.5. Both rigid and Demons-based deformable registrations are performed to map the moving phase images (such as the end-inhalation phase or 0% phase) to the fixed phase (typically the end-exhalation phase or 50% phase). The quality of image registration was evaluated slice by slice using an image similarity coefficient. Contours were automatically propagated into the moving phase using the image registration results. The match index was used to assess the quality of the contour propagation as compared to the manual contours. The dose distribution of each moving phase was transformed to the fixed phase and subsequently was summed as an average with equal weighting factor. To validate the application of APT4D utility, the 4D CT images of a thoracic cancer patient, an abdominal cancer patient and two kinds of dynamic thoracic phantom were acquired and resorted into ten respiratory phases. The 4D plans based on the 4D CT images were developed. The 4D plan was verified on the phantom plan: 4D delivery using the 0% phase and 50% phase plan with half of planned monitor units. The 3D conventional plan with radiation delivery in the absence of motion (50% phase plan with static beam-static target) and 3D conventional plan with small and large treatment margin in the presence of motion (50% phase plan with static beam-moving target) were compared to the 4D plan delivery respectively. The image correlation coefficient ranged from 0.992 to 0.999 for the resampled deformed moving phase image against the fixed phase image for the lung patient plan and from 0.977 to 0.999 for the abdominal patient plan. As for the phantom data, the image correlation coefficient was increased up to 1.0 after registration. The match indices between the manual contours and automatic contour propagation results ranged from 0.91 to 0.95 for all the tested organs and were up to 0.98 for the phantoms. Dosimetric reduction for cord was found for 4D planning compared to 3D planning. The 4D plan delivery agreed with the 4D planned dose within 3% in point dose measurements and did reproduce the measurements in the absence of target motion. In summary, the APT4D platform adds automation, efficiency, and functionality, while integrating the whole process of 4D treatment planning.