A technique is proposed for the development of an intraoperative, 3-dimensional registration of C-arm fluoroscopic images with spatially-registered ultrasound visualization and implant guidance of radioactive implants and on-line implant assessment during the procedure for treatment of prostate cancer. With present techniques using transrectal ultrasound guidance for brachytherapy, intra-operative localization of implanted seeds with respect to soft tissue anatomy is still an unsolved problem. Ultrasound (US) images provide satisfactory differentiation of relevant soft issue, but implanted brachytherapy seeds cannot be clearly identified in the US images. Currently sixty percent of the practitioners use intra-operative C-arm fluoroscopy as a qualitative check of the implants. While seeds can be accurately localized in X-ray, projected transluminal images do not reveal soft tissue anatomy. Hence, there is a standing clinical need to couple relevant information from C-arm with the US-guided delivery system, in a safe, robust, and cost-efficient manner. The goal of the proposed work is to implement intra-operative dosimetric quality assurance in transrectal US-guided prostate brachytherapy with the use of C-arm X-ray fluoroscopy. The specific objective of this program is to incorporate spatial location of implanted seeds determined from C-arm X-ray fluoroscopy images with soft tissue anatomy determined from ultrasound images. This will enable the actual dose distribution to be compared to the dose pre-plan and assessed while the implant process is underway. Thus, immediate therapeutic intervention would be possible to correct for any """"""""cold"""""""" regions or minimize """"""""hot"""""""" regions near critical structures and exactly """"""""match"""""""" the optimal source placement within the treatment volume. The outcome of this research could be of immediate benefit in the treatment of prostate cancer. It would provide the ability to visualize in real time the placement of implants, providing implants which reflect optimal dosimetry. A large group of patients with early-stage disease are candidates.
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