| Summary: | Low dose rate prostate brachytherapy has emerged as a treatment option for
localized prostate cancer. During prostate brachytherapy, tiny radioactive
capsules - seeds - are implanted inside the tissue using long needles. The quality of the treatment depends on the accuracy of seed delivery to their desired positions. Prostate deformation and displacement during insertion and lack of sufficient visual feedback complicate accurate targeting and necessitates extensive training on the part of the physician. Needle insertion simulators can be useful for physician training. In addition, insertion of the
needle with optimized parameters can compensate for prostate deformation,
can decrease the targeting errors and, subsequently, can increase the
post-treatment quality of life of the patients. Therefore, needle insertion
simulation and path planning have gained a lot of attention in the research community in the past decade. Moreover, several robots have been designed for brachytherapy; however, they are yet to be coupled with proper needle insertion path planning algorithms.
In this thesis, steps toward a path planning algorithm for needles are taken. An optimization method is proposed that updates the initial insertion parameters of a rigid needle, iteratively, based on the simulated positions of the targets, in order to reduce the error between the needle and several targets in a 3D tissue model. The finite element method is used in the needle insertion simulator. The simulator requires a model for the needle-tissue interaction. Therefore, an experimental method has been developed to identify the force model and the tissue elasticity parameters using
measurements of insertion force, tissue displacement and needle position.
Ultrasound imaging is used to measure tissue displacement. Ultrasound is a common imaging modality in the operating room and does not need beads or markers to track the tissue motion. Therefore, the experimental method can be used in patient studies. The needle-tissue modeling method and insertion parameter optimization were validated in experiments with tissue-mimicking phantoms.
In order to facilitate the accommodation of needle flexibility for future applications, three flexible needle models have been compared. Based on these comparisons, it was determined that an efficient and accurate angular spring model is best suited for future studies.
|
|---|
