Image registration for prostate MR spectroscopy using modeling and optimization of force and stiffness parameters

We develop an image registration system based on biomechanical modeling of the prostate and surrounding tissues to register cancerous tumor locations for targeted prostate brachytherapy treatment planning. Cancerous tumors can be identified using magnetic resonance spectroscopy (MRS) imaging, which is acquired with an endorectal probe that causes significant nonlinear deformation of the prostate. The probe is removed during magnetic resonance (MR) imaging for brachytherapy planning and therapy. Given 2-dimensional segmented MR and MRS images, our finite element based model defines a mapping between the probe-in/out images by estimating the deformation of the prostate and surrounding tissues due to endorectal probe insertion and balloon inflation. Treating uncertain patient-specific model parameters for tissue stiffness and external forces as variables, we compute a locally optimal solution to maximize image registration quality. We visualize results by applying the computed mapping to the MR image to generate a deformed MR image. We compare deformed MR images to corresponding MRS images for 5 patients and obtain an average dice similarity coefficient (DSC) of 95.6% for the prostate. Using the mapping, we warp a regular spectroscopy grid from the MRS image to the probe-out MR image for use during treatment planning.