Abstract. An image registration-based elastography algorithm is presented for assessing the stiffness of tissue regions inside the prostate for the purpose of detecting tumors. A 3D finite-element model of the prostate is built from ultrasound images and used to simulate the deformation of the prostate induced by a TRUS probe. To reconstruct the stiffness of tissues, their Young's moduli are varied using Powell's method so that the mutual information between a simulated and deformed image volume is maximized. The algorithm was validated using a gelatin prostate phantom embedded with a cylindrical inclusion that simulated a tumor. Results from the phantom study showed that the technique could detect the increased stiffness of the simulated tumor with a reasonable accuracy.

Proper targeting of radiation therapy during the treatment of prostate cancer requires the successful alignment of initial planning images with more recent ones taken during the treatment course. Prostatic displacement, if unaccounted for during the treatment course, can lead to radiation underdosage of the target area or radiation of the surrounding healthy tissue. Studies have shown that prostatic displacement is directly correlated with changes in the volume of the rectum. We have developed a non-rigid image registration system based on a biomechanical model of the prostate, rectum, and surrounding tissues, that incorporates statistical shape information about changes in the volume of the rectum. Using finite-element analysis and statistical shape models, our non-rigid registration method defines a mapping between two prostate image volumes. The proposed method assumes that the prostate image misregistration occurs as a result of changes in the rectum's shape. The change along the rectum's circumference was considered as the displacement boundary condition of the prostate's finite element model. As such we used a mutual information similarity measure in conjunction with the finite element model for computing the optimal boundary condition as well as estimating the location and relative Young's modulus of the central and peripheral zones within the prostate to the surrounding tissue. Compared to other techniques, this registration technique is not only efficient but also capable of providing valuable mechanical properties of tissue in vivo.