Registration algorithms for interventional MRI-guided treatment of the prostate

We are investigating interventional MRI (iMRI) guided radiofrequency thermal ablation for the minimally invasive treatment of prostate cancer. Nuclear medicine and MR spectroscopy can detect and localize tumor in the prostate not reliably seen in MR. We are investigating methods to combine the advantages of functional images such as SPECT with iMRI-guided treatments. Our concept is to first register the low-resolution functional images with a high resolution MR volume. Then by registering the high-resolution MR image with live-time iMRI acquisitions, we can, in turn, map the functional data and high-resolution anatomic information to iMRI images for improved tumor targeting. In this study, we registered noisy, thick iMRI image slices with high-resolution MR volumes and called this slice-to-volume registration. We investigated two similarity measures, i.e., mutual information and correlation coefficient, and three interpolation methods, i.e., tri-linear, re-normalized sinc, and nearest neighbor. To assess the quality of registration, we calculated 3D displacement on a voxel-by-voxel basis over a volume of interest (VOI) between slice-to-volume registration and volume-to-volume registration that was previously shown to be quite accurate for these image pairs. Over 300 registration experiments showed that transverse slice images covering the prostate work best with a registration error of only 0.4 ± 0.2 mm. Error was greater at other slice orientations and positions. Since live-time iMRI images are used for guidance and registered images are used for adjunctive information, the accuracy and robustness of slice-to-volume registration is very probably adequate.