MR to Ultrasound Registration for Image-Guided Prostate Biopsy

Transrectal ultrasound (TRUS) guided prostate biopsy is the standard approach for diagnosis of prostate cancer (PCa). However, due to the lack of image contrast of prostate tumors, it often results in false negatives. Magnetic Resonance Imaging (MRI) has been considered to be a promising imaging modality for noninvasive identification of PCa, since it can provide a high sensitivity and specificity for the detection of early stage PCa. Our main objective is to develop a registration method of 3D MR-TRUS images, allowing generation of volumetric 3D maps of targets identified in 3D MR images to be biopsied using 3D TRUS images. We proposed an image-based non-rigid registration approach which employs the modality independent neighborhood descriptor (MIND) as the local similarity feature. An efficient duality-based convex optimization-based algorithmic scheme was introduced to extract the deformations. The registration accuracy was evaluated using 20 patient images by calculating the target registration error (TRE) using manually identified corresponding intrinsic fiducials. Additional performance metrics (DSC, MAD, and MAXD) were also calculated by comparing the MR and TRUS manually segmented prostate surfaces in the registered images. Experimental results showed that the proposed method yielded an overall median TRE of 1.76 mm. In addition, we proposed a surface-based registration method, which first makes use of an initial rigid registration of 3D MR to TRUS using 6 manually placed corresponding landmarks in each image. Following the manual initialization, two prostate surfaces are segmented from 3D MR and TRUS images and then non-rigidly registered using a thin-plate spline algorithm. The registration accuracy was evaluated using 17 patient images by measuring TRE. Experimental results show that the proposed method yielded an overall mean TRE of 2.24 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm