Deformable image registration for cone-beam CT guided transoral robotic base-of-tongue surgery.

Transoral robotic surgery (TORS) offers a minimally invasive approach to resection of base-of-tongue tumors. However, precise localization of the surgical target and adjacent critical structures can be challenged by the highly deformed intraoperative setup. We propose a deformable registration method using intraoperative cone-beam computed tomography (CBCT) to accurately align preoperative CT or MR images with the intraoperative scene. The registration method combines a Gaussian mixture (GM) model followed by a variation of the Demons algorithm. First, following segmentation of the volume of interest (i.e. volume of the tongue extending to the hyoid), a GM model is applied to surface point clouds for rigid initialization (GM rigid) followed by nonrigid deformation (GM nonrigid). Second, the registration is refined using the Demons algorithm applied to distance map transforms of the (GM-registered) preoperative image and intraoperative CBCT. Performance was evaluated in repeat cadaver studies (25 image pairs) in terms of target registration error (TRE), entropy correlation coefficient (ECC) and normalized pointwise mutual information (NPMI). Retraction of the tongue in the TORS operative setup induced gross deformation >30 mm. The mean TRE following the GM rigid, GM nonrigid and Demons steps was 4.6, 2.1 and 1.7 mm, respectively. The respective ECC was 0.57, 0.70 and 0.73, and NPMI was 0.46, 0.57 and 0.60. Registration accuracy was best across the superior aspect of the tongue and in proximity to the hyoid (by virtue of GM registration of surface points on these structures). The Demons step refined registration primarily in deeper portions of the tongue further from the surface and hyoid bone. Since the method does not use image intensities directly, it is suitable to multi-modality registration of preoperative CT or MR with intraoperative CBCT. Extending the 3D image registration to the fusion of image and planning data in stereo-endoscopic video is anticipated to support safer, high-precision base-of-tongue robotic surgery.

Low-latency temporal filter design for real-time MRI using UNFOLD.

To improve real-time control of interventional procedures such as guidance of catheters, monitoring of ablation therapy, or control of dosage during drug delivery, the image acquisition and reconstruction must be high speed and have low latency (small time delay) in processing. A number of different methods have been demonstrated which increase the speed of MR acquisition by decreasing the number of sequential phase-encodes. A design and implementation of the UNFOLD method which achieves the desired low latency with a recursive temporal filter is presented. The recursive filter design is characterized for this application and compared with more commonly used moving average filters. Experimental results demonstrate low-latency UNFOLD for two applications: 1) high-speed, real-time imaging of the heart to be used in conjunction with cardiac interventional procedures; and 2) the injection of drugs into muscle tissue with contrast enhancement, i.e., monitoring needle insertion and injection of a drug with contrast enhancement properties. Proof-of-concept was demonstrated by injecting a contrast agent. In both applications the UNFOLD technique was used to double the frame rate.