A C-arm fluoroscopy-guided progressive cut refinement strategy using a surgical robot.

We describe a new method to cut a precise, high-quality femoral cavity in Revision Total Hip Replacement surgery (RTHR) using a surgical robot and an intra-operative C-arm fluoroscope. With respect to previous approaches, our method contains several new features. (1) We describe a novel checkerboard plate designed to correct the geometric distortion within fluoroscopic images. Unlike previous distortion correction devices, the plate does not completely obscure any part of the image, and the distortion correction algorithm works well even when there are some overlaid objects in the field of view. (2) Also included are a novel corkscrew fiducial object designed to be integrated with the robot end-effector, and a 6D pose estimation algorithm based on the two-dimensional (2D) projection of the corkscrew, used in robot-imager registration and imager co-registration. (3) In addition, we develop a cavity location algorithm, which utilizes image subtraction and 2D anatomy contour registration techniques. (4) Finally, we propose a progressive cut refinement strategy, which progressively improves the robot registration during the procedure. We have conducted several experiments, in both simulated and in vitro environments. The results indicate that our strategy is a promising method for precise orthopedic procedures like total hip replacement.

Computer-integrated revision total hip replacement surgery: concept and preliminary results.

This paper describes an ongoing project to develop a computer-integrated system to assist surgeons in revision total hip replacement (RTHR) surgery. In RTHR surgery, a failing orthopedic hip implant, typically cemented, is replaced with a new one by removing the old implant, removing the cement and fitting a new implant into an enlarged canal broached in the femur. RTHR surgery is a difficult procedure fraught with technical challenges and a high incidence of complications. The goals of the computer-based system are the significant reduction of cement removal labor and time, the elimination of cortical wall penetration and femur fracture, the improved positioning and fit of the new implant resulting from precise, high-quality canal milling and the reduction of bone sacrificed to fit the new implant. Our starting points are the ROBODOC system for primary hip replacement surgery and the manual RTHR surgical protocol. We first discuss the main difficulties of computer-integrated RTHR surgery and identify key issues and possible solutions. We then describe possible system architectures and protocols for preoperative planning and intraoperative execution. We present a summary of methods and preliminary results in CT image metal artifact removal, interactive cement cut-volume definition and cement machining, anatomy-based registration using fluoroscopic X-ray images and clinical trials using an extended RTHR version of ROBODOC. We conclude with a summary of lessons learned and a discussion of current and future work.

Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot.

We describe new methods for rigid registration of a preoperative computed tomography (CT)-scan image to a set of intraoperative X-ray fluoroscopic images, for guiding a surgical robot to its trajectory planned from CT. Our goal is to perform the registration, i.e., compute a rotation and translation of one data set with respect to the other to within a prescribed accuracy, based upon bony anatomy only, without external fiducial markers. With respect to previous approaches, the following aspects are new: 1) we correct the geometric distortion in fluoroscopic images and calibrate them directly with respect to the robot by affixing to it a new calibration device designed as a radiolucent rod with embedded metallic markers, and by moving the device along two planes, while radiographs are being acquired at regular intervals; 2) the registration uses an algorithm for computing the best transformation between a set of lines in three space, the (intraoperative) X-ray paths, and a set of points on the surface of the bone (imaged preoperatively), in a statistically robust fashion, using the Cayley parameterization of a rotation; and 3) to find corresponding sets of points to the X-ray paths on the surfaces, our new approach consists of extracting the surface apparent contours for a given viewpoint, as a set of closed three-dimensional nonplanar curves, before registering the apparent contours to X-ray paths. Aside from algorithms, there are a number of major technical difficulties associated with engineering a clinically viable system using anatomy and image-based registration. To detect and solve them, we have so far conducted two experiments with the surgical robot in an operating room (OR), using CT and fluoroscopic image data of a cadaver bone, and attempting to faithfully simulate clinical conditions. Such experiments indicate that intraoperative X-ray-based registration is a promising alternative to marker-based registration for clinical use with our proposed method.

Optimal reference electrode selection for electric source imaging.

One goal of recording voltages on the scalp is to form images of electrical sources across the cerebral cortex (electric source imaging). In this study, an objective criterion is introduced for selecting the optimal location for the reference electrode to attain the maximum spatial resolution of the source image, for example as provided here by the truncated singular value decomposition pseudo-inverse solution. The head model features a realistic cortex within a 3-shell conductive sphere, and pyramidal cell activity is represented by 9104 normal current elements distributed across the cortical area. On the scalp, 234 electrodes provide the measurements with respect to a chosen reference electrode. The effects of the reference electrode when located at the mastoid, occipital pole, vertex or center of the head are analyzed by a singular value decomposition of the lead field matrices. Sensitivity to noise, and hence the spatial resolution, is found to depend on characteristics of the lead field matrix that are determined by the choice of the image source surface, electrode array and location of the reference electrode. Using a reference close to a source surface increases the sensitivity of the measurement system in identifying the nearby activity of low spatial frequency content. However, this feature is compromised by a reduction in spatial resolution for distant cortical areas due to noise in the measurements. A new performance measure, the image sensitivity map, is introduced to identify the cortical regions that provide peak image sensitivity. This measure may be exploited in designing the geometry of an electrode array and selecting the location of the reference electrode to follow the activity on a specific area of the cortical surface.