J.M. Fitzpatrick

Registration of head volume images using implantable fiducial markers

Describes an extrinsic-point-based, interactive image-guided neurosurgical system designed at Vanderbilt University, Nashville, TN, as part of a collaborative effort among the Departments of Neurological Surgery, Computer Science, and Biomedical Engineering. Multimodal image-to-image (II) and image-to-physical (IP) registration is accomplished using implantable markers. Physical space tracking is accomplished with optical triangulation. The authors investigate the theoretical accuracy of point-based registration using numerical simulations, the experimental accuracy of their system using data obtained with a phantom, and the clinical accuracy of their system using data acquired in a prospective clinical trial by 6 neurosurgeons at 4 medical centers from 158 patients undergoing craniotomies to respect cerebral lesions. The authors can determine the position of their markers with an error of approximately 0.4 mm in X-ray computed tomography (CT) and magnetic resonance (MR) images and 0.3 mm in physical space. The theoretical registration error using 4 such markers distributed around the head in a configuration that is clinically practical is approximately 0.5-0.6 mm. The mean CT-physical registration error for the: phantom experiments is 0.5 mm and for the clinical data obtained with rigid head fixation during scanning is 0.7 mm. The mean CT-MR registration error for the clinical data obtained without rigid head fixation during scanning is 1.4 mm, which is the highest mean error that the authors observed. These theoretical and experimental findings indicate that this system is an accurate navigational aid that can provide real-time feedback to the surgeon about anatomical structures encountered in the surgical field.

The distribution of target registration error in rigid-body point-based registration

Guidance systems designed for neurosurgery, hip surgery, spine surgery and for approaches to other anatomy that is relatively rigid can use rigid-body transformations to accomplish image registration. These systems often rely on point-based registration to determine the transformation and many such systems use attached fiducial markers to establish accurate fiducial points for the registration, the points being established by some fiducial localization process. Accuracy is important to these systems, as is knowledge of the level of that accuracy. An advantage of marker-based systems, particularly those in which the markers are bone-implanted, is that registration error depends only on the fiducial localization and is, thus, to a large extent independent of the particular object being registered. Thus, it should be possible to predict the clinical accuracy of marker-based systems on the basis of experimental measurements made with phantoms or previous patients. For most registration tasks, the most important error measure is target registration error (TRE), which is the distance after registration between corresponding points not used in calculating the registration transform. Here, the authors derive an approximation to the distribution of TRE; this is an extension of previous work that gave the expected squared value of TRE. They show the distribution of the squared magnitude of TRE and that of the component of TRE in an arbitrary direction. Using numerical simulations, the authors show that their theoretical results are a close match to the simulated ones.

Validation of medical image processing in image-guided therapy

Do we need an abstract ?.

Retrospective intermodality registration techniques for images of the head: surface-based versus volume-based

A blinded evaluation of two groups of retrospective image registration techniques was performed using as a gold standard a prospective marker-based registration method, and we compared the performance of one group with the other. By grouping the techniques as volume-based or surface-based, we could make some interesting conclusions. In order to ensure blindness, all retrospective registrations were performed by participants who had no knowledge of the gold-standard results until after their results had been submitted. Image volumes of three modalities (X-ray CT, MRI and PET) were obtained from patients undergoing neurosurgery on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to outside collaborators, who then performed retrospective registrations on the volumes, calculating transformations from CT to MRI and/or from PET to MRI. The accuracy of each registration was then evaluated. The accuracy is measured at multiple volumes of interest. The volume-based techniques in this study tended to give substantially more accurate and reliable results than the surface-based ones for the CT-to-MRI registration tasks, and slightly more accurate results for the PET-to-MRI tasks. Analysis of these results revealed that the rotational component of error was more pronounced for the surface-based group. It was also apparent that all of the registration techniques we examined have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.

Effect of geometrical distortion correction in MR on image registration accuracy

In this article we investigate the effect of geometrical distortion correction in MR images on the accuracy of the registration of X-ray CT and MR head images for both a fiducial marker (extrinsic point) method and a surface-matching technique. We use CT and T2-weighted MR image volumes acquired from seven patients who underwent craniotomies in a stereotactic neurosurgical clinical trial. Each patient had four external markers attached to transcutaneous posts screwed into the outer table of the skull. The MR images are corrected for static field inhomogeneity by using an image rectification technique and corrected for scale distortion (gradient magnitude uncertainty) by using an attached stereotactic frame as an object of known shape and size. We define target registration error (TRE) as the distance between corresponding marker positions after registration and transformation. The accuracy of the fiducial marker method is determined by using each combination of three markers to estimate the transformation and the remaining marker to calculate registration error. Surface-based registration is accomplished by fitting MR contours corresponding to the CSF-dura interface to CT contours derived from the inner surface of the skull. The mean point-based TRE using three noncollinear fiducials improved 34%-from 1.15 to 0.76 mm-after correcting for both static field inhomogeneity and scale distortion. The mean surface-based TRE improved 46%-from 2.20 to 1.19 mm. Correction of geometrical distortion in MR images can significantly improve the accuracy of point-based and surface-based registration of CT and MR head images. Distortion correction can be important in clinical situations such as stereotactic and functional neurosurgery where 1 to 2 mm accuracy is required.

Surface-based registration of CT images to physical space for image-guided surgery of the spine: a sensitivity study

This paper presents a method designed to register preoperative computed tomography (CT) images to vertebral surface points acquired intraoperatively from ultrasound (US) images or via a tracked probe. It also presents a comparison of the registration accuracy achievable with surface points acquired from the entire posterior surface of the vertebra to the accuracy achievable with points acquired only from the spinous process and central laminar regions. Using a marker-based method as a reference, this work shows that submillimetric registration accuracy can be obtained even when a small portion of the posterior vertebral surface is used for registration. It also shows that when selected surface patches are used, CT slice thickness is not a critical parameter in the registration process. Furthermore, the paper includes qualitative results of registering vertebral surface points in US images to multiple CT slices. The method has been tested with US points and physical points on a plastic spine phantom and with simulated data on a patient CT scan.

The role of registration in accurate surgical guidance

Abstract Registration is presented as the central issue of surgical guidance. The focus is on the accuracy of approaches employed today, all of which use pre-operative images to guide surgery on rigid anatomy. The three most well-established approaches to guidance, namely the stereotactic frame, point fiducials, and surface matching, are examined in detail, together with two new approaches based on microstereotactic frames. It is shown that each method relies on the registration of points in the image to corresponding points in the operating room, and therefore that the error patterns associated with point registration are similar for all of them. Three types of registration error, namely fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE), are highlighted, as well as two additional guidance errors, namely target localization error and total targeting error, the latter of which is the overall error of the guidance system. Statistical relationships between TRE and FLE, between FRE and FLE, and between TRE, TLE, and TTE are given. Finally some myths concerning fiducial registration are highlighted.

Correcting scaling errors in tomographic images using a nine degree of freedom registration algorithm.

PURPOSE Clinical imaging systems, especially MR scanners, frequently have errors of a few percent in their voxel dimensions. We evaluate a nine degree of freedom registration algorithm that maximizes mutual information for determining scaling errors. We evaluate it by registering MR and CT images for each of five patients (patient scaling) and by registering MR images of a phantom to a computer model of the phantom (phantom scaling). METHOD Each scaling method was validated using bone-implanted markers localized in the patient images and also intraoperatively. The root mean square residual in the alignment of the fiducial markers [fiducial registration error (FRE)] was determined without scale correction, with patient scaling, and with phantom scaling. RESULTS Each scaling method significantly reduced the average FRE (p < 0.05) for MR to CT registration and for MR to physical space registration, indicating that voxel scaling errors were reduced. The greater reduction in scaling errors was achieved using the phantom scaling method. CONCLUSION We have demonstrated that a nine degree of freedom registration algorithm that maximizes mutual information can significantly reduce scaling errors in MR.

Minimally invasive, image-guided, facial-recess approach to the middle ear: demonstration of the concept of percutaneous cochlear access in vitro.

Hypothesis: Image-guided surgery will permit accurate access to the middle ear via the facial recess using a single drill hole from the lateral aspect of the mastoid cortex. Background: The widespread use of image-guided methods in otologic surgery has been limited by the need for a system that achieves the necessary level of accuracy with an easy-to-use, noninvasive fiducial marker system. We have developed and recently reported such a system (accuracy within the temporal bone = 0.76 ± 0.23 mm; n = 234 measurements). With this system, image-guided otologic surgery is feasible. Methods: Skulls (n = 2) were fitted with a dental bite-block affixed fiducial frame and scanned by computed tomography using standard temporal-bone algorithms. The frame was removed and replaced with an infrared emitter used to track the skull during dissection. Tracking was accomplished using an infrared tracker and commercially available software. Using this system in conjunction with a tracked otologic drill, the middle ear was approached via the facial recess using a single drill hole from the lateral aspect of the mastoid cortex. The path of the drill was verified by subsequently performing a traditional temporal bone dissection, preserving the tunnel of bone through which the drill pass had been made. Results: An accurate approach to the middle ear via the facial recess was achieved without violating the canal of the facial nerve, the horizontal semicircular canal, or the external auditory canal. Conclusions: Image-guided otologic surgery provides access to the cochlea via the facial recess in a minimally invasive, percutaneous fashion. While the present study was confined to in vitro demonstration, these exciting results warrant in vivo testing, which may lead to clinically applicable access.

General Approach to First-Order Error Prediction in Rigid Point Registration

A general approach to the first-order analysis of error in rigid point registration is presented that accommodates fiducial localization error (FLE) that may be inhomogeneous (varying from point to point) and anisotropic (varying with direction) and also accommodates arbitrary weighting that may also be inhomogeneous and anisotropic. Covariances are derived for target registration error (TRE) and for weighted fiducial registration error (FRE) in terms of covariances of FLE, culminating in a simple implementation that encompasses all combinations of weightings and anisotropy. Furthermore, it is shown that for ideal weighting, in which the weighting matrix for each fiducial equals the inverse of the square root of the cross covariance of its two-space FLE, fluctuations of FRE and TRE are mutually independent. These results are validated by comparison with previously published expressions and by simulation. Furthermore, simulations for randomly generated fiducial positions and FLEs are presented that show that correlation is negligible in the exact case for both ideal and uniform weighting (i.e., no weighting), the latter of which is employed in commercial surgical guidance systems. From these results we conclude that for these weighting schemes, while valid expressions exist relating the covariance of FRE to the covariance of TRE, there are no measures of the goodness of fit of the fiducials for a given registration that give to first order any information about the fluctuation of TRE from its expected value and none that give useful information in the exact case. Therefore, as estimators of registration accuracy, such measures should be approached with extreme caution both by the purveyors of guidance systems and by the practitioners who use them.