The CyberKnife Robotic Radiosurgery System in 2010.

This review provides a complete technical description of the CyberKnife VSI System, the latest addition to the CyberKnife product family, which was released in September 2009. This review updates the previous technical reviews of the original system version published in the late 1990s. Technical developments over the last decade have impacted virtually every aspect of the CyberKnife System. These developments have increased the geometric accuracy of the system and have enhanced the dosimetric accuracy and quality of treatment, with advanced inverse treatment planning algorithms, rapid Monte Carlo dose calculation, and post-processing tools that allow trade-offs between treatment efficiency and dosimetric quality to be explored. This review provides a system overview with detailed descriptions of key subsystems. A detailed review of studies of geometric accuracy is also included, reporting a wide range of experiments involving phantom tests and patient data. Finally, the relationship between technical developments and the greatly increased range of clinical applications they have allowed is reviewed briefly.

The design, physical properties and clinical utility of an iris collimator for robotic radiosurgery.

Robotic radiosurgery using more than one circular collimator can improve treatment plan quality and reduce total monitor units (MU). The rationale for an iris collimator that allows the field size to be varied during treatment delivery is to enable the benefits of multiple-field-size treatments to be realized with no increase in treatment time due to collimator exchange or multiple traversals of the robotic manipulator by allowing each beam to be delivered with any desired field size during a single traversal. This paper describes the Iris variable aperture collimator (Accuray Incorporated, Sunnyvale, CA, USA), which incorporates 12 tungsten-copper alloy segments in two banks of six. The banks are rotated by 30 degrees with respect to each other, which limits the radiation leakage between the collimator segments and produces a 12-sided polygonal treatment beam. The beam is approximately circular, with a root-mean-square (rms) deviation in the 50% dose radius of <0.8% (corresponding to <0.25 mm at the 60 mm field size) and an rms variation in the 20-80% penumbra width of about 0.1 mm at the 5 mm field size increasing to about 0.5 mm at 60 mm. The maximum measured collimator leakage dose rate was 0.07%. A commissioning method is described by which the average dose profile can be obtained from four profile measurements at each depth based on the periodicity of the isodose line variations with azimuthal angle. The penumbra of averaged profiles increased with field size and was typically 0.2-0.6 mm larger than that of an equivalent fixed circular collimator. The aperture reproducibility is < or =0.1 mm at the lower bank, diverging to < or =0.2 mm at a nominal treatment distance of 800 mm from the beam focus. Output factors (OFs) and tissue-phantom-ratio data are identical to those used for fixed collimators, except the OFs for the two smallest field sizes (5 and 7.5 mm) are considerably lower for the Iris Collimator. If average collimator profiles are used, the assumption of circular symmetry results in dose calculation errors that are <1 mm or <1% for single beams across the full range of field sizes; errors for multiple non-coplanar beam treatment plans are expected to be smaller. Treatment plans were generated for 19 cases using the Iris Collimator (12 field sizes) and also using one and three fixed collimators. The results of the treatment planning study demonstrate that the use of multiple field sizes achieves multiple plan quality improvements, including reduction of total MU, increase of target volume coverage and improvements in conformality and homogeneity compared with using a single field size for a large proportion of the cases studied. The Iris Collimator offers the potential to greatly increase the clinical application of multiple field sizes for robotic radiosurgery.

Evaluation of a new electromagnetic tracking system using a standardized assessment protocol.

This note uses a published protocol to evaluate a newly released 6 degrees of freedom electromagnetic tracking system (Aurora, Northern Digital Inc.). A practice for performance monitoring over time is also proposed. The protocol uses a machined base plate to measure relative error in position and orientation as well as the influence of metallic objects in the operating volume. Positional jitter (E(RMS)) was found to be 0.17 mm +/- 0.19 mm. A relative positional error of 0.25 mm +/- 0.22 mm at 50 mm offsets and 0.97 mm +/- 1.01 mm at 300 mm offsets was found. The mean of the relative rotation error was found to be 0.20 degrees +/- 0.14 degrees with respect to the axial and 0.91 degrees +/- 0.68 degrees for the longitudinal rotation. The most significant distortion caused by metallic objects is caused by 400-series stainless steel. A 9.4 mm maximum error occurred when the rod was closest to the emitter, 10 mm away. The improvement compared to older generations of the Aurora with respect to accuracy is substantial.

Shape-based averaging for combination of multiple segmentations.

Combination of multiple segmentations has recently been introduced as an effective method to obtain segmentations that are more accurate than any of the individual input segmentations. This paper introduces a new way to combine multiple segmentations using a novel shape-based averaging method. Individual segmentations are combined based on the signed Euclidean distance maps of the labels in each input segmentation. Compared to label voting, the new combination method produces smoother, more regular output segmentations and avoids fragmentation of contiguous structures. Using publicly available segmented human brain MR images (IBSR database), we perform a quantitative comparison between shape-based averaging and label voting by combining random segmentations with controlled error magnitudes and known ground truth. Shape-based averaging generated combined segmentations that were closer to the ground truth than combinations from label voting for all numbers of input segmentations (up to ten). The relative advantage of shape-based averaging over voting was larger for fewer input segmentations, and larger for greater deviations of the input segmentations from the ground truth. We conclude that shape-based averaging improves the accuracy of combined segmentations, in particular when only a few input segmentations are available and when the quality of the input segmentations is low.

Information fusion in biomedical image analysis: combination of data vs. combination of interpretations.

Information fusion has, in the form of multiple classifier systems, long been a successful tool in pattern recognition applications. It is also becoming increasingly popular in biomedical image analysis, for example in computer-aided diagnosis and in image segmentation. In this paper, we extend the principles of multiple classifier systems by considering information fusion of classifier inputs rather than on their outputs, as is usually done. We introduce the distinction between combination of data (i.e., classifier inputs) vs. combination of interpretations (i.e., classifier outputs). We illustrate the two levels of information fusion using four different biomedical image analysis applications that can be implemented using fusion of either data or interpretations: atlas-based image segmentation, "average image" tissue classification, multi-spectral classification, and deformation-based group morphometry.

Measurement and analysis of brain deformation during neurosurgery.

Recent studies have shown that the surface of the brain is deformed by up to 20 mm after the skull is opened during neurosurgery, which could lead to substantial error in commercial image-guided surgery systems. We quantitatively analyze the intraoperative brain deformation of 24 subjects to investigate whether simple rules can describe or predict the deformation. Interventional magnetic resonance images acquired at the start and end of the procedure are registered nonrigidly to obtain deformation values throughout the brain. Deformation patterns are investigated quantitatively with respect to the location and magnitude of deformation, and to the distribution and principal direction of the displacements. We also measure the volume change of the lateral ventricles by manual segmentation. Our study indicates that brain shift occurs predominantly in the hemisphere ipsi-lateral to the craniotomy, and that there is more brain deformation during resection procedures than during biopsy or functional procedures. However, the brain deformation patterns are extremely complex in this group of subjects. This paper quantitatively demonstrates that brain deformation occurs not only at the surface, but also in deeper brain structure, and that the principal direction of displacement does not always correspond with the direction of gravity. Therefore, simple computational algorithms that utilize limited intraoperative information (e.g., brain surface shift) will not always accurately predict brain deformation at the lesion.

Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images.

This paper describes a method for tracking the camera motion of a flexible endoscope, in particular a bronchoscope, using epipolar geometry analysis and intensity-based image registration. The method proposed here does not use a positional sensor attached to the endoscope. Instead, it tracks camera motion using real endoscopic (RE) video images obtained at the time of the procedure and X-ray CT images acquired before the endoscopic examination. A virtual endoscope system (VES) is used for generating virtual endoscopic (VE) images. The basic idea of this tracking method is to find the viewpoint and view direction of the VES that maximizes a similarity measure between the VE and RE images. To assist the parameter search process, camera motion is also computed directly from epipolar geometry analysis of the RE video images. The complete method consists of two steps: (a) rough estimation using epipolar geometry analysis and (b) precise estimation using intensity-based image registration. In the rough registration process, the method computes camera motion from optical flow patterns between two consecutive RE video image frames using epipolar geometry analysis. In the image registration stage, we search for the VES viewing parameters that generate the VE image that is most similar to the current RE image. The correlation coefficient and the mean square intensity difference are used for measuring image similarity. The result obtained in the rough estimation process is used for restricting the parameter search area. We applied the method to bronchoscopic video image data from three patients who had chest CT images. The method successfully tracked camera motion for about 600 consecutive frames in the best case. Visual inspection suggests that the tracking is sufficiently accurate for clinical use. Tracking results obtained by performing the method without the epipolar geometry analysis step were substantially worse. Although the method required about 20 s to process one frame, the results demonstrate the potential of image-based tracking for use in an endoscope navigation system.

Fiducial point placement and the accuracy of point-based, rigid body registration.

OBJECTIVE: To demonstrate that the shape of the configuration of fiducial points is an important factor governing target registration error (TRE) in point-based, rigid registration. METHODS: We consider two clinical situations: cranial neurosurgery and pedicle screw placement. For cranial neurosurgery, we apply theoretical results concerning TRE prediction, which we have previously derived and validated, to three hypothetical fiducial marker configurations. We illustrate the profile of expected TRE for each configuration. For pedicle screw placement, we apply the same theory to a common anatomic landmark configuration (tips of spinous and transverse processes) used for pedicle screw placement, and we estimate the error rate expected in placement of the screw. RESULTS: In the cranial neurosurgery example, we demonstrate that relatively small values of TRE may be achieved by using widely spread fiducial markers and/or placing the centroid of the markers near the target. We also demonstrate that near-collinear marker configurations far from the target may result in large TRE values. In the pedicle screw placement example, we demonstrate that the screw must be approximately 4 mm narrower than the pedicle in which it is implanted to minimize the chance of pedicle violation during placement. CONCLUSION: The placement of fiducial points is an important factor in minimizing the error rate for point-based, rigid registration. By using as many points as possible, avoiding near-collinear configurations, and ensuring that the centroid of the fiducial points is as near as possible to the target, TREs can be minimized.

Sources of error in comparing functional magnetic resonance imaging and invasive electrophysiological recordings.

OBJECT: Several authors have recently reported studies in which they aim to validate functional magnetic resonance (fMR) imaging against the accepted gold standard of invasive electrophysiological monitoring. The authors have conducted a similar study, and in this paper they identify and quantify two characteristics of these data that can make such a comparison problematic. METHODS: Eight patients in whom surgery for epilepsy was performed and five healthy volunteers underwent fMR imaging to localize the part of the sensorimotor cortex responsible for hand movement. In the patient group subdural electrode mats were subsequently implanted to identify eloquent regions of the brain and the epileptogenic zone. The fMR imaging data were processed to correct for motion during the study and then registered with a postimplantation computerized tomography (CT) scan on which the electrodes were visible. The motion during imaging in the two groups studied, and the deformation of the brain between the preoperative images and postoperative scans were measured. The patients who underwent epilepsy surgery moved significantly more during fMR imaging experiments than healthy volunteers performing the same motor task. This motion had a particularly increased out-of-plane component and was significantly more correlated with the stimulus than in the volunteers. This motion was especially increased when the patients were performing a task on the side affected by the lesion. The additional motion is hard to correct and substantially degrades the quality of the resulting fMR images, making it a much less reliable technique for use in these patients than in others. Also, the authors found that after electrode implantation, the brain surface can shift more than 10 mm relative to the skull compared with its preoperative location, substantially degrading the accuracy of the comparison of electrophysiological measurements made in the deformed brain and fMR studies obtained preoperatively. CONCLUSIONS: These two findings indicate that studies of this sort are currently of limited use for validating fMR imaging and should be interpreted with care. Additional image analysis research is necessary to solve the problems caused by patients' motion and brain deformation.

Design and evaluation of a system for microscope-assisted guided interventions (MAGI).

The problem of providing surgical navigation using image overlays on the operative scene can be split into four main tasks--calibration of the optical system; registration of preoperative images to the patient; system and patient tracking, and display using a suitable visualization scheme. To achieve a convincing result in the magnified microscope view a very high alignment accuracy is required. We have simulated an entire image overlay system to establish the most significant sources of error and improved each of the stages involved. The microscope calibration process has been automated. We have introduced bone-implanted markers for registration and incorporated a locking acrylic dental stent (LADS) for patient tracking. The LADS can also provide a less-invasive registration device with mean target error of 0.7 mm in volunteer experiments. These improvements have significantly increased the alignment accuracy of our overlays. Phantom accuracy is 0.3-0.5 mm and clinical overlay errors were 0.5-1.0 mm on the bone fiducials and 0.5-4 mm on target structures. We have improved the graphical representation of the stereo overlays. The resulting system provides three-dimensional surgical navigation for microscope-assisted guided interventions (MAGI).

Stereo augmented reality in the surgical microscope.

We present an augmented reality system that allows surgeons to view features from preoperative radiological images accurately overlaid in stereo in the optical path of a surgical microscope. The purpose of the system is to show the surgeon structures beneath the viewed surface in the correct 3-D position. The technical challenges are registration, tracking, calibration and visualisation. For patient registration, or alignment to preoperative images, we use bone-implanted markers and a dental splint is used for patient tracking. Both microscope and patient are tracked by an optical localiser. Calibration uses an accurately manufactured object with high contrast circular markers which are identified automatically. All ten camera parameters are modelled as a bivariate polynomial function of zoom and focus. The overall system has a theoretical overlay accuracy of better than 1 mm. Implementations of the system have been tested on seven patients. Recent measurements in the operating room conformed to our accuracy predictions. For visualisation the system has been implemented on a graphics workstation to enable high frame rates with a variety of rendering schemes. Several issues of 3-D depth perception remain unsolved, but early results suggest that perception of structures in the correct 3-D position beneath the viewed surface is possible.

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

The primary objective of this study is to perform a blinded evaluation of two groups of retrospective image registration techniques, using as a gold standard a prospective marker-based registration method, and to compare the performance of one group with the other. These techniques have already been evaluated individually [27]. In this paper, however, we find that by grouping the techniques as volume based or surface based, we can make some interesting conclusions which were not visible in the earlier study. 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 computed tomography (CT), magnetic resonance (MR), and positron emission tomography (PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/or from PET to MR. These investigators communicated their transformations, again via the Internet, to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOI's). Our results indicate that 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-MR registration tasks, and slightly more accurate results for the PET-to-MR 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.

A system for microscope-assisted guided interventions.

We present a system for surgical navigation using stereo overlays in the operating microscope aligned to the operative scene. This augmented reality system provides 3D information about nearby structures and offers a significant advancement over pointer-based guidance, which provides only the location of one point and requires the surgeon to look away from the operative scene. With a previous version of this system, we demonstrated feasibility, but it became clear that to achieve convincing guidance through the magnified microscope view, a very high alignment accuracy was required. We have made progress with several aspects of the system, including automated calibration, error simulation, bone-implanted fiducials and a dental attachment for tracking. We have performed experiments to establish the visual display parameters required to perceive overlaid structures beneath the operative surface. Easy perception of real and virtual structures with the correct transparency has been demonstrated in a laboratory and through the microscope. The result is a system with a predicted accuracy of 0.9 mm and phantom errors of 0.5 mm. In clinical practice errors are 0.5-1.5 mm, rising to 2-4 mm when brain deformation occurs.

Visual assessment of the accuracy of retrospective registration of MR and CT images of the brain.

In a previous study we demonstrated that automatic retrospective registration algorithms can frequently register magnetic resonance (MR) and computed tomography (CT) images of the brain with an accuracy of better than 2 mm, but in that same study we found that such algorithms sometimes fail, leading to errors of 6 mm or more. Before these algorithms can be used routinely in the clinic, methods must be provided for distinguishing between registration solutions that are clinically satisfactory and those that are not. One approach is to rely on a human observer to inspect the registration results and reject images that have been registered with insufficient accuracy. In this paper, we present a methodology for evaluating the efficacy of the visual assessment of registration accuracy. Since the clinical requirements for level of registration accuracy are likely to be application dependent, we have evaluated the accuracy of the observer's estimate relative to six thresholds: 1-6 mm. The performance of the observers was evaluated relative to the registration solution obtained using external fiducial markers that are screwed into the patient's skull and that are visible in both MR and CT images. This fiducial marker system provides the gold standard for our study. Its accuracy is shown to be approximately 0.5 mm. Two experienced, blinded observers viewed five pairs of clinical MR and CT brain images, each of which had each been misregistered with respect to the gold standard solution. Fourteen misregistrations were assessed for each image pair with misregistration errors distributed between 0 and 10 mm with approximate uniformity. For each misregistered image pair each observer estimated the registration error (in millimeters) at each of five locations distributed around the head using each of three assessment methods. These estimated errors were compared with the errors as measured by the gold standard to determine agreement relative to each of the six thresholds, where agreement means that the two errors lie on the same side of the threshold. The effect of error in the gold standard itself is taken into account in the analysis of the assessment methods. The results were analyzed by means of the Kappa statistic, the agreement rate, and the area of receiver-operating-characteristic (ROC) curves. No assessment performed well at 1 mm, but all methods performed well at 2 mm and higher. For these five thresholds, two methods agreed with the standard at least 80% of the time and exhibited mean ROC areas greater than 0.84. One of these same methods exhibited Kappa statistics that indicated good agreement relative to chance (Kappa > 0.6) between the pooled observers and the standard for these same five thresholds. Further analysis demonstrates that the results depend strongly on the choice of the distribution of misregistration errors presented to the observers.

Measurement of intraoperative brain surface deformation under a craniotomy.

OBJECTIVE: Several causes of spatial inaccuracies in image-guided surgery have been carefully studied and documented for several systems. These include error in identifying the external features used for registration, geometrical distortion in the preoperative images, and error in tracking the surgical instruments. Another potentially important source of error is brain deformation between the time of imaging and the time of surgery or during surgery. In this study, we measured the deformation of the dura and brain surfaces between the time of imaging and the start of surgical resection for 21 patients. METHODS: All patients underwent intraoperative functional mapping, allowing us to measure brain surface motion at two times that were separated by nearly an hour after opening the dura but before performing resection. The positions of the dura and brain surfaces were recorded and transformed to the coordinate space of a preoperative magnetic resonance image, using the Acustar surgical navigation system (manufactured by Johnson & Johnson Professional, Inc., Randolph, MA) (the Acustar trademark and associated intellectual property rights are now owned by Picker International, Highland Heights, OH). This system performs image registration with bone-implanted markers and tracks a surgical probe by optical triangulation. RESULTS: The mean displacements of the dura and the first and second brain surfaces were 1.2, 4.4, and 5.6 mm, respectively, with corresponding mean volume reductions under the craniotomy of 6, 22, and 29 cc. The maximum displacement was greater than 10 mm in approximately one-third of the patients for the first brain surface measurement and one-half of the patients for the second. In all cases, the direction of brain shift corresponded to a "sinking" of the brain intraoperatively, compared with its preoperative position. Analysis of the measurement error revealed that its magnitude was approximately 1 to 2 mm. We observed two different patterns of the brain surface deformation field, depending on the inclination of the craniotomy with respect to gravity. Separate measurements of brain deformation within the closed cranium caused by changes in patient head orientation with respect to gravity suggested that less than 1 mm of the brain shift recorded intraoperatively could have resulted from the change in patient orientation between the time of imaging and the time of surgery. CONCLUSION: These results suggest that intraoperative brain deformation is an important source of error that needs to be considered when using surgical navigation systems.

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.

Predicting error in rigid-body point-based registration.

Guidance systems designed for neurosurgery, hip surgery, and 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 error (FLE) 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. This paper presents two new expressions for estimating registration accuracy of such systems and points out a danger in using a traditional measure of registration accuracy. The new expressions represent fundamental theoretical results with regard to the relationship between localization error and registration error in rigid-body, point-based registration. Rigid-body, point-based registration is achieved by finding the rigid transformation that minimizes "fiducial registration error" (FRE), which is the root mean square distance between homologous fiducials after registration. Closed form solutions have been known since 1966. The expected value (FRE2) depends on the number N of fiducials and expected squared value of FLE, (FLE-2, but in 1979 it was shown that (FRE2) is approximately independent of the fiducial configuration C. The importance of this surprising result seems not yet to have been appreciated by the registration community: Poor registrations caused by poor fiducial configurations may appear to be good due to a small FRE value. A more critical and direct measure of registration error is the "target registration error" (TRE), which is the distance between homologous points other than the centroids of fiducials. Efforts to characterize its behavior have been made since 1989. Published numerical simulations have shown that (TRE2) is roughly proportional to (FLE2)/N and, unlike (FRE2), does depend in some way on C. Thus, FRE, which is often used as feedback to the surgeon using a point-based guidance system, is in fact an unreliable indicator of registration-accuracy. In this work we derive approximate expressions for (TRE2), and for the expected squared alignment error of an individual fiducial. We validate both approximations through numerical simulations. The former expression can be used to provide reliable feedback to the surgeon during surgery and to guide the placement of markers before surgery, or at least to warn the surgeon of potentially dangerous fiducial placements; the latter expression leads to a surprising conclusion: Expected registration accuracy (TRE) is worst near the fiducials that are most closely aligned! This revelation should be of particular concern to surgeons who may at present be relying on fiducial alignment as an indicator of the accuracy of their point-based guidance systems.

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.

Registration of head CT images to physical space using a weighted combination of points and surfaces.

Most previously reported registration techniques that align three-dimensional image volumes by matching geometrical features such as points or surfaces use a single type of feature. We recently reported a hybrid registration technique that uses a weighted combination of multiple geometrical feature shapes. In this study we use the weighted geometrical feature (WGF) algorithm to register computed tomography (CT) images of the head to physical space using the skin surface only, the bone surface only, and various weighted combinations of these surfaces and one fiducial point (centroid of a bone-implanted marker). We use data acquired from 12 patients that underwent temporal lobe craniotomies for the resection of cerebral lesions. We evaluate and compare the accuracy of the registrations obtained using these various approaches by using as a reference gold standard the registration obtained using three bone-implanted markers. The results demonstrate that a combination of geometrical features can improve the accuracy of CT-to-physical space registration. Point-based registration requires a minimum of three noncolinear points. The position of a bone-implanted marker can be determined much more accurately than that of a skin-affixed marker or an anatomic landmark. A major disadvantage of using bone-implanted markers is that an invasive procedure is required to implant each marker. By combining surface information, the WGF algorithm allows registration to be performed using only one or two such markers. One important finding is that the use of a single very accurate point (a bone-implanted marker) allows very accurate surface-based registration to be achieved using very few surface points. Finally, the WGF algorithm, which not only allows the combination of multiple types of geometrical information but also handles point-based and surface-based registration as degenerate cases, could form the foundation of a "flexible" surgical navigation system that allows the surgeon to use what he considers the method most appropriate for an individual clinical situation.

Investigation of intraoperative brain deformation using a 1.5-T interventional MR system: preliminary results.

All image-guided neurosurgical systems that we are aware of assume that the head and its contents behave as a rigid body. It is important to measure intraoperative brain deformation (brain shift) to provide some indication of the application accuracy of image-guided surgical systems, and also to provide data to develop and validate nonrigid registration algorithms to correct for such deformation. We are collecting data from patients undergoing neurosurgery in a high-field (1.5 T) interventional magnetic resonance (MR) scanner. High-contrast and high-resolution gradient-echo MR image volumes are collected immediately prior to surgery, during surgery, and at the end of surgery, with the patient intubated and lying on the operating table in the operative position. In this paper we report initial results from six patients: one freehand biopsy, one stereotactic functional procedure, and four resections. We investigate intraoperative brain deformation by examining threshold boundary overlays and difference images and by measuring ventricular volume. We also present preliminary results obtained using a nonrigid registration algorithm to quantify deformation. We found that some cases had much greater deformation than others, and also that, regardless of the procedure, there was very little deformation of the midline, the tentorium, the hemisphere contralateral to the procedure, and ipsilateral structures except those that are within 1 cm of the lesion or are gravitationally above the surgical site.