Registration of head volume images using implantable fiducial markers

Alignment of cone beam computed tomography data using intra-oral fiducial markers

This article illustrates a new method to align and merge two partially overlapping volumes each of them generated by cone beam computed tomography (CBCT). The aggregate volume covers a larger area of investigation and is determined by localizing one fixed LEGO brick in both of the primal volumes. Based on the LEGO brick an approximate registration of the volumes is determined. Afterwards we improve the transformation by minimizing the difference in overlapping space. In this paper we present a method which automates these two steps and provides an aligned volume.

Precision of navigated stereotactic probe implantation into the brainstem

OBJECT

The indications for stereotactic biopsies or implantation of probes for local chemotherapy in diffuse brainstem tumors have recently come under debate. The quality of performing these procedures significantly depends on the precision of the probes' placement in the brainstem. The authors evaluated the precision of brainstem probe positioning using a navigated frameless stereotactic system in an experimental setting.

METHODS

Using the VarioGuide stereotactic system, 33 probes were placed into a specially designed model filled with agarose. In a second experimental series, 8 anatomical specimens were implanted with a total of 32 catheters into the pontine brainstem using either a suboccipital or a precoronal entry point. Before intervention in both experimental settings, a thin-sliced CT scan for planning was obtained and fused to volumetric T1-weighted MR imaging data. After the probe positioning procedures, another CT scan and an MR image were obtained to compare the course of the catheters versus the planned trajectory. The deviation between the planned and the actual locations was measured to evaluate the precision of the navigated intervention.

RESULTS

Using the VarioGuide system, mean total target deviations of 2.8 +/- 1.2 mm on CT scanning and 3.1 +/- 1.2 mm on MR imaging were detected with a mean catheter length of 151 +/- 6.1 mm in the agarose model. The catheter placement in the anatomical specimens revealed mean total deviations of 1.95 +/- 0.6 mm on CT scanning and 1.8 +/- 0.7 mm on MR imaging for the suboccipital approach and a mean catheter length of 59.5 +/- 4.1 mm. For the precoronal approach, deviations of 2.2 +/- 1.2 mm on CT scanning and 2.1 +/- 1.1 mm on MR imaging were measured (mean catheter length 85.9 +/- 4.7 mm).

CONCLUSIONS

The system-based deviation of frameless stereotaxy using the VarioGuide system reveals good probe placement in deep-seated locations such as the brainstem. Therefore, the authors believe that the system can be accurately used to conduct biopsies and place probes in patients with brainstem lesions.

Target tracking errors for 5D and 6D spatial measurement systems

In recent years, magnetic tracking systems, whose fundamental unit of measurement is a 5D transformation (three translational and two rotational degrees-of-freedom), have become much more popular. Two 5D sensors can be combined to obtain a 6D transformation similar to the ones provided by the point-based registration in optical tracking. However, estimates of the tool tip uncertainty, which we have called the target tracking error (TTE) since no registration is explicitly performed, are not available in the same manner as their optical counterpart. If the systematic bias error can be corrected and estimates of the 5D or 6D fiducial localizer error (FLE) are provided in the form of zero mean normally distributed random variables in [Formula: see text] and [Formula: see text], respectively, then the TTE can be modeled. In this paper, the required expressions that model the TTE as a function of the systematic bias, FLE and target location are derived and then validated using Monte Carlo simulations. We also show that the first order approximation is sufficient beyond the range of errors typically observed during an image-guided surgery (IGS) procedure. Applications of the models are described for a minimally invasive intracardiac surgical guidance system and needle-based therapy systems. Together with the target registration error (TRE) statistical models for point-based registration, the models presented in this article provide the basic framework for estimating the total system measurement uncertainty for an IGS system. Future work includes developing TRE models for commonly used registration methods that do not already have them.

Estimation of optimal fiducial target registration error in the presence of heteroscedastic noise

We study the effect of point dependent (heteroscedastic) and identically distributed anisotropic fiducial localization noise on fiducial target registration error (TRE). We derive an analytic expression, based on the concept of mechanism spatial stiffness, for predicting TRE. The accuracy of the predicted TRE is compared to simulated values where the optimal registration transformation is computed using the heteroscedastic errors in variables algorithm. The predicted values are shown to be contained by the 95% confidence intervals of the root mean square TRE obtained from the simulations.

Error analysis for determination of accuracy of an ultrasound navigation system for head and neck surgery

OBJECTIVE

The use of conventional CT- or MRI-based navigation systems for head and neck surgery is unsatisfactory due to tissue shift. Moreover, changes occurring during surgical procedures cannot be visualized. To overcome these drawbacks, we developed a novel ultrasound-guided navigation system for head and neck surgery. A comprehensive error analysis was undertaken to determine the accuracy of this new system.

MATERIALS AND METHODS

The evaluation of the system accuracy was essentially based on the method of error definition for well-established fiducial marker registration methods (point-pair matching) as used in, for example, CT- or MRI-based navigation. This method was modified in accordance with the specific requirements of ultrasound-guided navigation. The Fiducial Localization Error (FLE), Fiducial Registration Error (FRE) and Target Registration Error (TRE) were determined.

RESULTS

In our navigation system, the real error (the TRE actually measured) did not exceed a volume of 1.58 mm(3) with a probability of 0.9. A mean value of 0.8 mm (standard deviation: 0.25 mm) was found for the FRE. The quality of the coordinate tracking system (Polaris localizer) could be defined with an FLE of 0.4 +/- 0.11 mm (mean +/- standard deviation). The quality of the coordinates of the crosshairs of the phantom was determined with a deviation of 0.5 mm (standard deviation: 0.07 mm).

CONCLUSION

The results demonstrate that our newly developed ultrasound-guided navigation system shows only very small system deviations and therefore provides very accurate data for practical applications.

Surface-based facial scan registration in neuronavigation procedures: a clinical study

OBJECT

Surface-based registration (SBR) with facial surface scans has been proposed as an alternative for the commonly used fiducial-based registration in image-guided neurosurgery. Recent studies comparing the accuracy of SBR and fiducial-based registration have been based on a few targets located on the head surface rather than inside the brain and have yielded contradictory conclusions. Moreover, no visual feedback is provided with either method to inform the surgeon about the estimated target registration error (TRE) at various target locations. The goals in the present study were: 1) to quantify the SBR error in a clinical setup, 2) to estimate the targeting error for many target locations inside the brain, and 3) to create a map of the estimated TRE values superimposed on a patient's head image.

METHODS

The authors randomly selected 12 patients (8 supine and 4 in a lateral position) who underwent neurosurgery with a commercial navigation system. Intraoperatively, scans of the patients' faces were acquired using a fast 3D surface scanner and aligned with their preoperative MR or CT head image. In the laboratory, the SBR accuracy was measured on the facial zone and estimated at various intracranial target locations. Contours related to different TREs were superimposed on the patient's head image and informed the surgeon about the expected anisotropic error distribution.

RESULTS

The mean surface registration error in the face zone was 0.9 +/- 0.35 mm. The mean estimated TREs for targets located 60, 105, and 150 mm from the facial surface were 2.0, 3.2, and 4.5 mm, respectively. There was no difference in the estimated TRE between the lateral and supine positions. The entire registration procedure, including positioning of the scanner, surface data acquisition, and the registration computation usually required < 5 minutes.

CONCLUSIONS

Surface-based registration accuracy is better in the face and frontal zones, and error increases as the target location lies further from the face. Visualization of the anisotropic TRE distribution may help the surgeon to make clinical decisions. The observed and estimated accuracies and the intraoperative registration time show that SBR using the fast surface scanner is practical and feasible in a clinical setup.

Submillimetric target-registration error using a novel, non-invasive fiducial system for image-guided otologic surgery

OBJECTIVE

Otologic surgery is undertaken to treat ailments of the ear, including persistent infections, hearing loss, vertigo, and cancer. Typically performed on otherwise-healthy patients in outpatient facilities, the application of image-guided surgery (IGS) has been limited because accurate (<1 mm), non-invasive fiducial systems for otologic surgery have not been available. We now present such a fiducial system.

METHODS

A dental bite-block was fitted with a custom-designed rigid frame with 7 fiducial markers surrounding each external ear. The bones containing the ear (i.e., the temporal bones) of 3 cadaveric skulls were removed and replaced with discs containing 13 surgical targets arranged in a cross-hair pattern about the centroid of each ear. The surgical targets (26/skull) and fiducial markers (14/skull) were identified both within CT scans using a published algorithm and in physical space using an infrared optical tracking system. Fiducial registration error (FRE), fiducial localization error (FLE), and target registration error (TRE) were calculated.

RESULTS

For all trials, root mean square FRE = 0.66, FLE = 0.72, and TRE = 0.77 mm. The mean TRE for n = 234 independent targets was 0.73 with a standard deviation of 0.25 mm.

CONCLUSIONS

Using a novel, non-invasive fiducial system (the EarMark), submillimetric accuracy was repeatably achieved. This system will facilitate image-guided otologic surgery.

Bootstrap resampling for image registration uncertainty estimation without ground truth

We address the problem of estimating the uncertainty of pixel based image registration algorithms, given just the two images to be registered, for cases when no ground truth data is available. Our novel method uses bootstrap resampling. It is very general, applicable to almost any registration method based on minimizing a pixel-based similarity criterion; we demonstrate it using the SSD, SAD, correlation, and mutual information criteria. We show experimentally that the bootstrap method provides better estimates of the registration accuracy than the state-of-the-art CramEr-Rao bound method. Additionally, we evaluate also a fast registration accuracy estimation (FRAE) method which is based on quadratic sensitivity analysis ideas and has a negligible computational overhead. FRAE mostly works better than the CramEr-Rao bound method but is outperformed by the bootstrap method.

RepliExplore: coupling physical and virtual anatomy models

PURPOSE

We present a system which co-registers physical anatomy models with virtual three-dimensional (3D) representations. Interactions performed on the physical model by means of a 3D pointing device are directly reflected on its virtual counterpart. Complex anatomical information integrated into the virtual model thus becomes accessible through the physical interface in a simple and intuitive manner.

METHODS

Using an optical tracking system, we implemented and tested a reference application that includes several tools for the exploration and quantification of anatomical models. We theoretically evaluated the accuracy of the landmark-based registration for different landmark configurations.

RESULTS

Physicians and computer scientists found the system simple to learn and intuitive to use. By optimizing landmark configurations, the accuracy could be significantly increased, particularly for scenarios in which only selected regions required higher accuracy.

CONCLUSIONS

Physical anatomical models can benefit from the combination with a virtual counterpart in several ways. Applications include anatomical education and the study of patient-individual organ models. Optimizing the registration landmark configuration for specific applications can lower the accuracy requirements for the tracking system.

[Neuronavigation in transnasal endoscopic paranasal sinuses and cranial base surgery: comparison of the optical and electromagnetic systems]

Transnasal endoscopic operative methods became increasingly popular in paranasal sinuses and cranial base surgery. Various types of localization systems are recently used to navigate through and between tangled anatomical structures in this region. The aim of this study was to compare (as basing on our own clinical experience), the advantages and limitations of the optical and electromagnetic neuronavigation systems.

MATERIAL AND METHOD

Optical neuronavigation system (Stealth Station Treon plus, Medtronic, U.S.A.) and electromagnetic neuronavigation systems (DigiPointeur, Collin, France and Fusion ENT, Medtronic, USA) were used during endoscopic operations of paranasal sinuses, anterior skull base, orbits, parasellar region and clivus. The subject of comparison were precision of both system types and additional time necessary for setting up the system. Also assessed were convenience of navigation and easiness of manipulation with neuronavigated instruments during surgical procedures performed using classical endoscopic technique, bimanual technique and four hand technique.

RESULTS

The accuracy was high and comparable for both system types and did not deteriorate during the procedure. The time needed to set up of the optical system was somewhat longer. Surgeon's comfort during operative procedures was assessed as slightly higher for the electromagnetic systems, especially if four hand or bimanual techniques were used and if constant neuronavigation was indispensible. The optical system allows for navigation of a variety of surgical tools and this was considered a great advantage over the electromagnetic systems in this particular application.

CONCLUSIONS

The additional time spent in the operative theatre for getting a system ready is well paid off by better orientation of a surgeon in the operative field consequently increasing safety and higher accuracy of surgical procedure. What system should a surgeon use depends to a great extent on the type of planed procedure and preferred surgical technique.

An optimised radial basis function algorithm for fast non-rigid registration of medical images

The registration of multi-modal medical image data is important in the fields of image guided surgery and computer aided medical diagnosis. Registration accuracy is of utmost importance in both fields, however in the former, the speed of registration is equally important. In this paper, we present a point-based 'fast' non-rigid registration algorithm which exhibits significant speedups as compared to the non-optimised equivalent algorithm. Additionally, we make use of the parallel nature of the graphics processing unit (GPU) of the video adapter card of a standard PC to gain further speedups. The algorithm achieved sub-second performance when tested on the registration of MR with CT image data of size 256(3).

Real-time estimation of FLE statistics for 3-D tracking with point-based registration

Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 microm. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option of changing their strategy in order to improve the overall system accuracy and, in turn, the quality of procedure.

Role of image-guidance systems during NOTES

Natural orifice translumenal endoscopic surgery (NOTES) is a developing field with the potential to revolutionize our approach to abdominal surgery. Performing operations via a flexible endoscope introduced through a natural orifice presents several challenges to physicians. Orientation and interpretation of the endoscopic video image can be difficult. The surgeon must also learn to operate with the camera and instruments "in line." Advances in technology are currently addressing the challenges of NOTES. Image-guided navigation could potentially provide invaluable assistance during NOTES. Real-time information on spatial positioning and orientation as well as assistance with the identification of anatomy and localization of pathology are some of the possibilities. Image-guided surgery has become commonplace in disciplines such as neurosurgery where the anatomy is relatively rigid. To become widespread in intra-abdominal procedures and NOTES, advances that will allow systems to adapt to moving and deforming anatomy are needed. This article reviews the basics of image-guided surgery, the various image-guided systems, and their potential application to NOTES.

Distribution of target registration error for anisotropic and inhomogeneous fiducial localization error

In point-based rigid-body registration, target registration error (TRE) is an important measure of the accuracy of the performed registration. The registration's accuracy depends on the fiducial localization error (FLE) which, in turn, is due to the measurement errors in the points (fiducials) used to perform the registration. FLE may have different characteristics and distributions at each point of the registering data sets, and along each orthogonal axis. Previously, the distribution of TRE was estimated based on the assumption that FLE has an independent, identical, and isotropic or anisotropic distribution for each point in the registering data sets. In this article, we present a general solution based on the Maximum Likelihood (ML) algorithm that estimates the distribution of TRE for the cases where FLE has an independent, identical or inhomogeneous, isotropic or anisotropic, distribution at each point in the registering data sets, and when an algorithm is available that is capable of calculating the optimum registration to first order. Mathematically, we show that the proposed algorithm simplifies to the one proposed by Fitzpatrick and West when FLE has an independent, identical, and isotropic distribution in the registering data sets. Furthermore, we use numerical simulations to show that the proposed algorithm accurately estimates the distribution of TRE when FLE has an independent, inhomogeneous, and anisotropic distribution in the registering data sets.

Initial investigation of an automatic registration algorithm for surgical navigation

The procedure required for registering a surgical navigation system prior to use in a surgical procedure is conventionally a time-consuming manual process that is prone to human errors and must be repeated as necessary through the course of a procedure. The conventional procedure becomes even more time consuming when intra-operative 3D imaging such as the C-arm cone-beam CT (CBCT) is introduced, as each updated volume set requires a new registration. To improve the speed and accuracy of registering image and world reference frames in image-guided surgery, a novel automatic registration algorithm was developed and investigated. The surgical navigation system consists of either Polaris (Northern Digital Inc., Waterloo, ON) or MicronTracker (Claron Technology Inc., Toronto, ON) tracking camera(s), custom software (Cogito running on a PC), and a prototype CBCT imaging system based on a mobile isocentric C-arm (Siemens, Erlangen, Germany). Experiments were conducted to test the accuracy of automatic registration methods for both the MicronTracker and Polaris tracking cameras. Results indicate the automated registration performs as well as the manual registration procedure using either the Claron or Polaris camera. The average root-mean-squared (rms) observed target registration error (TRE) for the manual procedure was 2.58 +/- 0.42 mm and 1.76 +/- 0.49 mm for the Polaris and MicronTracker, respectively. The mean observed TRE for the automatic algorithm was 2.11 +/- 0.13 and 2.03 +/- 0.3 mm for the Polaris and MicronTracker, respectively. Implementation and optimization of the automatic registration technique in Carm CBCT guidance of surgical procedures is underway.

Computer-assisted pelvic tumor resection: fields of application, limits, and perspectives

The treatment of malignant tumors involving the pelvic area is a challenging problem in musculoskeletal oncology due to the complex pelvic anatomy and the often large tumor size at presentation. The use of navigation systems has effectively increased surgical precision aiming at optimal preservation of pelvic structures without compromising oncologic outcome by means of improved visibility of the surgical field, and enabling intraoperative display and 3D reproduction of preoperatively determined pelvic osteotomy and resection levels. In the following sections, current developments in computer-assisted pelvic surgery are reviewed and possible fields of application, as well as limitations of navigation systems, are discussed.

Fast and accurate registration of cranial CT images with A-mode ultrasound

PURPOSE

Within the CRANIO project, a navigation module based on preoperative computed tomography (CT) data was developed for Computer and Robot Assisted Neurosurgery. The approach followed for non-invasive user-interactive registration of cranial CT images with the physical operating space consists of surface-based registration following pre-registration based on anatomical landmarks. Surface-based registration relies on bone surface points digitized transcutaneously by means of an optically tracked A-mode ultrasound (US) probe. As probe alignment and thus bone surface point digitization may be time-consuming, we investigated how to obtain high registration accuracy despite inaccurate pre-registration and a limited number of digitized bone surface points. Furthermore, we aimed at efficient man-machine-interaction during the probe alignment process. Finally, we addressed the problem of registration plausibility estimation in our approach.

METHOD

We modified the Iterative Closest Point (ICP) algorithm, presented by Besl and McKay and frequently used for surface-based registration, such that it can escape from local minima of the cost function to be iteratively minimized. The random-based ICP (R-ICP) we developed is less influenced by the quality of the pre-registration as it can escape from local minima close to the starting point for iterative optimization in the 6D domain of rigid transformations. The R-ICP is also better suited to approximate the global minimum as it can escape from local minima in the vicinity of the global minimum, too. Furthermore, we developed both CT-less and CT-based probe alignment tools along with appropriate man-machine strategies for a more time-efficient palpation process. To improve registration reliability, we developed a simple plausibility test based on data readily available after registration.

RESULTS

In a cadaver study, where we evaluated the R-ICP algorithm, the probe alignment tools, and the plausibility test, the R-ICP algorithm consistently outperformed the ICP algorithm. Almost no influence of the pre-registration on the final R-ICP registration accuracy could be observed. The probe alignment tools were judged to be useful and allowed for the digitization of 18 bone surface points within 2 min on average. The plausibility test was helpful to detect poor registration accuracy.

CONCLUSION

The R-ICP algorithm can provide high registration accuracy despite inaccurate pre-registration and a very limited number of data points. R-ICP registration was shown to be practical and robust versus the quality of the pre-registration. Time-efficiency of the cranial palpation process may be greatly increased and should encourage clinical acceptance.

A minimally invasive registration method using surface template-assisted marker positioning (STAMP) for image-guided otologic surgery

OBJECTIVE

A new, minimally invasive registration method was developed for image-guided otologic surgery. We utilized laser-sintered template of the patient's bone surface to transfer the virtual markers to the patient's bone intraoperatively and eliminated the necessity for preoperative marker positioning or additional CT scan.

STUDY DESIGN

Simulation surgeries and clinical application.

SUBJECTS AND METHODS

We measured registration errors in 10 trials using replicas and six ear surgeries (two cochlear implant insertions, four translabyrinthine acoustic tumor removals).

RESULTS

The target registration errors varied among the surgical targets. Errors were less than 1 mm near the cochlear implant insertion target both in phantom study and in actual surgeries.

CONCLUSION

Our newly developed method reduced the preoperative procedures for patients but did not reduce the accuracy in cochlear implant surgery. Our method would be a useful image-guided surgery method in the field of otology, where both accuracy and noninvasiveness are required.

Customized, rapid-production microstereotactic table for surgical targeting: description of concept and in vitro validation

PURPOSE

To introduce a novel microstereotactic frame, called the Microtable, consisting of a tabletop that mounts on bone-implanted spherical markers. The microtable is customized for individual patient anatomy to guide a surgical instrument to a specified target.

METHODS

Fiducial markers are bone-implanted, and CT scanning is performed. A microtable is custom-designed for the location of the markers and the desired surgical trajectory and is constructed using a computer-numerical-control machine. Validation studies were performed on phantoms with geometry similar to that for cochlear implant surgery. Two designs were tested with two different types of fiducial markers.

RESULTS

Mean targeting error of the microtables for the two designs were 0.37 +/- 0.18 and 0.60 +/- 0.21 mm (n = 5). Construction of each microtable required approximately 6 min.

CONCLUSIONS

The new frame achieves both high accuracy and rapid fabrication. We are currently using the microtable for clinical testing of the concept of percutaneous cochlear implant surgery.

Accuracy of image-guided surgical systems at the lateral skull base as clinically assessed using bone-anchored hearing aid posts as surgical targets

OBJECTIVE

Image-guided surgical (IGS) technology has been clinically available for more than a decade. To date, no acceptable standard exists for reporting the accuracy of IGS systems, especially for lateral skull base applications. We present a validation method that uses the post from bone-anchored hearing aid (BAHA) patients as a target. We then compare the accuracy of 2 IGS systems-one using laser skin-surface scanning (LSSS) and another using a noninvasive fiducial frame (FF) attached to patient via dental bite-block (DBB) for registration.

STUDY DESIGN

Prospective.

SETTING

Tertiary referral center.

PATIENTS

Six BAHA patients who had adequate dentition for creation of a DBB.

INTERVENTION(S)

For each patient, a dental impression was obtained, and a customized DBB was made to hold an FF. Temporal bone computed tomographic (CT) scans were obtained with the patient wearing the DBB, FF, and a customized marker on the BAHA post. In a mock operating room, CT scans were registered to operative anatomy using 2 methods: 1) LSSS and 2) FF.

MAIN OUTCOME MEASURE(S)

For each patient and each system, the position of the BAHA marker in the CT scan and in the mock operating room (using optical measurement technology) was compared, and the distances between them are reported to demonstrate accuracy.

RESULTS

Accuracy (mean +/- standard deviation) was 1.54 +/- 0.63 mm for DBB registration and 3.21 +/- 1.02 mm for LSSS registration.

CONCLUSION

An IGS system using FF registration is more accurate than one using LSSS (p = 0.03, 2-sided Student's t test). BAHA patients provide a unique patient population upon which IGS systems may be validated.

An integrated system for planning, navigation and robotic assistance for skull base surgery

BACKGROUND

We developed an image-guided robot system to provide mechanical assistance for skull base drilling, which is performed to gain access for some neurosurgical interventions, such as tumour resection. The motivation for introducing this robot was to improve safety by preventing the surgeon from accidentally damaging critical neurovascular structures during the drilling procedure.

METHODS

We integrated a Stealthstation navigation system, a NeuroMate robotic arm with a six-degree-of-freedom force sensor, and the 3D Slicer visualization software to allow the robotic arm to be used in a navigated, cooperatively-controlled fashion by the surgeon. We employed virtual fixtures to constrain the motion of the robot-held cutting tool, so that it remained in the safe zone that was defined on a preoperative CT scan.

RESULTS

We performed experiments on both foam skull and cadaver heads. The results for foam blocks cut using different registrations yielded an average placement error of 0.6 mm and an average dimensional error of 0.6 mm. We drilled the posterior porus acusticus in three cadaver heads and concluded that the robot-assisted procedure is clinically feasible and provides some ergonomic benefits, such as stabilizing the drill. We obtained postoperative CT scans of the cadaver heads to assess the accuracy and found that some bone outside the virtual fixture boundary was cut. The typical overcut was 1-2 mm, with a maximum overcut of about 3 mm.

CONCLUSIONS

The image-guided cooperatively-controlled robot system can improve the safety and ergonomics of skull base drilling by stabilizing the drill and enforcing virtual fixtures to protect critical neurovascular structures. The next step is to improve the accuracy so that the overcut can be reduced to a more clinically acceptable value of about 1 mm.

Evaluation of four volume-based image registration algorithms

We evaluated 4 volume-based automatic image registration algorithms from 2 commercially available treatment planning systems (Philips Syntegra and BrainScan). The algorithms based on cross correlation (CC), local correlation (LC), normalized mutual information (NMI), and BrainScan mutual information (BSMI) were evaluated with: (1) the synthetic computed tomography (CT) images, (2) the CT and magnetic resonance (MR) phantom images, and (3) the CT and MR head image pairs from 12 patients with brain tumors. For the synthetic images, the registration results were compared with known transformation parameters, and all algorithms achieved accuracy of submillimeter in translation and subdegree in rotation. For the phantom images, the registration results were compared with those provided by frame and marker-based manual registration. For the patient images, the results were compared with anatomical landmark-based manual registration to qualitatively determine how the results were close to a clinically acceptable registration. NMI and LC outperformed CC and BSMI, with the sense of being closer to a clinically acceptable result. As for the robustness, NMI and BSMI outperformed CC and LC. A guideline of image registration in our institution was given, and final visual assessment is necessary to guarantee reasonable results.

Image guided medialization laryngoplasty

Techniques that originate in computer graphics and computer vision have found prominent applications in the medical domain. In this paper, we have seamlessly developed techniques from computer graphics and computer vision together with domain knowledge from medicine to develop an image guided surgical system for medialization laryngoplasty. The technical focus of this paper is to register the preoperative radiological data to the intraoperative anatomical structure of the patient. With careful analysis of the real-world surgical environment, we have developed an ICP-based partial shape matching algorithm to register the partially visible anatomical structure to the preoperative CT data. We extracted distinguishable features from the human thyroid cartilage surface and applied image space template matching to find the initial guess for the shape matching. The experimental result shows that our feature-based partial shape matching method has better performance and robustness compared with original ICP-based shape matching method. Although this paper concentrates on the medialization laryngoplasty procedure, its generality makes our methods ideal for future applications in other image guided surgical areas.

Mutual-information-based image to patient re-registration using intraoperative ultrasound in image-guided neurosurgery

An image-based re-registration scheme has been developed and evaluated that uses fiducial registration as a starting point to maximize the normalized mutual information (nMI) between intraoperative ultrasound (iUS) and preoperative magnetic resonance images (pMR). We show that this scheme significantly (p<0.001) reduces tumor boundary misalignment between iUS pre-durotomy and pMR from an average of 2.5 mm to 1.0 mm in six resection surgeries. The corrected tumor alignment before dural opening provides a more accurate reference for assessing subsequent intraoperative tumor displacement, which is important for brain shift compensation as surgery progresses. In addition, we report the translational and rotational capture ranges necessary for successful convergence of the nMI registration technique (5.9 mm and 5.2 deg, respectively). The proposed scheme is automatic, sufficiently robust, and computationally efficient (<2 min), and holds promise for routine clinical use in the operating room during image-guided neurosurgical procedures.

Robust gradient-based 3-D/2-D registration of CT and MR to X-ray images

One of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patient's anatomy and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D images and matching them to the preinterventional 3-D image via 3-D/2-D image registration. A novel 3-D/2-D registration method is proposed in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was evaluated using the publicly available standardized evaluation methodology for 3-D/2-D registration, consisting of 3-D rotational X-ray, computed tomography, magnetic resonance (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.

Feasibility study for image-guided kidney surgery: assessment of required intraoperative surface for accurate physical to image space registrations

A notable complication of applying current image-guided surgery techniques of soft tissue to kidney resections (nephrectomies) is the limited field of view of the intraoperative kidney surface. This limited view constrains the ability to obtain a sufficiently geometrically descriptive surface for accurate surface-based registrations. The authors examined the effects of the limited view by using two orientations of a kidney phantom to model typical laparoscopic and open partial nephrectomy views. Point-based registrations, using either rigidly attached markers or anatomical landmarks as fiducials, served as initial alignments for surface-based registrations. Laser range scanner (LRS) obtained surfaces were registered to the phantom's image surface using a rigid iterative closest point algorithm. Subsets of each orientation's LRS surface were used in a robustness test to determine which parts of the surface yield the most accurate registrations. Results suggest that obtaining accurate registrations is a function of the percentage of the total surface and of geometric surface properties, such as curvature. Approximately 28% of the total surface is required regardless of the location of that surface subset. However, that percentage decreases when the surface subset contains information from opposite ends of the surface and/or unique anatomical features, such as the renal artery and vein.

Validation of a method for coregistering scalp recording locations with 3D structural MR images

A common problem in brain imaging is how to most appropriately coregister anatomical and functional data sets into a common space. For surface-based recordings such as the event related optical signal (EROS), near-infrared spectroscopy (NIRS), event-related potentials (ERPs), and magnetoencephalography (MEG), alignment is typically done using either (1) a landmark-based method involving placement of surface markers that can be detected in both modalities; or (2) surface-fitting alignment that samples many points on the surface of the head in the functional space and aligns those points to the surface of the anatomical image. Here we compare these two approaches and advocate a combination of the two in order to optimize coregistration of EROS and NIRS data with structural magnetic resonance images (sMRI). Digitized 3D sensor locations obtained with a Polhemus digitizer can be effectively coregistered with sMRI using fiducial alignment as an initial guess followed by a Marquardt-Levenberg least-squares rigid-body transform (df = 6) to match the surfaces. Additional scaling parameters (df = 3) and point-by-point surface constraints can also be employed to further improve fitting. These alignment procedures place the lower-bound residual error at 1.3 +/- 0.1 mm (micro +/- s) and the upper-bound target registration error at 4.4 +/- 0.6 mm (micro +/- s). The dependence of such errors on scalp segmentation, number of registration points, and initial guess is also investigated. By optimizing alignment techniques, anatomical localization of surface recordings can be improved in individual subjects.

Localization and registration accuracy in image guided neurosurgery: a clinical study

PURPOSE

To measure and compare the clinical localization and registration errors in image-guided neurosurgery, with the purpose of revising current assumptions.

MATERIALS AND METHODS

Twelve patients who underwent brain surgeries with a navigation system were randomly selected. A neurosurgeon localized and correlated the landmarks on preoperative MRI images and on the intraoperative physical anatomy with a tracked pointer. In the laboratory, we generated 612 scenarios in which one landmark pair was defined as the target and the remaining ones were used to compute the registration transformation. Four errors were measured: (1) fiducial localization error (FLE); (2) target registration error (TRE); (3) fiducial registration error (FRE); (4) Fitzpatrick's target registration error estimation (F-TRE). We compared the different errors and computed their correlation.

RESULTS

The image and physical FLE ranges were 0.5-2.0 and 1.6-3.0 mm, respectively. The measured TRE, FRE and F-TRE were 4.1 +/- 1.6, 3.9 +/- 1.2, and 3.7 +/- 2.2 mm, respectively. Low correlations of 0.19 and 0.37 were observed between the FRE and TRE and between the F-TRE and the TRE, respectively. The differences of the FRE and F-TRE from the TRE were 1.3 +/- 1.0 mm (max = 5.5 mm) and 1.3 +/- 1.2 mm (max = 7.3 mm), respectively.

CONCLUSION

Contrary to common belief, the FLE presents significant variations. Moreover, both the FRE and the F-TRE are poor indicators of the TRE in image-to-patient registration.

Frameless stereotactic placement of foramen ovale electrodes in patients with drug-refractory temporal lobe epilepsy

OBJECTIVE

Semi-invasive foramen ovale electrodes (FOEs) are used as an alternative to invasive recording techniques in the presurgical evaluation of patients with temporal lobe epilepsy. To maximize patient safety and interventional success, frameless stereotactic FOE placement by use of a variation of an upper jaw fixation device with an external fiducial frame, in combination with an aiming device and standard navigation software, was evaluated by the Innsbruck Epilepsy Surgery Program.

METHODS

Patients were immobilized noninvasively with the Vogele-Bale-Hohner headholder (Medical Intelligence GmbH, Schwabmünchen, Germany) to plan computed tomography and surgery. Frameless stereotactic cannulation of the foramen and intracranial electrode placement were achieved with the help of an aiming device mounted to the base plate of the headholder. Ease of applicability, safety, and results obtained with foramen ovale recording were investigated.

RESULTS

Twenty-six FOEs were placed in 13 patients under general anesthesia. The foramen ovale was successfully cannulated in all patients. One patient reported transient painful mastication after the procedure as a complication attributable to use of the Vogele-Bale-Hohner mouthpiece. In one patient, a persistent slight buccal hypesthesia was present 3 months after the procedure. To pass the foramen, slight adjustments in the needle position had to be made in 10 sides (38.4%). To place the intracranial electrodes, adjustments were necessary six times (23.7%). An entirely new path had to be planned once (3.8%). Seizure recording provided conclusive information in all patients (100%). Outcome in operated patients was Engel Class Ia in six patients, Class IId in one patient, Class IIb in one patient, and Class IVa in one patient (minimum follow-up, 6 mo).

CONCLUSION

The Vogele-Bale-Hohner headholder combined with an external registration frame eliminates the need for invasive head clamp fixation. FOE placement can be planned "offline" and performed under general anesthesia later. This can be valuable in patients with distorted anatomy and/or small foramina or in patients not able to undergo the procedure under sedation. Results are satisfactory with regard to patient safety, patient comfort, predictability, and reproducibility. FOEs supported further treatment decisions in all patients.

Accuracy and reproducibility of tumor positioning during prolonged and multi-modality animal imaging studies

Dedicated small-animal imaging devices, e.g. positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI) scanners, are being increasingly used for translational molecular imaging studies. The objective of this work was to determine the positional accuracy and precision with which tumors in situ can be reliably and reproducibly imaged on dedicated small-animal imaging equipment. We designed, fabricated and tested a custom rodent cradle with a stereotactic template to facilitate registration among image sets. To quantify tumor motion during our small-animal imaging protocols, 'gold standard' multi-modality point markers were inserted into tumor masses on the hind limbs of rats. Three types of imaging examination were then performed with the animals continuously anesthetized and immobilized: (i) consecutive microPET and MR images of tumor xenografts in which the animals remained in the same scanner for 2 h duration, (ii) multi-modality imaging studies in which the animals were transported between distant imaging devices and (iii) serial microPET scans in which the animals were repositioned in the same scanner for subsequent images. Our results showed that the animal tumor moved by less than 0.2-0.3 mm over a continuous 2 h microPET or MR imaging session. The process of transporting the animal between instruments introduced additional errors of approximately 0.2 mm. In serial animal imaging studies, the positioning reproducibility within approximately 0.8 mm could be obtained.

Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations

In this article a comprehensive set of registration methods is utilized to provide image-to-physical space registration for image-guided neurosurgery in a clinical study. Central to all methods is the use of textured point clouds as provided by laser range scanning technology. The objective is to perform a systematic comparison of registration methods that include both extracranial (skin marker point-based registration (PBR), and face-based surface registration) and intracranial methods (feature PBR, cortical vessel-contour registration, a combined geometry/intensity surface registration method, and a constrained form of that method to improve robustness). The platform facilitates the selection of discrete soft-tissue landmarks that appear on the patient's intraoperative cortical surface and the preoperative gadolinium-enhanced magnetic resonance (MR) image volume, i.e., true corresponding novel targets. In an 11 patient study, data were taken to allow statistical comparison among registration methods within the context of registration error. The results indicate that intraoperative face-based surface registration is statistically equivalent to traditional skin marker registration. The four intracranial registration methods were investigated and the results demonstrated a target registration error of 1.6 +/- 0.5 mm, 1.7 +/- 0.5 mm, 3.9 +/- 3.4 mm, and 2.0 +/- 0.9 mm, for feature PBR, cortical vessel-contour registration, unconstrained geometric/intensity registration, and constrained geometric/intensity registration, respectively. When analyzing the results on a per case basis, the constrained geometric/intensity registration performed best, followed by feature PBR, and finally cortical vessel-contour registration. Interestingly, the best target registration errors are similar to targeting errors reported using bone-implanted markers within the context of rigid targets. The experience in this study as with others is that brain shift can compromise extracranial registration methods from the earliest stages. Based on the results reported here, organ-based approaches to registration would improve this, especially for shallow lesions.

A comparative analysis of coregistered ultrasound and magnetic resonance imaging in neurosurgery

OBJECTIVE

This work presents qualitative and quantitative side-by-side comparisons of oblique coregistered magnetic resonance imaging (MRI) scans and ultrasound images obtained during 35 neurosurgical procedures.

METHODS

Spatially registered series of ultrasound images were recorded for subsequent off-line evaluation and comparison with corresponding preoperative MRI studies. The degree of misalignment was reduced by reregistering the target volume directly with segmented features.

RESULTS

The initial apparent spatial misalignment of the target volume after craniotomy ranged from 0.11 to 8.73 mm (mean, 4.01 mm). After reregistration, the mutual information in overlapping segmented features was increased, presumably evidence of a better alignment locally. Additionally, the degree of feature congruence, which was assessed quantitatively through a convex hull approximation, demonstrated that the ultrasound volume was consistently smaller than its MRI counterpart.

CONCLUSION

Although intraoperative ultrasound tends to be difficult to interpret by itself, when accurately coregistered with preoperative MRI scans, its potential utility as a navigational guide is enhanced.