Comparison of registration accuracy of skin- and bone-implanted fiducials for frameless stereotaxis of the brain: a prospective study

Accuracy of frameless image-guided implantation of depth electrodes for intracranial epilepsy monitoring

OBJECTIVE

Various techniques are available for stereotactic implantation of depth electrodes for intracranial epilepsy monitoring. The goal of this study was to evaluate the accuracy and effectiveness of frameless MRI-guided depth electrode implantation.

METHODS

Using a frameless MRI-guided stereotactic approach (Stealth), depth electrodes were implanted in patients via burr holes or craniotomy, mostly into the medial temporal lobe. In all cases in which it was possible, postoperative MR images were coregistered to planning MR images containing the marked targets for quantitative analysis of intended versus actual location of each electrode tip. In the subset of MR images done with sufficient resolution, qualitative assessment of anatomical accuracy was performed. Finally, the effectiveness of implanted electrodes for identifying seizure onset was retrospectively examined.

RESULTS

Sixty-eight patients underwent frameless implantation of 413 depth electrodes (96% to mesial temporal structures) via burr holes by one surgeon at 2 institutions. In 36 patients (203 electrodes) planning and postoperative MR images were available for quantitative analysis; an additional 8 procedures with 19 electrodes implanted via craniotomy for grid were also available for quantitative analysis. The median distance between intended target and actual tip location was 5.19 mm (mean 6.19 ± 4.13 mm, range < 2 mm-29.4 mm). Inaccuracy for transtemporal depths was greater along the electrode (i.e., deep), and posterior, whereas electrodes inserted via an occipital entry deviated radially. Failure to localize seizure onset did not result from implantation inaccuracy, although 2 of 62 patients (3.2%)-both with electrodes inserted occipitally-required reoperation. Complications were mostly transient, but resulted in long-term deficit in 2 of 68 patients (3%).

CONCLUSIONS

Despite modest accuracy, frameless depth electrode implantation was sufficient for seizure localization in the medial temporal lobe when using the orthogonal approach, but may not be adequate for occipital trajectories.

Intraoperative image updating for brain shift following dural opening

OBJECTIVE Preoperative magnetic resonance images (pMR) are typically coregistered to provide intraoperative navigation, the accuracy of which can be significantly compromised by brain deformation. In this study, the authors generated updated MR images (uMR) in the operating room (OR) to compensate for brain shift due to dural opening, and evaluated the accuracy and computational efficiency of the process. METHODS In 20 open cranial neurosurgical cases, a pair of intraoperative stereovision (iSV) images was acquired after dural opening to reconstruct a 3D profile of the exposed cortical surface. The iSV surface was registered with pMR to detect cortical displacements that were assimilated by a biomechanical model to estimate whole-brain nonrigid deformation and produce uMR in the OR. The uMR views were displayed on a commercial navigation system and compared side by side with the corresponding coregistered pMR. A tracked stylus was used to acquire coordinate locations of features on the cortical surface that served as independent positions for calculating target registration errors (TREs) for the coregistered uMR and pMR image volumes. RESULTS The uMR views were visually more accurate and well aligned with the iSV surface in terms of both geometry and texture compared with pMR where misalignment was evident. The average misfit between model estimates and measured displacements was 1.80 ± 0.35 mm, compared with the average initial misfit of 7.10 ± 2.78 mm between iSV and pMR, and the average TRE was 1.60 ± 0.43 mm across the 20 patients in the uMR image volume, compared with 7.31 ± 2.82 mm on average in the pMR cases. The iSV also proved to be accurate with an average error of 1.20 ± 0.37 mm. The overall computational time required to generate the uMR views was 7-8 minutes. CONCLUSIONS This study compensated for brain deformation caused by intraoperative dural opening using computational model-based assimilation of iSV cortical surface displacements. The uMR proved to be more accurate in terms of model-data misfit and TRE in the 20 patient cases evaluated relative to pMR. The computational time was acceptable (7-8 minutes) and the process caused minimal interruption of surgical workflow.

Exposing the Fundus of the Internal Acoustic Meatus without Entering the Labyrinth Using a Retrosigmoid Approach: Is It Possible?

OBJECTIVES

To evaluate the feasibility of performing a labyrinth-sparing neuronavigation-assisted retrosigmoid approach to the fundus of the internal acoustic meatus (IAM) and to describe the anatomy of the structures embedded in the posterior meatal wall.

METHODS

Ten surgical dissections were performed bilaterally on 5 fresh cadavers. Cadavers were subjected to preoperative computed tomography scans and spatial coordinates of inner ear structures were recorded. A retrosigmoid craniectomy was performed. The IAM was drilled towards the fundus until no more than 1 mm of bone covered the labyrinthine structures. Specimens underwent a new computed tomography scan to verify the length of opened IAM and the status of the labyrinth. We then opened the labyrinthine structures and recorded their coordinates using navigation. These were compared with the radiologic coordinates to verify the neuronavigation accuracy.

RESULTS

In 9 sides, the IAM was opened to the fundus without injuring the labyrinth; in 1 side, the vestibule was opened. The mean residual bone on the fundus was 0.97 mm. The average length of the accessible IAM was 88.95%. The best accuracy of the navigation was for the identification of the common crus, with a mean value of 0.73 mm.

CONCLUSIONS

This surgical technique could facilitate the opening of the IAM with preservation of inner ear structures. We opened a mean of 88.95% of the IAM without entering the labyrinthine structures in 90% of cases. These results confirm the feasibility of the retrosigmoid approach for the exposure of the IAM fundus with preservation of labyrinthine structures.

Stereovision to MR image registration for cortical surface displacement mapping to enhance image-guided neurosurgery

PURPOSE

A surface registration method is presented to align intraoperative stereovision (iSV) with preoperative magnetic resonance (pMR) images, which utilizes both geometry and texture information to extract tissue displacements as part of the overall process of compensating for intraoperative brain deformation in order to maintain accurate neuronavigational image guidance during surgery.

METHODS

A sum-of-squared-difference rigid image registration was first executed to detect lateral shift of the cortical surface and was followed by a mutual-information-based block matching method to detect local nonrigid deformation caused by distention or collapse of the cortical surface. Ten (N = 10) surgical cases were evaluated in which an independent point measurement of a dominant cortical surface feature location was recorded with a tracked stylus in each case and compared to its surface-registered counterpart. The full three-dimensional (3D) displacement field was also extracted to drive a biomechanical brain deformation model, the results of which were reconciled with the reconstructed iSV surface as another form of evaluation.

RESULTS

Differences between the tracked stylus coordinates of cortical surface features and their surface-registered locations were 1.94 ± 0.59 mm on average across the ten cases. When the complete displacement map derived from surface registration was utilized, the resulting images generated from mechanical model updates were consistent in terms of both geometry (1-2 mm of model misfit) and texture, and were generated with less than 10 min of computational time. Analysis of the surface-registered 3D displacements indicate that the magnitude of motion ranged from 4.03 to 9.79 mm in the ten patient cases, and the amount of lateral shift was not related statistically to the direction of gravity (p = 0.73 ≫ 0.05) or the craniotomy size (p = 0.48 ≫ 0.05) at the beginning of surgery.

CONCLUSIONS

The iSV-pMR surface registration method utilizes texture and geometry information to extract both global lateral shift and local nonrigid movement of the cortical surface in 3D. The results suggest small differences exist in surface-registered locations when compared to positions measured independently with a coregistered stylus and when the full iSV surface was aligned with model-updated MR. The effectiveness and efficiency of the registration method is also minimally disruptive to surgical workflow.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

PURPOSE

Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.

METHODS

Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.

RESULTS

In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).

CONCLUSIONS

Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.

Data assimilation using a gradient descent method for estimation of intraoperative brain deformation

Biomechanical models that simulate brain deformation are gaining attention as alternatives for brain shift compensation. One approach, known as the "forced-displacement method", constrains the model to exactly match the measured data through boundary condition (BC) assignment. Although it improves model estimates and is computationally attractive, the method generates fictitious forces and may be ill-advised due to measurement uncertainty. Previously, we have shown that by assimilating intraoperatively acquired brain displacements in an inversion scheme, the Representer algorithm (REP) is able to maintain stress-free BCs and improve model estimates by 33% over those without data guidance in a controlled environment. However, REP is computationally efficient only when a few data points are used for model guidance because its costs scale linearly in the number of data points assimilated, thereby limiting its utility (and accuracy) in clinical settings. In this paper, we present a steepest gradient descent algorithm (SGD) whose computational complexity scales nearly invariantly with the number of measurements assimilated by iteratively adjusting the forcing conditions to minimize the difference between measured and model-estimated displacements (model-data misfit). Solutions of full linear systems of equations are achieved with a parallelized direct solver on a shared-memory, eight-processor Linux cluster. We summarize the error contributions from the entire process of model-updated image registration compensation and we show that SGD is able to attain model estimates comparable to or better than those obtained with REP, capturing about 74-82% of tumor displacement, but with a computational effort that is significantly less (a factor of 4-fold or more reduction relative to REP) and nearly invariant to the amount of sparse data involved when the number of points assimilated is large. Based on five patient cases, an average computational cost of approximately 2 min for estimating whole-brain deformation has been achieved with SGD using 100 sparse data points, suggesting the new algorithm is sufficiently fast with adequate accuracy for routine use in the operating room (OR).

Application accuracy of computed tomography-based, image-guided navigation of temporal bone

OBJECTIVE

Although frameless stereotactic techniques have become indispensable in neurosurgery, their technical complexity requires careful definition and evaluation. Navigation is of particular concern when it is applied to approach a complex, tight surgical area like the temporal bone, where every millimeter is important. Theoretically, the temporal bone is an ideal location in which to use image-guided navigation because its bony construct precludes pre- and intraoperative shift. In this context, the feasibility of using a navigational system is determined by the system's accuracy and by the spatial characteristics of the targets. Literature addressing the accuracy of image guidance techniques in temporal bone surgery is relatively sparse. Accuracy of these systems within the temporal bone is still under investigation. We investigated the application accuracy of computed tomography-based, frameless, image-guided navigation to identify various bony structures in the temporal bone via a retrosigmoid approach.

METHODS

In a total of 10 operations, we performed a retrosigmoid approach simulating operative conditions on either side of 5 whole, fresh cadaveric heads. Six titanium microscrews were implanted around the planned craniotomy site as permanent bone reference markers before the surgical procedure. High-resolution computed tomographic scans were obtained (slice thickness, 0.6-mm, contiguous non-overlapping slices; gantry setting, 0 degrees; scan window diameter, 225 mm; pixel size, >0.44 x 0.44). We used a Stryker navigation system (Stryker Instruments, Kalamazoo, MI) for intraoperative navigation. External and internal targets were selected for calculation of navigation accuracy.

RESULTS

The system calculated target registration error to be 0.48 +/- 0.21 mm, and the global accuracies (navigation accuracies) were calculated using external over-the-skull and internal targets within the temporal bone. Overall navigation accuracy was 0.91 +/- 0.28 mm; for reaching internal targets within temporal bone, accuracy was 0.94 +/- 0.22 mm; and for external targets, accuracy was 0.83 +/- 0.11 mm. Ninety-five percent of targets could be reached within 1.4 mm of their actual position.

CONCLUSION

Using high-resolution computed tomography and bone-implanted reference markers, frameless navigation can be as accurate as frame-based stereotaxy in providing a guide to maximize safe surgical approaches to the temporal bone. Although error-free navigation is not possible with the submillimetric accuracy required by direct anatomic contouring of tiny structures within temporal bone, it still provides a road map to maximize safe surgical exposure.

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.

Computer aided surgery: concepts and applications in rhinology

Computer-aided surgery (CAS) has become relevant in a growing number of disciplines. This article will describe the history and principals of CAS and explain some of the technical issues, applications, and outcomes for CAS in the domain of rhinology.

Sources of registration error with image guidance systems during endoscopic anterior cranial base surgery

OBJECTIVES

The goal of this study was to evaluate the accuracy of the registration process and to identify potential sources of error during anterior cranial base surgery.

STUDY DESIGN AND SETTING

The registration accuracy of image guidance and the location of excluded fiducials were recorded prospectively from 50 endoscopic, anterior cranial base procedures in an academic university setting.

RESULTS

The mean error of initial registration was 2.8 mm (range, 1.4 to 7.1 mm). Following the exclusion of fiducials the mean error of registration was 1.6 mm (range, 0.6 to 3.7 mm). There was a significant improvement in the mean error rate from initial to final registration following the exclusion of fiducials (P < 0.0001). Posterior fiducials were excluded most often and anterior fiducials were excluded the least. Registration accuracy was similar for CT and MRI (P = 0.64).

CONCLUSIONS

The accuracy of the Stryker Image Guidance System is enhanced by the exclusion of individual fiducials with high registration errors.

SIGNIFICANCE

The exclusion of fiducials with high registration errors increases the accuracy of image guidance in anterior cranial base surgery.