Three-dimensional optical flow method for measurement of volumetric brain deformation from intraoperative MR images

Visualizing the neuroanatomical changes in Han Chinese adulthood: A pseudo-longitudinal study based on age-related large-scale statistical Chinese brain atlases

Objective:

Understanding how brain changes over lifetime provides the basis for new insights into neurophysiology and neuropathology. In this study, we carried out a pseudo-longitudinal study based on age-related Chinese brain atlases (i.e., Chinese2020) constructed from large-scale volumetric brain MRI data collected in normal Han Chinese adults at varying ages.

Methods:

In order to quantify the deformation and displacement of brains for each voxel as age increases, optical flow algorithm was employed to compute motion vectors between every two consecutive brain templates of the age-related brain atlas, i.e., Chinese2020.

Results:

Dynamic age-related neuroanatomical changes in a standardized brain space were shown. Overall, our results demonstrate that brain inward deformation (mainly due to atrophy) can appear in adulthood and this trend generally accelerates as age increases, affecting multiple regions including frontal cortex, temporal cortex, parietal cortex, and cerebellum, whereas occipital cortex is least affected by aging, and even showed some degree of outward deformation in the midlife.

Conclusion:

Our findings indicated more complicated age-related changes instead of a simple trend of brain volume decrease, which may be in line with the recently increasing interests in the age-related cortical complexity with other morphometry measures.

A comparison of thin-plate spline deformation and finite element modeling to compensate for brain shift during tumor resection

PURPOSE

Brain shift during tumor resection can progressively invalidate the accuracy of neuronavigation systems and affect neurosurgeons' ability to achieve optimal resections. This paper compares two methods that have been presented in the literature to compensate for brain shift: a thin-plate spline deformation model and a finite element method (FEM). For this comparison, both methods are driven by identical sparse data. Specifically, both methods are driven by displacements between automatically detected and matched feature points from intraoperative 3D ultrasound (iUS). Both methods have been shown to be fast enough for intraoperative brain shift correction (Machado et al. in Int J Comput Assist Radiol Surg 13(10):1525-1538, 2018; Luo et al. in J Med Imaging (Bellingham) 4(3):035003, 2017). However, the spline method requires no preprocessing and ignores physical properties of the brain while the FEM method requires significant preprocessing and incorporates patient-specific physical and geometric constraints. The goal of this work was to explore the relative merits of these methods on recent clinical data.

METHODS

Data acquired during 19 sequential tumor resections in Brigham and Women's Hospital's Advanced Multi-modal Image-Guided Operating Suite between December 2017 and October 2018 were considered for this retrospective study. Of these, 15 cases and a total of 24 iUS to iUS image pairs met inclusion requirements. Automatic feature detection (Machado et al. in Int J Comput Assist Radiol Surg 13(10):1525-1538, 2018) was used to detect and match features in each pair of iUS images. Displacements between matched features were then used to drive both the spline model and the FEM method to compensate for brain shift between image acquisitions. The accuracies of the resultant deformation models were measured by comparing the displacements of manually identified landmarks before and after deformation.

RESULTS

The mean initial subcortical registration error between preoperative MRI and the first iUS image averaged 5.3 ± 0.75 mm. The mean subcortical brain shift, measured using displacements between manually identified landmarks in pairs of iUS images, was 2.5 ± 1.3 mm. Our results showed that FEM was able to reduce subcortical registration error by a small but statistically significant amount (from 2.46 to 2.02 mm). A large variability in the results of the spline method prevented us from demonstrating either a statistically significant reduction in subcortical registration error after applying the spline method or a statistically significant difference between the results of the two methods.

CONCLUSIONS

In this study, we observed less subcortical brain shift than has previously been reported in the literature (Frisken et al., in: Miller (ed) Biomechanics of the brain, Springer, Cham, 2019). This may be due to the fact that we separated out the initial misregistration between preoperative MRI and the first iUS image from our brain shift measurements or it may be due to modern neurosurgical practices designed to reduce brain shift, including reduced craniotomy sizes and better control of intracranial pressure with the use of mannitol and other medications. It appears that the FEM method and its use of geometric and biomechanical constraints provided more consistent brain shift correction and better correction farther from the driving feature displacements than the simple spline model. The spline-based method was simpler and tended to give better results for small deformations. However, large variability in the spline results and relatively small brain shift prevented this study from demonstrating a statistically significant difference between the results of the two methods.

Preliminary Results Comparing Thin Plate Splines with Finite Element Methods for Modeling Brain Deformation during Neurosurgery using Intraoperative Ultrasound

Brain shift compensation attempts to model the deformation of the brain which occurs during the surgical removal of brain tumors to enable mapping of presurgical image data into patient coordinates during surgery and thus improve the accuracy and utility of neuro-navigation. We present preliminary results from clinical tumor resections that compare two methods for modeling brain deformation, a simple thin plate spline method that interpolates displacements and a more complex finite element method (FEM) that models physical and geometric constraints of the brain and its material properties. Both methods are driven by the same set of displacements at locations surrounding the tumor. These displacements were derived from sets of corresponding matched features that were automatically detected using the SIFT-Rank algorithm. The deformation accuracy was tested using a set of manually identified landmarks. The FEM method requires significantly more preprocessing than the spline method but both methods can be used to model deformations in the operating room in reasonable time frames. Our preliminary results indicate that the FEM deformation model significantly out-performs the spline-based approach for predicting the deformation of manual landmarks. While both methods compensate for brain shift, this work suggests that models that incorporate biophysics and geometric constraints may be more accurate.

Role of high-field intraoperative magnetic resonance imaging on a multi-image fusion-guided stereotactic biopsy of the basal ganglia: A case report

The aim of the present case study was to investigate the advantages of intraoperative magnetic resonance imaging (iMRI) on the real-time guidance and monitoring of a stereotactic biopsy. The study describes a patient with intracranial lesions, which were examined by conventional MRI and diffusion tensor imaging using a 1.5T intraoperative MRI system. The digital and pre-operative positron emission/computed tomography image data were transferred to a BrainLAB planning workstation, and a variety of images were automatically fused. The BrainLAB software was then used to reconstruct the corticospinal tract (CST) and create a three-dimensional display of the anatomical association between the CST and the brain lesions. A Leksell surgical planning workstation was used to identify the ideal target site and a reasonable needle track for the biopsy. The 1.5T iMRI was used to effectively monitor the intracranial condition during the brain biopsy procedure. Post-operatively, the original symptoms of the patient were not aggravated and no further neurological deficits were apparent. The histopathological diagnosis of non-Hodgkin's B-cell lymphoma was made. Using high-field iMRI, the multi-image fusion-guided stereotactic brain biopsy allows for a higher positive rate of biopsy and a lower incidence of complications. The approach of combining multi-image fusion images with the frame-based stereotactic biopsy may be clinically useful for intracranial lesions of deep functional areas.

Brain shift during bur hole–based procedures using interventional MRI

Object

Brain shift during minimally invasive, bur hole–based procedures such as deep brain stimulation (DBS) electrode implantation and stereotactic brain biopsy is not well characterized or understood. We examine shift in various regions of the brain during a novel paradigm of DBS electrode implantation using interventional imaging throughout the procedure with high-field interventional MRI.

Methods

Serial MR images were obtained and analyzed using a 1.5-T magnet prior to, during, and after the placement of DBS electrodes via frontal bur holes in 44 procedures. Three-dimensional coordinates in MR space of unique superficial and deep brain structures were recorded, and the magnitude, direction, and rate of shift were calculated. Measurements were recorded to the nearest 0.1 mm.

Results

Shift ranged from 0.0 to 10.1 mm throughout all structures in the brain. The greatest shift was seen in the frontal lobe, followed by the temporal and occipital lobes. Shift was also observed in deep structures such as the anterior and posterior commissures and basal ganglia; shift in the pallidum and subthalamic region ipsilateral to the bur hole averaged 0.6 mm, with 9% of patients having over 2 mm of shift in deep brain structures. Small amounts of shift were observed during all procedures; however, the initial degree of shift and its direction were unpredictable.

Conclusions

Brain shift is continual and unpredictable and can render traditional stereotactic targeting based on preoperative imaging inaccurate even in deep brain structures such as those used for DBS.

Near Real-Time Computer Assisted Surgery for Brain Shift Correction Using Biomechanical Models

Conventional image-guided neurosurgery relies on preoperative images to provide surgical navigational information and visualization. However, these images are no longer accurate once the skull has been opened and brain shift occurs. To account for changes in the shape of the brain caused by mechanical (e.g., gravity-induced deformations) and physiological effects (e.g., hyperosmotic drug-induced shrinking, or edema-induced swelling), updated images of the brain must be provided to the neuronavigation system in a timely manner for practical use in the operating room. In this paper, a novel preoperative and intraoperative computational processing pipeline for near real-time brain shift correction in the operating room was developed to automate and simplify the processing steps. Preoperatively, a computer model of the patient's brain with a subsequent atlas of potential deformations due to surgery is generated from diagnostic image volumes. In the case of interim gross changes between diagnosis, and surgery when reimaging is necessary, our preoperative pipeline can be generated within one day of surgery. Intraoperatively, sparse data measuring the cortical brain surface is collected using an optically tracked portable laser range scanner. These data are then used to guide an inverse modeling framework whereby full volumetric brain deformations are reconstructed from precomputed atlas solutions to rapidly match intraoperative cortical surface shift measurements. Once complete, the volumetric displacement field is used to update, i.e., deform, preoperative brain images to their intraoperative shifted state. In this paper, five surgical cases were analyzed with respect to the computational pipeline and workflow timing. With respect to postcortical surface data acquisition, the approximate execution time was 4.5 min. The total update process which included positioning the scanner, data acquisition, inverse model processing, and image deforming was ~11-13 min. In addition, easily implemented hardware, software, and workflow processes were identified for improved performance in the near future.

Special surgical considerations for functional brain mapping

The development of functional mapping techniques gives neurosurgeons many options for preoperative planning. Integrating functional and anatomic data can inform patient selection and surgical planning and makes functional mapping more accessible than when only invasive studies were available. However, the applications of functional mapping to neurosurgical patients are still evolving. Functional imaging remains complex and requires an understanding of the underlying physiologic and imaging characteristics. Neurosurgeons must be accustomed to interpreting highly processed data. Successful implementation of functional image-guided procedures requires efficient interactions between neurosurgeon, neurologist, radiologist, neuropsychologist, and others, but promises to enhance the care of patients.

Multimodality intraoperative MRI for brain tumor surgery

Intraoperative MRI has already fundamentally changed the way current brain tumor surgery is performed. The ability to integrate high-field MRI into the operating room has allowed intraoperative MRI to emerge as an important adjunct to CNS tumor treatment. Furthermore, the ability of MRI to successfully couple with molecular imaging (PET and/or optical imaging), neuroendoscopy and therapeutic devices, such as focused ultrasound, will allow it to emerge as an important image-guidance modality for improving brain tumor therapy and outcomes.

From vision to reality: the origins of intraoperative MR imaging

Intraoperative MR imaging has become one of the most important concepts in present day neurosurgery. The brain shift problem with navigation, the need for assessment of the degree of resection and the need for detection of early postoperative complications were the three most important motives that drove the development of this technology. The GE Signa System with the "double doughnut" design was the world's first intraoperative MRI. From 1995 to 2007 more than 1,000 neurosurgical cases were performed with the system. The system was used by several different specialties and in neurosurgery it was most useful for complete resection of low-grade gliomas, identification and resection of small or deep metastases or cavernomas, recurrent pituitary adenomas, cystic tumors, biopsies in critical areas and surgery in recurrent GBM cases. Main superiorities of the system were the ability to scan without patient movement to get image updates, the ability to do posterior fossa cases and other difficult patient positioning, the easiness of operation using intravenous sedation anesthesia and the flexibility of the system to be used as platform for new diagnostic and therapeutic modalities.

Image-guided ultrasonography for recurrent cystic gliomas

BACKGROUND

Long-term survival of patients with recurrent gliomas depends on the extent of resection. Thus, the desirability of an intra-operative imaging modality that can augment the resection extension without affecting vital surrounding structures is more than obvious. It was the aim of the present study to evaluate a possible benefit of image-guided intra-operative ultrasonography for the surgery of recurrent gliomas.

METHOD

The authors performed ultrasonography-assisted image-guided resection of recurrent gliomas in 16 patients. An ultrasound device (IGSonic) was integrated into the VectorVision2 navigation system (BrainLAB, Heimstetten, Germany). The IGSonic Probe 10V5 was connected to the VectorVision Navigation station via an IGSonic Device Box. Following patient registration, MRI based neuronavigation was used to determine the skin incision and the bone flap. Before opening the dura, the underlying structures were explored by ultrasound combined with the corresponding MR images. The navigated ultrasound displayed the sonographic image of the intracranial anatomy on the navigation screen in a composed overlay fashion.

FINDINGS

The integration of intra-operative ultrasound into neuronavigation system offered quick and helpful intra-operative images in all 16 procedures. Due to the specific ultrasonic characteristics of the solid and the cystic parts, our technique created highly useful images in 10 patients with cystic recurrences. In these, user friendly images were obtained that were easy to understand even for neurosurgeons without major experience in intra-operative ultrasound.

CONCLUSIONS

Neurosonography is a time- and cost-effective technology offering intra-operative imaging. The improved orientation and visualization of tumour remnants, adjacent ventricles, and the enhanced intra- and peri-tumoural vasculature is one of the main advantages of ultrasonography-assisted image-guided surgery, which is most obvious during surgery for cystic gliomas.

Quasi-real-time neurosurgery support by MRI processing via grid computing

One problem of providing time-critical medical services over the grid is always its dependency on the Internet. It cannot be assumed that transfer ofa certain amount of data over the Internet is always achieved during a specified period. Such a requirement cannot be fulfilled by the infrastructure of the Web. There is always the risk of a network delay or even an overload. Because of this, another goal of this project is the evaluation of grid services versus the use of local services. A further point for future research related to the chain has to deal with the optimization approach for the linear registration step. Because the optimization uses the downhill simplex algorithm in a nine-dimensional search space, the number of iterations needed to find the optimum can vary dramatically. This makes linear registration the most unpredictable step of the chain in terms of execution time. It cannot be assured that the global optimum is found. Additional work has to be done in validating the registration accuracy, including the examination of the influence of intensity variations between intraoperative images as well as the influence of tumor resection and the presence of the opened skull versus the closed skull in the fluid-based registration.

Brain Shift Estimation in Image-Guided Neurosurgery Using 3-D Ultrasound

Intraoperative brain deformation is one of the most important causes affecting the overall accuracy of image-guided neurosurgical procedures. One option for correcting for this deformation is to acquire three-dimensional (3-D) ultrasound data during the operation and use this data to update the information provided by the preoperatively acquired MR data. For 12 patients 3-D ultrasound images have been reconstructed from freehand sweeps acquired during neurosurgical procedures. Ultrasound data acquired prior to and after opening the dura, but prior to surgery, have been quantitatively compared to the preoperatively acquired MR data to estimate the rigid component of brain shift at the first stages of surgery. Prior to opening the dura the average brain shift measured was 3.0 mm parallel to the direction of gravity, with a maximum of 7.5 mm, and 3.9 mm perpendicular to the direction of gravity, with a maximum of 8.2 mm. After opening the dura the shift increased on average 0.2 mm parallel to the direction of gravity and 1.4 mm perpendicular to the direction of gravity. Brain shift can be detected by acquiring 3-D ultrasound data during image-guided neurosurgery. Therefore, it can be used as a basis for correcting image data and preoperative planning for intraoperative deformations.

Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms

Computational anatomy (CA) is the mathematical study of anatomy I in I = I(alpha) o G, an orbit under groups of diffeomorphisms (i.e., smooth invertible mappings) g in G of anatomical exemplars I(alpha) in I. The observable images are the output of medical imaging devices. There are three components that CA examines: (i) constructions of the anatomical submanifolds, (ii) comparison of the anatomical manifolds via estimation of the underlying diffeomorphisms g in G defining the shape or geometry of the anatomical manifolds, and (iii) generation of probability laws of anatomical variation P(.) on the images I for inference and disease testing within anatomical models. This paper reviews recent advances in these three areas applied to shape, growth, and atrophy.

Capturing intraoperative deformations: research experience at Brigham and Women's Hospital

During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.

Tissue deformation and shape models in image-guided interventions: a discussion paper

This paper promotes the concept of active models in image-guided interventions. We outline the limitations of the rigid body assumption in image-guided interventions and describe how intraoperative imaging provides a rich source of information on spatial location of anatomical structures and therapy devices, allowing a preoperative plan to be updated during an intervention. Soft tissue deformation and variation from an atlas to a particular individual can both be determined using non-rigid registration. Established methods using free-form deformations have a very large number of degrees of freedom. Three examples of deformable models--motion models, biomechanical models and statistical shape models--are used to illustrate how prior information can be used to restrict the number of degrees of freedom of the registration algorithm and thus provide active models for image-guided interventions. We provide preliminary results from applications for each type of model.

Strategies for brain shift evaluation

For the analysis of the brain shift phenomenon different strategies were applied. In 32 glioma cases pre- and intraoperative MR datasets were acquired in order to evaluate the maximum displacement of the brain surface and the deep tumor margin. After rigid registration using the software of the neuronavigation system, a direct comparison was made with 2D- and 3D visualizations. As a result, a great variability of the brain shift was observed ranging up to 24 mm for cortical displacement and exceeding 3 mm for the deep tumor margin in 66% of all cases. Following intraoperative imaging the neuronavigation system was updated in eight cases providing reliable guidance. For a more comprehensive analysis a voxel-based nonlinear registration was applied. Aiming at improved speed of alignment we performed all interpolation operations with 3D texture mapping based on OpenGL functions supported in graphics hardware. Further acceleration was achieved with an adaptive refinement of the underlying control point grid focusing on the main deformation areas. For a quick overview the registered datasets were evaluated with different 3D visualization approaches. Finally, the results were compared to the initial measurements contributing to a better understanding of the brain shift phenomenon. Overall, the experiments clearly demonstrate that deformations of the brain surface and deeper brain structures are uncorrelated.

Remote computing environment compensating for brain shift

OBJECTIVE

Anatomical and functional image data become invalid during an operation due to brain shift. Compensation is achieved by using intraoperative imaging to update anatomical information. To accelerate the registration and visualization of pre- and intraoperative image data, the presented work focuses on remote computing capabilities. The underlying framework efficiently combines local desktop computers and remote high-end graphics workstations exploiting expensive hardware.

METHODS

By performing all computations on the remote computer, the MR volumes are rigidly aligned via voxel-based registration. Using graphics hardware for acceleration, all interpolation operations are performed with 3D texture-mapping hardware. A new approach then transforms functional markers from preoperative measurements to the intraoperative situation using an automatic tracking algorithm to identify corresponding sulci. Communicating Java viewers are suggested for analyzing the results interactively on a local computer, with all calculations being performed exclusively on the remote computer.

RESULTS

The suggested approach was successfully applied in 5 cases using MR data containing functional markers of MEG and fMRI measurements identifying eloquent brain areas. Remote large-scale graphics hardware was thereby efficiently made available for fast registration and interactive direct volume rendering in neurosurgery.

CONCLUSION

Overall, the presented framework demonstrates efficient access of expensive high-end hardware remotely controlled by thin clients, and further emphasizes the need to compensate for brain shift in functional neuronavigation.

Surgical navigation in the open MRI

The introduction of MRI into neurosurgery has opened multiple avenues, but also introduced new challenges. The open-configuration intraoperative MRI installed at the Brigham and Women's Hospital in 1996 has been used for more than 500 open craniotomies and beyond 100 biopsies. Furthermore the versatile applicability, employing the same principles, is evident by its frequent use in other areas of the body. However, while intraoperative scanning in the SignaSP yielded unprecedented imaging during neurosurgical procedures their usage for navigation proved bulky and unhandy. To be fully integrated into the procedure, acquisition and display of intraoperative data have to be dynamic and primarily driven by the surgeon performing the procedure. To use the benefits of computer-assisted navigation systems together with immediate availability of intraoperative imaging we developed a software package. This "3D Slicer" has been used routinely for biopsies and open craniotomies. The system is stable and reliable. Pre- and intraoperative data can be visualized to plan and perform surgery, as well as to accommodate for intraoperative deformations, "brain shift", by providing online data acquisition.

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.

On the metrics and euler-lagrange equations of computational anatomy

This paper reviews literature, current concepts and approaches in computational anatomy (CA). The model of CA is a Grenander deformable template, an orbit generated from a template under groups of diffeomorphisms. The metric space of all anatomical images is constructed from the geodesic connecting one anatomical structure to another in the orbit. The variational problems specifying these metrics are reviewed along with their associated Euler-Lagrange equations. The Euler equations of motion derived by Arnold for the geodesics in the group of divergence-free volume-preserving diffeomorphisms of incompressible fluids are generalized for the larger group of diffeomorphisms used in CA with nonconstant Jacobians. Metrics that accommodate photometric variation are described extending the anatomical model to incorporate the construction of neoplasm. Metrics on landmarked shapes are reviewed as well as Joshi's diffeomorphism metrics, Bookstein's thin-plate spline approximate-metrics, and Kendall's affine invariant metrics. We conclude by showing recent experimental results from the Toga & Thompson group in growth, the Van Essen group in macaque and human cortex mapping, and the Csernansky group in hippocampus mapping for neuropsychiatric studies in aging and schizophrenia.

Computation and visualization of three-dimensional soft tissue motion in the orbit

This work presents a method to measure the soft tissue motion in three dimensions in the orbit during gaze. It has been shown that two-dimensional (2-D) quantification of soft tissue motion in the orbit is effective in the study of orbital anatomy and motion disorders. However, soft tissue motion is a three-dimensional (3-D) phenomenon and part of the kinematics is lost in any 2-D measurement. Therefore, T1-weighted magnetic resonance (MR) imaging volume sequences are acquired during gaze and soft tissue motion is quantified using a generalization of the Lucas and Kanade optical flow algorithm to three dimensions. New techniques have been developed for visualizing the 3-D flow field as a series of color-texture mapped 2-D slices or as a combination of volume rendering for display of the anatomy and scintillation rendering for the display of the motion field. We have studied the performance of the algorithm on four-dimensional volume sequences of synthetic motion, simulated motion of a static object imaged by MR, an MR-imaged rotating object and MR-imaged motion in the human orbit during gaze. The accuracy of the analysis is sufficient to characterize motion in the orbit and scintillation rendering is an effective visualization technique for 3-D motion in the orbit.

Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model

We present a new algorithm for the nonrigid registration of three-dimensional magnetic resonance (MR) intraoperative image sequences showing brain shift. The algorithm tracks key surfaces of objects (cortical surface and the lateral ventricles) in the image sequence using a deformable surface matching algorithm. The volumetric deformation field of the objects is then inferred from the displacements at the boundary surfaces using a linear elastic biomechanical finite-element model. Two experiments on synthetic image sequences are presented, as well as an initial experiment on intraoperative MR images showing brain shift. The results of the registration algorithm show a good correlation of the internal brain structures after deformation, and a good capability of measuring surface as well as subsurface shift. We measured distances between landmarks in the deformed initial image and the corresponding landmarks in the target scan. Cortical surface shifts of up to 10 mm and subsurface shifts of up to 6 mm were recovered with an accuracy of 1 mm or less and 3 mm or less respectively.

Intraoperative compensation for brain shift

BACKGROUND

Tumor removal, brain swelling, the use of brain retractors, and cerebrospinal-fluid drainage all result in an intraoperative brain deformation that is known as brain shift. Thus, neuronavigation systems relying on preoperative image data have a decreasing accuracy during the surgical procedure. Intraoperative image data represent the correct anatomic situation, so their use may compensate for the effects of brain shift.

METHODS

In a series of 16 brain tumor patients, we used intraoperative magnetic resonance (MR) imaging to obtain 3-D data, which were then transferred to the microscope-based neuronavigation system. With the help of bone fiducial markers these images were registered intraoperatively, updating the neuronavigation system.

RESULTS

In all patients the updating of the neuronavigation system with the intraoperative MR data was successful. It led to reliable neuronavigation with high accuracy; the mean registration error of the update procedure in all patients was 1.1 mm. The updating procedure added about 15 minutes to the operation time. In all patients the area suggestive of remaining tumor was reached and the additional tumor could be resected, resulting in a complete tumor removal in 14 patients. In the remaining patients extension of the tumor into eloquent brain areas prevented a complete excision.

CONCLUSIONS

The update of a neuronavigation system with intraoperative MR images reliably compensates for the effects of brain shift. This method allows completion of tumor removal in some difficult brain tumors.

Serial intraoperative magnetic resonance imaging of brain shift

OBJECTIVE

A major shortcoming of image-guided navigational systems is the use of preoperatively acquired image data, which does not account for intraoperative changes in brain morphology. The occurrence of these surgically induced volumetric deformations ("brain shift") has been well established. Maximal measurements for surface and midline shifts have been reported. There has been no detailed analysis, however, of the changes that occur during surgery. The use of intraoperative magnetic resonance imaging provides a unique opportunity to obtain serial image data and characterize the time course of brain deformations during surgery.

METHODS

The vertically open intraoperative magnetic resonance imaging system (SignaSP, 0.5 T; GE Medical Systems, Milwaukee, WI) permits access to the surgical field and allows multiple intraoperative image updates without the need to move the patient. We developed volumetric display software (the 3D Slicer) that allows quantitative analysis of the degree and direction of brain shift. For 25 patients, four or more intraoperative volumetric image acquisitions were extensively evaluated.

RESULTS

Serial acquisitions allow comprehensive sequential descriptions of the direction and magnitude of intraoperative deformations. Brain shift occurs at various surgical stages and in different regions. Surface shift occurs throughout surgery and is mainly attributable to gravity. Subsurface shift occurs during resection and involves collapse of the resection cavity and intraparenchymal changes that are difficult to model.

CONCLUSION

Brain shift is a continuous dynamic process that evolves differently in distinct brain regions. Therefore, only serial imaging or continuous data acquisition can provide consistently accurate image guidance. Furthermore, only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.