Updated neuroimaging using intraoperative brain modeling and sparse data

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.

Neck tumor dissection improved with 3-dimensional ultrasound image guidance: technical case report

BACKGROUND AND IMPORTANCE

Three-dimensional ultrasound navigation has been performed to assist in resection of cranial and spinal tumors, but to the best of our knowledge, no one has described the use of real-time 3-dimensional ultrasound navigation in the resection of neck tumors beyond biopsy.

CLINICAL PRESENTATION

This case report describes the use of 3-dimensional ultrasonic navigation in assisting with resection of a large neck paraganglioma. The 3-dimensional ultrasonic navigation improved real-time visualization of the carotid arteries, the trachea, and other vital structures.

CONCLUSION

The use of 3-dimensional ultrasound navigation should be considered in aiding resection of large neck tumors because it can allow more efficient and safer tumor resection.

An optimized system for interventional magnetic resonance imaging-guided stereotactic surgery: preliminary evaluation of targeting accuracy

BACKGROUND

Deep brain stimulation electrode placement with interventional magnetic resonance imaging (MRI) has previously been reported using a commercially available skull-mounted aiming device (Medtronic Nexframe MR) and native MRI scanner software. This first-generation method has technical limitations that are inherent to the hardware and software used. A novel system (SurgiVision ClearPoint) consisting of an aiming device (SMARTFrame) and software has been developed specifically for interventional MRI, including deep brain stimulation.

OBJECTIVE

To report a series of phantom and cadaver tests performed to determine the capability, preliminary accuracy, and workflow of the system.

METHODS

Eighteen experiments using a water phantom were used to determine the predictive accuracy of the software. Sixteen experiments using a gelatin-filled skull phantom were used to determine targeting accuracy of the aiming device. Six procedures in 3 cadaver heads were performed to compare the workflow and accuracy of ClearPoint with Nexframe MR.

RESULTS

Software prediction experiments showed an average error of 0.9 ± 0.5 mm in magnitude in pitch and roll (mean pitch error, -0.2 ± 0.7 mm; mean roll error, 0.2 ± 0.7 mm) and an average error of 0.7 ± 0.3 mm in X-Y translation with a slight anterior (0.5 ± 0.3 mm) and lateral (0.4 ± 0.3 mm) bias. Targeting accuracy experiments showed an average radial error of 0.5 ± 0.3 mm. Cadaver experiments showed a radial error of 0.2 ± 0.1 mm with the ClearPoint system (average procedure time, 88 ± 14 minutes) vs 0.6 ± 0.2 mm with the Nexframe MR (average procedure time, 92 ± 12 minutes).

CONCLUSION

This novel system provides the submillimetric accuracy required for stereotactic interventions, including deep brain stimulation placement. It also overcomes technical limitations inherent in the first-generation interventional MRI system.

A fast and efficient method to compensate for brain shift for tumor resection therapies measured between preoperative and postoperative tomograms

In this paper, an efficient paradigm is presented to correct for brain shift during tumor resection therapies. For this study, high resolution preoperative (pre-op) and postoperative (post-op) MR images were acquired for eight in vivo patients, and surface/subsurface shift was identified by manual identification of homologous points between the pre-op and immediate post-op tomograms. Cortical surface deformation data were then used to drive an inverse problem framework. The manually identified subsurface deformations served as a comparison toward validation. The proposed framework recaptured 85% of the mean subsurface shift. This translated to a subsurface shift error of 0.4 +/- 0.4 mm for a measured shift of 3.1 +/- 0.6 mm. The patient's pre-op tomograms were also deformed volumetrically using displacements predicted by the model. Results presented allow a preliminary evaluation of correction both quantitatively and visually. While intraoperative (intra-op) MR imaging data would be optimal, the extent of shift measured from pre- to post-op MR was comparable to clinical conditions. This study demonstrates the accuracy of the proposed framework in predicting full-volume displacements from sparse shift measurements. It also shows that the proposed framework can be extended and used to update pre-op images on a time scale that is compatible with surgery.

Image guidance and neuromonitoring in neurosurgery

INTRODUCTION

The localization of tumors and epileptogenic foci within the somatosensory or language cortex of the brain of a child poses unique neurosurgical challenges. In the past, lesions in these regions were not treated aggressively for fear of inducing neurological deficits. As a result, while function may have been preserved, the underlying disease may not have been optimally treated, and repeat neurosurgical procedures were frequently required. Today, with the advent of preoperative brain mapping, image guidance or neuronavigation, and intraoperative monitoring, peri-Rolandic and language cortex lesions can be approached directly and definitively with a high degree of confidence that neurosurgical function will be maintained.

METHODS AND RESULTS

The preoperative brain maps can now be achieved with magnetic resonance imaging (MRI), functional MRI, magnetoencephalography, and diffusion tensor imaging. Image guidance systems have improved significantly and include the use of the intraoperative MRI. Somatosensory, motor, and brainstem auditory-evoked potentials are used as standard neuromonitoring techniques in many centers around the world. Added to this now is the use of continuous train-of-five monitoring of the integrity of the corticospinal tract while operating in the peri-Rolandic region.

CONCLUSION

We are in an era where continued advancements can be expected in mapping additional pathways such as visual, memory, and hearing pathways. With these new advances, neurosurgeons can expect to significantly improve their surgical outcomes further.

Semiautomatic registration of pre- and postbrain tumor resection laser range data: method and validation

This paper presents a semiautomatic method for the registration of images acquired during surgery with a tracked laser range scanner (LRS). This method, which relies on the registration of vessels that can be visualized in the pre- and the postresection images, is a component of a larger system designed to compute brain shift that occurs during tumor resection cases. Because very large differences between pre- and postresection images are typically observed, the development of fully automatic methods to register these images is difficult. The method presented herein is semiautomatic and requires only the identification of a number of points along the length of the vessels. Vessel segments joining these points are then automatically identified using an optimal path finding algorithm that relies on intensity features extracted from the images. Once vessels are identified, they are registered using a robust point-based nonrigid registration algorithm. The transformation computed with the vessels is then applied to the entire image. This permits establishment of a complete correspondence between the pre- and post-3-D LRS data. Experiments show that the method is robust to operator errors in localizing homologous points and a quantitative evaluation performed on ten surgical cases shows submillimetric registration accuracy.

Is the image guidance of ultrasonography beneficial for neurosurgical routine?

BACKGROUND

Intraoperative US has been widely used in neurosurgical procedures. However, images are often difficult to read. In the present study, we evaluate whether the image guidance of ultrasonography is helpful for the interpretation of US scans.

METHODS

Twenty-nine patients with tumor were operated on with the aid of intraoperative US from January to June 2005. Image-guided sonography was used in 13 cases and nonnavigated US technology in the remaining cases. We compared the 2 technologies retrospectively.

RESULTS

Although image quality was good in most cases, orientation remained difficult in 8 of the 16 patients where conventional sonography was used. With the aid of image fusion for navigated sonography, the orientation was judged superior to nonnavigated US.

CONCLUSION

In our experience, integration of the US into the navigation system facilitates anatomical understanding. Thus, we feel that this technology is beneficial for neurosurgical routine.

Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery

OBJECTIVE

The usefulness of neurosurgical navigation with current visualizations is seriously compromised by brain shift, which inevitably occurs during the course of the operation, significantly degrading the precise alignment between the pre-operative MR data and the intra-operative shape of the brain. Our objectives were (i) to evaluate the feasibility of non-rigid registration that compensates for the brain deformations within the time constraints imposed by neurosurgery, and (ii) to create augmented reality visualizations of critical structural and functional brain regions during neurosurgery using pre-operatively acquired fMRI and DT-MRI.

MATERIALS AND METHODS

Eleven consecutive patients with supratentorial gliomas were included in our study. All underwent surgery at our intra-operative MR imaging-guided therapy facility and have tumors in eloquent brain areas (e.g. precentral gyrus and cortico-spinal tract). Functional MRI and DT-MRI, together with MPRAGE and T2w structural MRI were acquired at 3 T prior to surgery. SPGR and T2w images were acquired with a 0.5 T magnet during each procedure. Quantitative assessment of the alignment accuracy was carried out and compared with current state-of-the-art systems based only on rigid registration.

RESULTS

Alignment between pre-operative and intra-operative datasets was successfully carried out during surgery for all patients. Overall, the mean residual displacement remaining after non-rigid registration was 1.82 mm. There is a statistically significant improvement in alignment accuracy utilizing our non-rigid registration in comparison to the currently used technology (p<0.001).

CONCLUSIONS

We were able to achieve intra-operative rigid and non-rigid registration of (1) pre-operative structural MRI with intra-operative T1w MRI; (2) pre-operative fMRI with intra-operative T1w MRI, and (3) pre-operative DT-MRI with intra-operative T1w MRI. The registration algorithms as implemented were sufficiently robust and rapid to meet the hard real-time constraints of intra-operative surgical decision making. The validation experiments demonstrate that we can accurately compensate for the deformation of the brain and thus can construct an augmented reality visualization to aid the surgeon.

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.

Modality independent elastography (MIE): a new approach to elasticity imaging

The correlation between tissue stiffness and health is an accepted form of organ disease assessment. As a result, there has been a significant amount of interest in developing methods to image elasticity parameters (i.e., elastography). The modality independent elastography (MIE) method combines a nonlinear optimization framework, computer models of soft-tissue deformation, and standard measures of image similarity to reconstruct elastic property distributions within soft tissue. In this paper, simulation results demonstrate successful elasticity image reconstructions in breast cross-sectional images acquired from magnetic resonance (MR) imaging. Results from phantom experiments illustrate its modality independence by reconstructing elasticity images of the same phantom in both MR and computed tomographic imaging units. Additional results regarding the performance of a new multigrid strategy to MIE and the implementation of a parallel architecture are also presented.