Coregistered ultrasound as a neurosurgical guide

Utilizing Intraoperative Navigated 3D Color Doppler Ultrasound in Glioma Surgery

Background

In glioma surgery, the patient’s outcome is dramatically influenced by the extent of resection and residual tumor volume. To facilitate safe resection, neuronavigational systems are routinely used. However, due to brain shift, accuracy decreases with the course of the surgery. Intraoperative ultrasound has proved to provide excellent live imaging, which may be integrated into the navigational procedure. Here we describe the visualization of vascular landmarks and their shift during tumor resection using intraoperative navigated 3D color Doppler ultrasound (3D iUS color Doppler).

Methods

Six patients suffering from glial tumors located in the temporal lobe were included in this study. Intraoperative computed tomography was used for registration. Datasets of 3D iUS color Doppler were generated before dural opening and after tumor resection, and the vascular tree was segmented manually. In each dataset, one to four landmarks were identified, compared to the preoperative MRI, and the Euclidean distance was calculated.

Results

Pre-resectional mean Euclidean distance of the marked points was 4.1 ± 1.3 mm (mean ± SD), ranging from 2.6 to 6.0 mm. Post-resectional mean Euclidean distance was 4.7. ± 1.0 mm, ranging from 2.9 to 6.0 mm.

Conclusion

3D iUS color Doppler allows estimation of brain shift intraoperatively, thus increasing patient safety. Future implementation of the reconstructed vessel tree into the navigational setup might allow navigational updating with further consecutive increasement of accuracy.

A framework for correcting brain retraction based on an eXtended Finite Element Method using a laser range scanner

BACKGROUND

Brain retraction causes great distortion that limits the accuracy of an image-guided neurosurgery system that uses preoperative images. Therefore, brain retraction correction is an important intraoperative clinical application.

METHODS

We used a linear elastic biomechanical model, which deforms based on the eXtended Finite Element Method (XFEM) within a framework for brain retraction correction. In particular, a laser range scanner was introduced to obtain a surface point cloud of the exposed surgical field including retractors inserted into the brain. A brain retraction surface tracking algorithm converted these point clouds into boundary conditions applied to XFEM modeling that drive brain deformation. To test the framework, we performed a brain phantom experiment involving the retraction of tissue. Pairs of the modified Hausdorff distance between Canny edges extracted from model-updated images, pre-retraction, and post-retraction CT images were compared to evaluate the morphological alignment of our framework. Furthermore, the measured displacements of beads embedded in the brain phantom and the predicted ones were compared to evaluate numerical performance.

RESULTS

The modified Hausdorff distance of 19 pairs of images decreased from 1.10 to 0.76 mm. The forecast error of 23 stainless steel beads in the phantom was between 0 and 1.73 mm (mean 1.19 mm). The correction accuracy varied between 52.8 and 100 % (mean 81.4 %).

CONCLUSIONS

The results demonstrate that the brain retraction compensation can be incorporated intraoperatively into the model-updating process in image-guided neurosurgery systems.

Combining multiple true 3D ultrasound image volumes through re-registration and rasterization

We present an accurate and efficient technique to combine and rasterize multiple 3D ultrasound (3DUS) image volumes originally presented in spherical coordinates into a single, 3D Cartesian image that uniformly samples the total field of view. To ensure the consistency of merged image content in overlapping regions, image re-registration was performed by maximizing mutual information (MI). The technique was applied to 22 3DUS image volumes obtained during five neurosurgical patient cases. The computational cost of the approach increases linearly with the number of images involved (average time to combine and rasterize one pair of 3DUS images was 1.5 sec). Interpolation was approximately 20% more accurate in overlapping regions when reregistration was performed before rasterization and minimized feature loss and/or blurring that was evident without re-registration. In addition, we report the average translational (35.2 mm) and rotational (38.5 degrees) capture ranges for the MI re-registration of two volumetric 3DUS images. The technique is applicable in any clinical application in which volumetric true 3DUS is acquired.

Estimation of brain deformation for volumetric image updating in protoporphyrin IX fluorescence-guided resection

INTRODUCTION

Fluorescence-guided resection (FGR) of brain tumors is an intuitive, practical and emerging technology for visually delineating neoplastic tissue exposed intraoperatively. Image guidance is the standard technique for producing 3-dimensional spatially coregistered information for surgical decision making. Both technologies together are synergistic: the former detects surface fluorescence as a biomarker of the current surgical margin while the latter shows coregistered volumetric neuroanatomy but can be degraded by intraoperative brain shift. We present the implementation of deformation modeling for brain shift compensation in protoporphyrin IX FGR, integrating these two sources of information for maximum surgical benefit.

METHODS

Two patients underwent FGR coregistered with conventional image guidance. Histopathological analysis, intraoperative fluorescence and image space coordinates were recorded for biopsy specimens acquired during surgery. A biomechanical brain deformation model driven by intraoperative ultrasound data was used to generate updated MR images.

RESULTS

Combined use of fluorescence signatures and updated MR image information showed substantially improved accuracy compared to fluorescence or the original (i.e., nonupdated) MR images, detecting only true positives and true negatives, and no instances of false positives or false negatives.

CONCLUSION

Implementation of brain deformation modeling in FGR shows promise for increasing the accuracy of neurosurgical guidance in the delineation and resection of brain tumors.

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.

Coregistration accuracy and detection of brain shift using intraoperative sononavigation during resection of hemispheric tumors

OBJECTIVE

Sononavigation, which combines real-time anatomic ultrasound data with neuronavigation techniques, is a potentially valuable adjunct during the surgical excision of brain tumors.

METHODS

In this study, we report our preliminary observations using this technology on 58 adult patients harboring hemispheric tumors. Data regarding coregistration accuracy was collected from various landmarks that typically do not shift as well as from tumor boundaries and the cortical surface. In a subset of patients, we evaluated the extent and direction of postresection brain displacement and its relationship with patient age, tumor histology, tumor volume, and use of mannitol.

RESULTS

For all structures excluding the cortex, average coregistration accuracy measurements between ultrasound and preoperatively acquired magnetic resonance imaging scans were within the range of 2 mm. The most accurate alignments were obtained with the choroid plexus and the falx, and the least reliable structure in terms of coregistration accuracy was the cortical surface.

CONCLUSION

Sononavigation provides real-time information during tumor removal in alignment with the preoperative magnetic resonance imaging scans, thus enabling the surgeon to detect intraoperative hemorrhage, cyst drainage, and tumor resection, and it allows for calculation of brain shift during the use of standard navigation techniques.

Intra-operative image updating

Intraoperative brain shift and deformation pose challenges for image-guided surgery. One strategy to address these problems utilizes computational modeling coupled with intraoperatively acquired information from efficient and economical sources such as ultrasound and the optics of the operating microscope. Calibration algorithms for the accurate integration of these sparse data sources have been implemented. Assessment has been performed in both phantom and pig brain models, and accuracy better than 2 mm has been achieved. Methods of incorporating these data into the computational model are being developed.

Three-dimensional intraoperative ultrasound of vascular malformations and supratentorial tumors

The benefits and limits of a magnetic sensor-based 3-dimensional (3D) intraoperative ultrasound technique during surgery of vascular malformations and supratentorial tumors were evaluated. Twenty patients with 11 vascular malformations and 9 supratentorial tumors undergoing microsurgical resection or clipping were investigated with an interactive magnetic sensor data acquisition system allowing freehand scanning. An ultrasound probe with a mounted sensor was used after craniotomies to localize lesions, outline tumors or malformation margins, and identify supplying vessels. A 3D data set was obtained allowing reformation of multiple slices in all 3 planes and comparison to 2-dimensional (2D) intraoperative ultrasound images. Off-line gray-scale segmentation analysis allowed differentiation between tissue with different echogenicities. Color-coded information about blood flow was extracted from the images with a reconstruction algorithm. This allowed photorealistic surface displays of perfused tissue, tumor, and surrounding vessels. Three-dimensional intraoperative ultrasound data acquisition was obtained within 5 minutes. Off-line analysis and reconstruction time depends on the type of imaging display and can take up to 30 minutes. The spatial relation between aneurysm sac and surrounding vessels or the skull base could be enhanced in 3 out of 6 aneurysms with 3D intraoperative ultrasound. Perforating arteries were visible in 3 cases only by using 3D imaging. 3D ultrasound provides a promising imaging technique, offering the neurosurgeon an intraoperative spatial orientation of the lesion and its vascular relationships. Thereby, it may improve safety of surgery and understanding of 2D ultrasound images.

Ultrasound imaging in three and four dimensions

Three-dimensional (3D) reconstruction of ultrasound images was first demonstrated nearly 15 years ago, but only now is becoming a clinical reality. In the meantime, methods for 3D reconstruction of CT and MRI images have achieved an advanced state of development, and 3D imaging with these modalities has been applied widely in clinical practice. 3D applications in ultrasound have lagged behind CT and MRI, because ultrasound data is much more difficult to render in 3D, for a variety of technical reasons, than either CT or MRI data. Only in the past few years has the computing power of ultrasound equipment reached a level adequate enough for the complex signal processing tasks needed to render ultrasound data in three dimensions. At this point in time, the clinical application of 3D ultrasound is likely to advance rapidly, as improved 3D rendering technology becomes more widely available. This article is a review of the present status of 3D ultrasound imaging. It begins by comparing the characteristics of CT, MRI, and ultrasound image data that either make these data amenable or not amenable to 3D reconstruction. The article then considers the technical features involved with acquiring an ultrasound 3D data set and the mechanisms for reconstructing the images. Finally, the article reviews the literature that is available regarding clinical application of 3D ultrasound in obstetrics, ultrasound, the abdomen, and blood vessels.