Strategies for brain shift evaluation

Hastreiter, Peter; Rezk‐Salama, Christof; Soza, Grzegorz; Bauer, Michael; Greiner, Günther; Fahlbusch, Rudolf; Ganslandt, Oliver; Nimsky, Christopher

doi:10.1016/j.media.2004.02.001

Cited by 135 publications

(98 citation statements)

References 86 publications

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“…The accuracy of the registration was evaluated using manually identified landmarks and resulted in a mean error of less than 1.6 mm. A second image based registration technique was published by Hastreiter et al (2004). After having characterized the brain deformations, they used a non-linear registration method based on mutual information to register pre-operative and intra-operative data.…”

Section: Intraoperative Mr Imagingmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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The displacement and deformation of brain tissue is a major source of error in image-guided neurosurgery systems. We have designed and implemented a method to detect and correct brain shift using pre-operative MR images and intraoperative Doppler ultrasound data and present its validation with both real and simulated data. The algorithm uses segmented vessels from both modalities, and estimates the deformation using a modified version of the iterative closest point (ICP) algorithm. We use the least trimmed squares (LTS) to reduce the number of outliers in the point matching procedure. These points are used to drive a thin-plate spline transform to achieve non-linear registration. Validation was completed in two parts. First, the technique was tested and validated using realistic simulations where the results were compared to the known deformation. The registration technique recovered 75% of the deformation in the region of interest accounting for deformations as large as 20 mm. Second, we performed a PVA-cryogel phantom study where both MR and ultrasound images of the phantom were obtained for three different deformations. The registration results based on MR data were used as a gold standard to evaluate the performance of the ultrasound based registration. On average, deformations of 7.5 mm magnitude were corrected to within 1.6 mm for the ultrasound based registration and 1.07 mm for the MR based registration.

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Section: Intraoperative Mr Imagingmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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“…Deformation of the brain during open-skull neurosurgical procedures can be a significant source of error for neuronavigation systems (Hastreiter et al, 2004). Brain shift in human surgeries increases with time, so MER trajectories obtained early in the procedure are more likely to align with atlases customized to the preoperative MRI/CT scans.…”

Section: Discussionmentioning

confidence: 99%

Stereotactic neurosurgical planning, recording, and visualization for deep brain stimulation in non-human primates

Miocinovic¹,

Zhang²,

Xu³

et al. 2007

Journal of Neuroscience Methods

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Methodologies for stereotactic neurosurgery and neurophysiological microelectrode recordings (MER) in non-human primate research typically rely on brain atlases that are not customized to the individual animal, and require paper records of MER data. To address these limitations, we developed a software tool (Cicerone) that enables simultaneous interactive 3D visualization of the neuroanatomy, neurophysiology, and neurostimulation data pertinent to deep brain stimulation (DBS) research studies in non-human primates. Cicerone allows for analysis of co-registered magnetic resonance images (MRI), computed tomography (CT) scans, 3D brain atlases, MER data, and DBS electrode(s) with predictions of the volume of tissue activated (VTA) as a function of the stimulation parameters. We used Cicerone to aid the implantation of DBS electrodes in two parkinsonian rhesus macaques, targeting the subthalamic nucleus in one monkey and the globus pallidus in the other. Cicerone correctly predicted the anatomical position of 79% and 73% of neurophysiologically defined MER sites in the two animals, respectively. In contrast, traditional 2D print atlases achieved 61% and 48% accuracy. Our experience suggests that Cicerone can improve anatomical targeting, enhance electrophysiological data visualization, and augment the design of stimulation experiments.

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“…After sampling the function D, the resulting texture coordinates on the sparse grid are used to propagate the deformation onto the whole volume using trilinear interpolation. For this purpose, the 3D Bézier function is approximated with a 3D piecewise linear model (Soza, 2005;Hastreiter et al, 2004). This approach is computationally less expensive since there is no need to process the whole 3D image voxel by voxel to obtain new intensity values which is necessary in software approaches.…”

Section: Hardware-accelerated Free-form Deformationmentioning

confidence: 99%

Correction of susceptibility artifacts in diffusion tensor data using non-linear registration

Merhof

Soza

Stadlbauer

et al. 2007

Medical Image Analysis

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Diffusion tensor imaging can be used to localize major white matter tracts within the human brain. For surgery of tumors near eloquent brain areas such as the pyramidal tract this information is of importance to achieve an optimal resection while avoiding post-operative neurological deficits. However, due to the small bandwidth of echo planar imaging, diffusion tensor images suffer from susceptibility artifacts resulting in positional shifts and distortion. As a consequence, the fiber tracts computed from echo planar imaging data are spatially distorted. We present an approach based on non-linear registration using Bézier functions to efficiently correct distortions due to susceptibility artifacts. The approach makes extensive use of graphics hardware to accelerate the non-linear registration procedure. An improvement presented in this paper is a more robust and efficient optimization strategy based on simultaneous perturbation stochastic approximation (SPSA).Since the accuracy of non-linear registration is crucial for the value of the presented correction method, two techniques were applied in order to prove the quality of the proposed framework. First, the registration accuracy was evaluated by recovering a known transformation with non-linear registration. Second, landmark-based evaluation of the registration method for anatomical and diffusion tensor data was performed. The registration was then applied to patients with lesions adjacent to the pyramidal tract in order to compensate for susceptibility artifacts. The effect of the correction on the pyramidal tract was then quantified by measuring the position of the tract before and after registration. As a result, the distortions observed in phase encoding direction were most prominent at the cortex and the brainstem. The presented approach allows correcting fiber tract distortions which is an important prerequisite when tractography data are integrated into a stereotactic setup for intra-operative guidance.

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Strategies for brain shift evaluation

Cited by 135 publications

References 86 publications

Validation of vessel-based registration for correction of brain shift

Validation of vessel-based registration for correction of brain shift

Stereotactic neurosurgical planning, recording, and visualization for deep brain stimulation in non-human primates

Correction of susceptibility artifacts in diffusion tensor data using non-linear registration

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