A GPU-based approach to compute the brain shift using a fully nonlinear biomechanical model

2015 ◽  
Author(s):  
Ye Tian ◽  
Xukun Shen
Keyword(s):  
Biomechanical Model ◽  
Brain Shift ◽  
Fully Nonlinear ◽  
The Brain

scholarly journals A Simple Method to Avoid Brain Shift during Neuronavigation: Technical Note

2020 ◽  
Author(s):  
Jair Leopoldo Raso
Keyword(s):  
Dura Mater ◽  
Brain Area ◽  
Conventional Technique ◽  
Technical Note ◽  
Cortical Surface ◽  
Brain Shift ◽  
Simple Method ◽  
Cortex Area ◽  
Neuronavigation System ◽  
The Brain

Abstract Introduction The precise identification of anatomical structures and lesions in the brain is the main objective of neuronavigation systems. Brain shift, displacement of the brain after opening the cisterns and draining cerebrospinal fluid, is one of the limitations of such systems. Objective To describe a simple method to avoid brain shift in craniotomies for subcortical lesions. Method We used the surgical technique hereby described in five patients with subcortical neoplasms. We performed the neuronavigation-guided craniotomies with the conventional technique. After opening the dura and exposing the cortical surface, we placed two or three arachnoid anchoring sutures to the dura mater, close to the edges of the exposed cortical surface. We placed these anchoring sutures under microscopy, using a 6–0 mononylon wire. With this technique, the cortex surface was kept close to the dura mater, minimizing its displacement during the approach to the subcortical lesion. In these five cases we operated, the cortical surface remained close to the dura, anchored by the arachnoid sutures. All the lesions were located with a good correlation between the handpiece tip inserted in the desired brain area and the display on the navigation system. Conclusion Arachnoid anchoring sutures to the dura mater on the edges of the cortex area exposed by craniotomy constitute a simple method to minimize brain displacement (brain-shift) in craniotomies for subcortical injuries, optimizing the use of the neuronavigation system.

Brain shift: an error factor during implantation of deep brain stimulation electrodes

2007 ◽  
Vol 107 (5) ◽  
pp. 989-997 ◽  
Author(s):  
Yasushi Miyagi ◽  
Fumio Shima ◽  
Tomio Sasaki
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Brain Shift ◽  
Mr Images ◽  
Implanted Electrodes ◽  
Error Factor ◽  
Bilateral Surgery ◽  
Second Procedure ◽  
The Brain ◽  
Deep Brain

Object The goal of this study was to focus on the tendency of brain shift during stereotactic neurosurgery and the shift's impact on the unilateral and bilateral implantation of electrodes for deep brain stimulation (DBS). Methods Eight unilateral and 10 bilateral DBS electrodes at 10 nuclei ventrales intermedii and 18 subthalamic nuclei were implanted in patients at Kaizuka Hospital with the aid of magnetic resonance (MR) imaging–guided and microelectrode-guided methods. Brain shift was assessed as changes in the 3D coordinates of the anterior and posterior commissures (AC and PC) with MR images before and immediately after the implantation surgery. The positions of the implanted electrodes, based on the midcommissural point and AC–PC line, were measured both on x-ray films (virtual position) during surgery and the postoperative MR images (actual position) obtained on the 7th day postoperatively. Results Contralateral and posterior shift of the AC and PC were the characteristics of unilateral and bilateral procedures, respectively. The authors suggest the following. 1) The first unilateral procedure elicits a unilateral air invasion, resulting in a contralateral brain shift. 2) During the second procedure in the bilateral surgery, the contralateral shift is reset to the midline and, at the same time, the anteroposterior support by the contralateral hemisphere against gravity is lost due to a bilateral air invasion, resulting in a significant posterior (caudal) shift. Conclusions To note the tendency of the brain to shift is very important for accurate implantation of a DBS electrode or high frequency thermocoagulation, as well as for the prediction of therapeutic and adverse effects of stereotactic surgery.

Analysis and Visualization of the Brain Shift Phenomenon in Neurosurgery

1999 ◽  
pp. 285-289 ◽  
Author(s):  
C. Lürig ◽  
P. Hastreiter ◽  
C. Nimsky ◽  
T. Ertl
Keyword(s):  
Brain Shift ◽  
The Brain

scholarly journals Image Updating for Brain Shift Compensation During Resection

2017 ◽  
Vol 14 (4) ◽  
pp. 402-411 ◽  
Author(s):  
Xiaoyao Fan ◽  
David W Roberts ◽  
Jonathan D Olson ◽  
Songbai Ji ◽  
Timothy J Schaewe ◽  
...  
Keyword(s):  
Biomechanical Model ◽  
Partial Resection ◽  
Computational Time ◽  
Brain Shift ◽  
Registration Errors ◽  
Brain Deformation ◽  
Preoperative Magnetic Resonance ◽  
Surgical Field ◽  
Image Pairs ◽  
Dural Opening

Abstract BACKGROUND In open-cranial neurosurgery, preoperative magnetic resonance (pMR) images are typically coregistered for intraoperative guidance. Their accuracy can be significantly degraded by intraoperative brain deformation, especially when resection is involved. OBJECTIVE To produce model updated MR (uMR) images to compensate for brain shift that occurred during resection, and evaluate the performance of the image-updating process in terms of accuracy and computational efficiency. METHODS In 14 resection cases, intraoperative stereovision image pairs were acquired after dural opening and during resection to generate displacement maps of the surgical field. These data were assimilated by a biomechanical model to create uMR volumes of the evolving surgical field. A tracked stylus provided independent measurements of feature locations to quantify target registration errors (TREs) in the original coregistered pMR and uMR as surgery progressed. RESULTS Updated MR TREs were 1.66 ± 0.27 and 1.92 ± 0.49 mm in the 14 cases after dural opening and after partial resection, respectively, compared to 8.48 ± 3.74 and 8.77 ± 4.61 mm for pMR, respectively. The overall computational time for generating uMRs after partial resection was less than 10 min. CONCLUSION We have developed an image-updating system to compensate for brain deformation during resection using a computational model with data assimilation of displacements measured with intraoperative stereovision imaging that maintains TREs less than 2 mm on average.

Registration techniques for the analysis of the brain shift in neurosurgery

2000 ◽  
Vol 24 (3) ◽  
pp. 385-389 ◽  
Author(s):  
P Hastreiter ◽  
C Rezk-Salama ◽  
C Nimsky ◽  
C Lürig ◽  
G Greiner ◽  
...  
Keyword(s):  
Brain Shift ◽  
The Brain

scholarly journals Intraoperative image updating for brain shift following dural opening

2016 ◽  
Vol 126 (6) ◽  
pp. 1924-1933 ◽  
Author(s):  
Xiaoyao Fan ◽  
David W. Roberts ◽  
Timothy J. Schaewe ◽  
Songbai Ji ◽  
Leslie H. Holton ◽  
...  
Keyword(s):  
Biomechanical Model ◽  
Magnetic Resonance Images ◽  
Computational Time ◽  
Average Error ◽  
Cortical Surface ◽  
Brain Shift ◽  
Surgical Workflow ◽  
Brain Deformation ◽  
Time Required ◽  
Dural Opening

OBJECTIVEPreoperative 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.METHODSIn 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.RESULTSThe 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.CONCLUSIONSThis 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.

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