Cortical Surface Motion Estimation for Brain Shift Prediction

2010 ◽  
pp. 53-62 ◽  
Author(s):  
Grand Roman Joldes ◽  
Adam Wittek ◽  
Karol Miller
Keyword(s):  
Motion Estimation ◽  
Cortical Surface ◽  
Brain Shift ◽  
Surface Motion

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.

scholarly journals Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4396
Author(s):  
Li Fang ◽  
Zhen Ye ◽  
Shu Su ◽  
Jian Kang ◽  
Xiaohua Tong
Keyword(s):  
Motion Estimation ◽  
Estimation Method ◽  
Correlation Method ◽  
Image Correlation ◽  
Matching Method ◽  
Glacier Surface ◽  
Surface Motion ◽  
Alpine Regions ◽  
Intensity Images ◽  
Comparative Results

With the current extensive availability of synthetic-aperture radar (SAR) datasets with high temporal (e.g., a repeat cycle of a few or a dozen days) and spatial resolution (e.g., in the order of ∼1 m), radar remote sensing possesses an increasing potential for the monitoring of glacier surface motion thanks to the nearly weather and time-independent advantages. This paper proposes a robust subpixel frequency-based image correlation method for dense matching and integrates the improved matching into a workflow of glacier surface motion estimation using SAR intensity images with specific pre-processing and post-processing steps. The proposed matching method combines complex edge maps and local upsampling in the frequency domain for subpixel intensity tracking, which ensure the accuracy and robustness of glacier surface motion estimation. Experiments were carried out with TerraSAR-X and Sentinel-1 images covering two glacier areas in pole and alpine regions. The results of the monitoring and investigation of glacier motion validate the feasibility and reliability of the presented motion estimation method based on subpixel gradient correlation. The comparative results using both simulated and real SAR data indicate that the proposed matching method outperforms commonly used correlation-based matching methods in terms of matching accuracy and the ability to obtain correct matches.

scholarly journals Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

2021 ◽  
Vol 15 ◽  
Author(s):  
Chantel M. Charlebois ◽  
David J. Caldwell ◽  
Sumientra M. Rampersad ◽  
Andrew P. Janson ◽  
Jeffrey G. Ojemann ◽  
...  
Keyword(s):  
Computational Models ◽  
Projection Methods ◽  
Patient Specific ◽  
Clinical Effects ◽  
Cortical Surface ◽  
Brain Shift ◽  
Model Errors ◽  
Computer Interfaces ◽  
Electrode Localization

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

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.

scholarly journals Shelf Surface Motion Estimation from Repeat Satellite Imagery

2013 ◽  
Vol 9 (S7) ◽  
pp. 43
Author(s):  
Yi Liu ◽  
Yan Fei ◽  
Weian Wang
Keyword(s):  
Motion Estimation ◽  
Satellite Imagery ◽  
Surface Motion

Coregistration Accuracy and Detection of Brain Shift Using Intraoperative Sononavigation during Resection of Hemispheric Tumors

Neurosurgery ◽  
2003 ◽  
Vol 53 (3) ◽  
pp. 556-564 ◽  
Author(s):  
G. Evren Keles ◽  
Kathleen R. Lamborn ◽  
Mitchel S. Berger
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Real Time ◽  
Tumor Resection ◽  
Surgical Excision ◽  
Cortical Surface ◽  
Brain Shift ◽  
Resonance Imaging ◽  
Valuable Adjunct ◽  
Real Time Information

Abstract 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.

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