Preventing Shift from Pneumocephalus During Deep Brain Stimulation Surgery: Don't Give Up the 'Fork in the Brain'

Clinical vignette

We present the case of a patient who developed intra-operative pneumocephalus during left globus pallidus internus deep brain stimulation (DBS) placement for Parkinson's disease (PD). Microelectrode recording (MER) revealed that we were anterior and lateral to the intended target.

Clinical dilemma

Clinically, we suspected brain shift from pneumocephalus. Removal of the guide-tube for readjustment of the brain target would have resulted in the introduction of movement resulting from brain shift and from displacement from the planned trajectory.

Clinical solution

We elected to leave the guide-tube cannula in place and to pass the final DBS lead into a channel that was located posterior-medially from the center microelectrode pass.

Gap in knowledge

Surgical techniques which can be employed to minimize brain shift in the operating room setting are critical for reduction in variation of the final DBS lead placement. Pneumocephalus after dural opening is one potential cause of brain shift. The recognition that the removal of a guide-tube cannula could worsen brain shift creates an opportunity for an intraoperative team to maintain the advantage of the 'fork' in the brain provided by the initial procedure's requirement of guide-tube placement.

The Related Factors and Effect of Electrode Displacement on Motor Outcome of Subthalamic Nuclei Deep Brain Stimulation in Parkinson's Disease

BACKGROUND

Previous studies have revealed the existence of electrode displacement during subthalamic nucleus deep brain stimulation (STN-DBS). However, the effect of electrode displacement on treatment outcomes is still unclear. In this study, we aimed to analyze the related factors of electrode displacement and assess postoperative electrode displacement in relation to the motor outcomes of STN-DBS.

METHODS

A total of 88 patients aged 62.73 ± 6.35 years (55 males and 33 females) with Parkinson's disease undergoing STN-DBS, with comprehensive clinical characterization before and 1 month after surgery, were involved retrospectively and divided into a cross-incision group and cannula puncture group according to different dura opening methods. The electrode displacement, unilateral pneumocephalus volume percent (uPVP), and brain volume percent were estimated.

RESULTS

A significant anterior and lateral electrode displacement was observed among all implanted electrodes after pneumocephalus absorption (p < 0.0001). The degree of electrode displacement was positively correlated with the uPVP (p = 0.005) and smaller in females than males (p = 0.0384). Electrode displacement was negatively correlated with motor improvement following STN-DBS in both on-medication and off-medication conditions (p < 0.05). Dural puncture reduced the uPVP (p < 0.0001) and postoperative electrode displacement (p = 0.0086) compared with dural incision.

CONCLUSIONS

Electrode displacement had a negative impact on the therapeutic efficacy of STN-DBS. Opening the dura via cannula puncture is recommended to increase the accuracy of the lead implantation.

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation

Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurgeries. We generated updated magnetic resonance images (uMR) in this study to compensate for brain shifts after dural opening using a convolutional neural network (CNN). This study included 248 consecutive patients who underwent craniotomy for initial intra-axial brain tumor removal and correspondingly underwent preoperative MR (pMR) and intraoperative MR (iMR) imaging. Deep learning using CNN to compensate for brain shift was performed using the pMR as input data, and iMR obtained after dural opening as the ground truth. For the tumor center (TC) and the maximum shift position (MSP), statistical analysis using the Wilcoxon signed-rank test was performed between the target registration error (TRE) for the pMR and iMR (i.e., the actual amount of brain shift) and the TRE for the uMR and iMR (i.e., residual error after compensation). The TRE at the TC decreased from 4.14 ± 2.31 mm to 2.31 ± 1.15 mm, and the TRE at the MSP decreased from 9.61 ± 3.16 mm to 3.71 ± 1.98 mm. The Wilcoxon signed-rank test of the pMR TRE and uMR TRE yielded a p-value less than 0.0001 for both the TC and MSP. Using a CNN model, we designed and implemented a new system that compensated for brain shifts after dural opening. Learning pMR and iMR with a CNN demonstrated the possibility of correcting the brain shift after dural opening.

Mapping Resection Progress by Tool-Tip Tracking during Brain Tumor Surgery for Real-Time Estimation of Residual Tumor

Surgical resection continues to be the primary initial therapeutic strategy in the treatment of patients with brain tumors. Computerized cranial neuronavigation based on preoperative imaging offers precision guidance during craniotomy and early tumor resection but progressively loses validity with brain shift. Intraoperative MRI (iMRI) and intraoperative ultrasound (iUS) can update the imaging used for guidance and navigation but are limited in terms of temporal and spatial resolution, respectively. We present a system that uses time-stamped tool-tip positions of surgical instruments to generate a map of resection progress with high spatial and temporal accuracy. We evaluate this system and present results from 80 cranial tumor resections. Regions of the preoperative tumor segmentation that are covered by the resection map (True Positive Tracking) and regions of the preoperative tumor segmentation not covered by the resection map (True Negative Tracking) are determined for each case. We compare True Negative Tracking, which estimates the residual tumor, with the actual residual tumor identified using iMRI. We discuss factors that can cause False Positive Tracking and False Negative Tracking, which underestimate and overestimate the residual tumor, respectively. Our method provides good estimates of the residual tumor when there is minimal brain shift, and line-of-sight is maintained. When these conditions are not met, surgeons report that it is still useful for identifying regions of potential residual.

Augmented Reality to Compensate for Navigation Inaccuracies

This study aims to report on the capability of microscope-based augmented reality (AR) to evaluate registration and navigation accuracy with extracranial and intracranial landmarks and to elaborate on its opportunities and obstacles in compensation for navigation inaccuracies. In a consecutive single surgeon series of 293 patients, automatic intraoperative computed tomography-based registration was performed delivering a high initial registration accuracy with a mean target registration error of 0.84 ± 0.36 mm. Navigation accuracy is evaluated by overlaying a maximum intensity projection or pre-segmented object outlines within the recent focal plane onto the in situ patient anatomy and compensated for by translational and/or rotational in-plane transformations. Using bony landmarks (85 cases), there was two cases where a mismatch was seen. Cortical vascular structures (242 cases) showed a mismatch in 43 cases and cortex representations (40 cases) revealed two inaccurate cases. In all cases, with detected misalignment, a successful spatial compensation was performed (mean correction: bone (6.27 ± 7.31 mm), vascular (3.00 ± 1.93 mm, 0.38° ± 1.06°), and cortex (5.31 ± 1.57 mm, 1.75° ± 2.47°)) increasing navigation accuracy. AR support allows for intermediate and straightforward monitoring of accuracy, enables compensation of spatial misalignments, and thereby provides additional safety by increasing overall accuracy.

Anisocoria and mydriasis after scalp nerve block: a case report

Strategies for the assessment of abnormal neurological findings during general anesthesia are limited. However, pupil abnormalities may represent serious neurological complications. We herein present a case of new-onset anisocoria and mydriasis that developed after scalp nerve block. The patient's signs were possibly related to increased intracranial pressure with resulting brain shift that ultimately affected the oculomotor nerves. A 45-year-old man was scheduled for left cerebellar tumor resection and ventricular drainage surgery; however, anisocoria and left pupillary mydriasis were observed after induction of general anesthesia and performance of scalp nerve block. After reducing the intracranial pressure, the right pupil showed constriction (1 mm) but the left pupil was dilated (5 mm). The pupils were of similar size postoperatively. Although pupillary dilation during general anesthesia has been previously described, this is the first case in which the mydriasis was considered to have been caused by brain shift due to increased intracranial pressure after scalp nerve block. Thus, we propose this phenomenon as a new possible cause of pupillary changes. Actively monitoring this presentation intraoperatively could enable early detection of and intervention for complications, therefore improving the prognosis.

Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images are proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI.

Tracking motor and language eloquent white matter pathways with intraoperative fiber tracking versus preoperative tractography adjusted by intraoperative MRI-based elastic fusion

OBJECTIVE

Preoperative fiber tracking (FT) enables visualization of white matter pathways. However, the intraoperative accuracy of preoperative image registration is reduced due to brain shift. Intraoperative FT is currently considered the standard of anatomical accuracy, while intraoperative imaging can also be used to correct and update preoperative data by intraoperative MRI (ioMRI)-based elastic fusion (IBEF). However, the use of intraoperative tractography is restricted due to the need for additional acquisition of diffusion imaging in addition to scanner limitations, quality factors, and setup time. Since IBEF enables compensation for brain shift and updating of preoperative FT, the aim of this study was to compare intraoperative FT with IBEF of preoperative FT.

METHODS

Preoperative MRI (pMRI) and ioMRI, both including diffusion tensor imaging (DTI) data, were acquired between February and November 2018. Anatomy-based DTI FT of the corticospinal tract (CST) and the arcuate fascicle (AF) was reconstructed at various fractional anisotropy (FA) values on pMRI and ioMRI, respectively. The intraoperative DTI FT, as a baseline tractography, was fused with original preoperative FT and IBEF-compensated FT, processes referred to as rigid fusion (RF) and elastic fusion (EF), respectively. The spatial overlap index (Dice coefficient [DICE]) and distances of surface points (average surface distance [ASD]) of fused FT before and after IBEF were analyzed and compared in operated and nonoperated hemispheres.

RESULTS

Seventeen patients with supratentorial brain tumors were analyzed. On the operated hemisphere, the overlap index of pre- and intraoperative FT of the CST by DICE significantly increased by 0.09 maximally after IBEF. A significant decrease by 0.5 mm maximally in the fused FT presented by ASD was observed. Similar improvements were found in IBEF-compensated FT, for which AF tractography on the tumor hemispheres increased by 0.03 maximally in DICE and decreased by 1.0 mm in ASD.

CONCLUSIONS

Preoperative tractography after IBEF is comparable to intraoperative tractography and can be a reliable alternative to intraoperative FT.

Computer simulation of tumour resection-induced brain deformation by a meshless approach

Tumour resection requires precise planning and navigation to maximise tumour removal while simultaneously protecting nearby healthy tissues. Neurosurgeons need to know the location of the remaining tumour after partial tumour removal before continuing with the resection. Our approach to the problem uses biomechanical modelling and computer simulation to compute the brain deformations after the tumour is resected. In this study, we use meshless Total Lagrangian explicit dynamics as the solver. The problem geometry is extracted from the patient-specific magnetic resonance imaging (MRI) data and includes the parenchyma, tumour, cerebrospinal fluid and skull. The appropriate non-linear material formulation is used. Loading is performed by imposing intra-operative conditions of gravity and reaction forces between the tumour and surrounding healthy parenchyma tissues. A finite frictionless sliding contact is enforced between the skull (rigid) and parenchyma. The meshless simulation results are compared to intra-operative MRI sections. We also calculate Hausdorff distances between the computed deformed surfaces (ventricles and tumour cavities) and surfaces observed intra-operatively. Over 80% of points on the ventricle surface and 95% of points on the tumour cavity surface were successfully registered (results within the limits of two times the original in-plane resolution of the intra-operative image). Computed results demonstrate the potential for our method in estimating the tissue deformation and tumour boundary during the resection.

Causes, clinical significance and solution of the problem]

Intraoperative brain shift is the main cause of inaccurate navigation. This limits the use of both conventional and functional neuronavigation. Causes of brain shift are divided into surgical, pathophysiological and metabolic ones. Brain shift is usually unidirectional and directed towards gravitation. Brain dislocation depends on lesion size and its location. Shift is minimal in patients with tumors <20 ml and skull base neoplasms. Small craniotomy, retractor-free surgery and no ventriculostomy are valuable to reduce brain shift. Brain dislocation increases during surgery that's why marking of eloquent lesions at the beginning of surgery and primary resection near subcortical tracts minimize the risk of damage to conduction pathways. Augmented reality and manual shift of marked objects are the cornerstones of linear correction of brain shift in modern navigation systems. In case of nonlinear brain shift, sonography and intraoperative magnetic resonance imaging can clarify location of surgical target and cerebral structures.

Placement accuracy of the second electrode in bilateral deep brain stimulation surgery

PURPOSE

Due to brain shift during bilateral deep brain stimulation (DBS) surgery, placement of the second electrode may be subjected to more error than that of the first electrode. The authors aimed to investigate the accuracy of second electrode placement in this setting.

MATERIALS AND METHODS

Fifty-five patients with Parkinson's disease who underwent bilateral DBS surgery (110 electrodes) were retrospectively evaluated. The targets were subthalamic nucleus (STN) and globus pallidus interna (GPi) in 40 and 15 cases, respectively. Preoperative planning and postoperative electrode images were co-registered to compare the error margin between the two sides.

RESULTS

There is a statistically significant difference in the directional axis error along the y axis only when comparing each laterality (posterior 0.04 ± 1.21 mm vs anterior 0.41 ± 1.07 mm, p = 0.006). There is no significant difference of other error parameters, final track location, and number of microelectrode recording passes between the two sides. In a subgroup analysis, there is a significant difference in directional axis error along the y axis only in the STN subgroup (posterior 0.40 ± 1.05 mm vs anterior 0.18 ± 1.04 mm, p = 0.003).

CONCLUSION

Although a statistically significant difference in directional axis error along the y axis was found between first and second electrode placements in the STN group but not in the GPi group, its magnitude is well below the clinically significant threshold.

Viscoelastic biomechanical models to predict inward brain-shift using public benchmark data

Brain-shift during neurosurgery compromises the accuracy of tracking the boundaries of the tumor to be resected. Although several studies have used various finite element models (FEMs) to predict inward brain-shift, evaluation of their accuracy and efficiency based on public benchmark data has been limited. This study evaluates several FEMs proposed in the literature (various boundary conditions, mesh sizes, and material properties) by using intraoperative imaging data (the public REtroSpective Evaluation of Cerebral Tumors [RESECT] database). Four patients with low-grade gliomas were identified as having inward brain-shifts. We computed the accuracy (using target registration error) of several FEM-based brain-shift predictions and compared our findings. Since information on head orientation during craniotomy is not included in this database, we tested various plausible angles of head rotation. We analyzed the effects of brain tissue viscoelastic properties, mesh size, craniotomy position, CSF drainage level, and rigidity of meninges and then quantitatively evaluated the trade-off between accuracy and central processing unit time in predicting inward brain-shift across all models with second-order tetrahedral FEMs. The mean initial target registration error (TRE) was 5.78 ± 3.78 mm with rigid registration. FEM prediction (edge-length, 5 mm) with non-rigid meninges led to a mean TRE correction of 1.84 ± 0.83 mm assuming heterogeneous material. Results show that, for the low-grade glioma patients in the study, including non-rigid modeling of the meninges was significant statistically. In contrast including heterogeneity was not significant. To estimate the optimal head orientation and CSF drainage, an angle step of 5° and an CSF height step of 5 mm were enough leading to <0.26 mm TRE fluctuation.

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.

Brain Shift in Neuronavigation of Brain Tumors: An Updated Review of Intra-Operative Ultrasound Applications

Neuronavigation using pre-operative imaging data for neurosurgical guidance is a ubiquitous tool for the planning and resection of oncologic brain disease. These systems are rendered unreliable when brain shift invalidates the patient-image registration. Our previous review in 2015, Brain shift in neuronavigation of brain tumours: A review offered a new taxonomy, classification system, and a historical perspective on the causes, measurement, and pre- and intra-operative compensation of this phenomenon. Here we present an updated review using the same taxonomy and framework, focused on the developments of intra-operative ultrasound-based brain shift research from 2015 to the present (2020). The review was performed using PubMed to identify articles since 2015 with the specific words and phrases: “Brain shift” AND “Ultrasound”. Since 2015, the rate of publication of intra-operative ultrasound based articles in the context of brain shift has increased from 2–3 per year to 8–10 per year. This efficient and low-cost technology and increasing comfort among clinicians and researchers have allowed unique avenues of development. Since 2015, there has been a trend towards more mathematical advancements in the field which is often validated on publicly available datasets from early intra-operative ultrasound research, and may not give a just representation to the intra-operative imaging landscape in modern image-guided neurosurgery. Focus on vessel-based registration and virtual and augmented reality paradigms have seen traction, offering new perspectives to overcome some of the different pitfalls of ultrasound based technologies. Unfortunately, clinical adaptation and evaluation has not seen as significant of a publication boost. Brain shift continues to be a highly prevalent pitfall in maintaining accuracy throughout oncologic neurosurgical intervention and continues to be an area of active research. Intra-operative ultrasound continues to show promise as an effective, efficient, and low-cost solution for intra-operative accuracy management. A major drawback of the current research landscape is that mathematical tool validation based on retrospective data outpaces prospective clinical evaluations decreasing the strength of the evidence. The need for newer and more publicly available clinical datasets will be instrumental in more reliable validation of these methods that reflect the modern intra-operative imaging in these procedures.

Importance of Veins for Neurosurgery as Landmarks Against Brain Shifting Phenomenon: An Anatomical and 3D-MPRAGE MR Reconstruction of Superficial Cortical Veins

Modern neurosurgery uses preoperative imaging daily. Three-dimensional reconstruction of the cortical anatomy and of the superficial veins helps the surgeons plan and perform neurosurgical procedures much more safely. The target is always to give the patient maximum benefit in terms of outcome and minimize intraoperative and postoperative complications. This study aims to develop a method for the combined representation of the cerebral cortex anatomy and the superficial cerebral veins, whose integration is beneficial in daily practice. Only those patients who underwent surgical procedures with craniotomy and a large opening of the dura mater were included in this study, for a total of 23 patients, 13 females (56.5%) and 10 males (43.5%). The average age was 50.1 years. We used a magnetic resonance tomograph Magnetom Vision® 1.5T (Siemens AG). Two sequences were applied: a strongly T1-weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequence to visualize cerebral anatomical structures, and a FLASH-2D-TOF angiography sequence to visualize the venous vessels on the cortical surface after the administration of a paramagnetic contrast agent. The two data sets were superimposed manually, co-registered in an interactive process, and merged to create a combined data set, segmented and visualized as a three-dimensional reconstruction. Furthermore, we present our method for visualizing superficial veins, which helps manage brain shift (BS). We also performed anatomical observations on the reconstructions. The reconstructions of the cortical and venous anatomy proved to be a valuable tool in surgical planning and positively influenced the surgical procedure. Due to the good correlation with the existing surgical site, this method should be validated on a larger cohort or in a multicentric study.

Comparing Programming Sessions of Vim-DBS

Background: Essential Tremor (ET) is a progressive neurological disorder characterized by postural and kinetic tremor most commonly affecting the hands and arms. Medically intractable ET can be treated by deep brain stimulation (DBS) of the ventral intermediate nucleus of thalamus (VIM). We investigated whether the location of the effective contact (most tremor suppression with at least side effects) in VIM-DBS for ET changes over time, indicating a distinct mechanism of loss of efficacy that goes beyond progression of tremor severity, or a mere reduction of DBS efficacy.

Methods: We performed programming sessions in 10 patients who underwent bilateral vim-DBS surgery between 2009 and 2017 at our department. In addition to the intraoperative (T1) and first clinical programming session (T2) a third programming session (T3) was performed to assess the effect- and side effect threshold (minimum voltage at which a tremor suppression or side effects occurred). Additionally, we compared the choice of the effective contact between T1 and T2 which might be affected by a surgical induced “brain shift.”

Discussion: Over a time span of about 4 years VIM-DBS in ET showed continuous efficacy in tremor suppression during stim-ON compared to stim-OFF. Compared to immediate postoperative programming sessions in ET-patients with DBS, long-term evaluation showed no relevant change in the choice of contact with respect to side effects and efficacy. In the majority of the cases the active contact at T2 did not correspond to the most effective intraoperative stimulation site T1, which might be explained by a brain-shift due to cerebral spinal fluid loss after neurosurgical procedure.

Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge

In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets and other vital structures such as blood vessels, thus invalidating the pre-surgical plan. Intra-operative ultrasound (iUS) is a convenient and cost-effective imaging tool to track brain shift and tumor resection. Accurate image registration techniques that update pre-surgical MRI based on iUS are crucial but challenging. The MICCAI Challenge 2018 for Correction of Brain shift with Intra-Operative UltraSound (CuRIOUS2018) provided a public platform to benchmark MRI-iUS registration algorithms on newly released clinical datasets. In this work, we present the data, setup, evaluation, and results of CuRIOUS 2018, which received 6 fully automated algorithms from leading academic and industrial research groups. All algorithms were first trained with the public RESECT database, and then ranked based on a test dataset of 10 additional cases with identical data curation and annotation protocols as the RESECT database. The article compares the results of all participating teams and discusses the insights gained from the challenge, as well as future work.

Biomechanical modeling and computer simulation of the brain during neurosurgery

Computational biomechanics of the brain for neurosurgery is an emerging area of research recently gaining in importance and practical applications. This review paper presents the contributions of the Intelligent Systems for Medicine Laboratory and its collaborators to this field, discussing the modeling approaches adopted and the methods developed for obtaining the numerical solutions. We adopt a physics-based modeling approach and describe the brain deformation in mechanical terms (such as displacements, strains, and stresses), which can be computed using a biomechanical model, by solving a continuum mechanics problem. We present our modeling approaches related to geometry creation, boundary conditions, loading, and material properties. From the point of view of solution methods, we advocate the use of fully nonlinear modeling approaches, capable of capturing very large deformations and nonlinear material behavior. We discuss finite element and meshless domain discretization, the use of the total Lagrangian formulation of continuum mechanics, and explicit time integration for solving both time-accurate and steady-state problems. We present the methods developed for handling contacts and for warping 3D medical images using the results of our simulations. We present two examples to showcase these methods: brain shift estimation for image registration and brain deformation computation for neuronavigation in epilepsy treatment.

Intraoperative acquisition of DTI in cranial neurosurgery: readout-segmented DTI versus standard single-shot DTI

OBJECTIVE

Diffusion tensor imaging (DTI) tractography is commonly used in neurosurgical practice but is largely limited to the preoperative setting. This is due primarily to image degradation caused by susceptibility artifact when conventional single-shot (SS) echo-planar imaging (EPI) DTI (SS-DTI) is acquired for open cranial, surgical position intraoperative DTI (iDTI). Readout-segmented (RS) EPI DTI (RS-DTI) has been reported to reduce such artifact but has not yet been evaluated in the intraoperative MRI (iMRI) environment. The authors evaluated the performance of RS versus SS EPI for DTI of the human brain in the iMRI setting.

METHODS

Pre- and intraoperative 3-T 3D T1-weighted and 2D multislice RS-iDTI (called RESOLVE [readout segmentation of long variable echo-trains] on the Siemens platform) and SS-iDTI images were acquired in 22 adult patients undergoing intraaxial iMRI resections for suspected low-grade glioma (14; 64%), high-grade glioma (7; 32%), or focal cortical dysplasia. Regional susceptibility artifact, anatomical deviation relative to T1-weighted imaging, and tractographic output for surgically relevant tracts were compared between iDTI sequences as well as the intraoperative tract shifts from preoperative DTI.

RESULTS

RS-iDTI resulted in qualitatively less regional susceptibility artifact (resection cavity, orbitofrontal and anterior temporal cortices) and mean anatomical deviation in regions most prone to susceptibility artifact (RS-iDTI 2.7 ± 0.2 vs SS-iDTI 7.5 ± 0.4 mm) compared to SS-iDTI. Although tract reconstruction success did not significantly differ by DTI method, susceptibility artifact-related tractography failure (of at least 1 surgically relevant tract) occurred for SS-iDTI in 8/22 (36%) patients, and in 5 of these 8 patients RS-iDTI permitted successful reconstruction. Among cases with successful tractography for both sequences, maximal intersequence differences were substantial (mean 9.5 ± 5.7 mm, range -27.1 to 18.7 mm).

CONCLUSIONS

RS EPI enables higher quality and more accurate DTI for surgically relevant tractography of major white matter tracts in intraoperative, open cranium neurosurgical applications at 3 T.

Preliminary Results Comparing Thin Plate Splines with Finite Element Methods for Modeling Brain Deformation during Neurosurgery using Intraoperative Ultrasound

Brain shift compensation attempts to model the deformation of the brain which occurs during the surgical removal of brain tumors to enable mapping of presurgical image data into patient coordinates during surgery and thus improve the accuracy and utility of neuro-navigation. We present preliminary results from clinical tumor resections that compare two methods for modeling brain deformation, a simple thin plate spline method that interpolates displacements and a more complex finite element method (FEM) that models physical and geometric constraints of the brain and its material properties. Both methods are driven by the same set of displacements at locations surrounding the tumor. These displacements were derived from sets of corresponding matched features that were automatically detected using the SIFT-Rank algorithm. The deformation accuracy was tested using a set of manually identified landmarks. The FEM method requires significantly more preprocessing than the spline method but both methods can be used to model deformations in the operating room in reasonable time frames. Our preliminary results indicate that the FEM deformation model significantly out-performs the spline-based approach for predicting the deformation of manual landmarks. While both methods compensate for brain shift, this work suggests that models that incorporate biophysics and geometric constraints may be more accurate.

Efficacy of Dural Sealant System for Preventing Brain Shift and Improving Accuracy in Deep Brain Stimulation Surgery

The success of deep brain stimulation (DBS) depends heavily on surgical accuracy, and brain shift is recognized as a significant factor influencing accuracy. We investigated the factors associated with surgical accuracy and showed the effectiveness of a dural sealant system for preventing brain shift in 32 consecutive cases receiving DBS. Thirty-two patients receiving DBS between March 2014 and May 2015 were included in this study. We employed conventional burr hole techniques for the first 18 cases (Group I) and a dural sealant system (DuraSeal) for the subsequent 14 cases (Group II). We measured gaps between the actual positions of electrodes and the predetermined target positions. We then retrospectively evaluated the factors involved in surgical accuracy. The average gap between an electrode’s actual and target positions was 1.55 ± 0.83 mm in all cases. Postoperative subdural air volume e, the only factor associated with surgical accuracy (r = 0.536, P < 0.0001), was significantly smaller in Group II (Group I: 43.9 ± 27.7, Group II: 12.1 ± 12.5 ml, P = 0.0006). The average electrode position gap was also significantly smaller in Group II (Group I: 1.77 ± 0.91, Group II: 1.27 ± 0.59 mm, P = 0.035). Use of a dural sealant system could significantly reduce intracranial air volume, which should improve surgical accuracy.

Controlling the error on target motion through real-time mesh adaptation: Applications to deep brain stimulation

An error-controlled mesh refinement procedure for needle insertion simulations is presented. As an example, the procedure is applied for simulations of electrode implantation for deep brain stimulation. We take into account the brain shift phenomena occurring when a craniotomy is performed. We observe that the error in the computation of the displacement and stress fields is localised around the needle tip and the needle shaft during needle insertion simulation. By suitably and adaptively refining the mesh in this region, our approach enables to control, and thus to reduce, the error whilst maintaining a coarser mesh in other parts of the domain. Through academic and practical examples we demonstrate that our adaptive approach, as compared with a uniform coarse mesh, increases the accuracy of the displacement and stress fields around the needle shaft and, while for a given accuracy, saves computational time with respect to a uniform finer mesh. This facilitates real-time simulations. The proposed methodology has direct implications in increasing the accuracy, and controlling the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anaesthesia, or cryotherapy. Moreover, the proposed approach can be helpful in the development of robotic surgeries because the simulation taking place in the control loop of a robot needs to be accurate, and to occur in real time.

Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases

We present our work investigating the feasibility of combining intraoperative ultrasound for brain shift correction and augmented reality (AR) visualization for intraoperative interpretation of patient-specific models in image-guided neurosurgery (IGNS) of brain tumors. We combine two imaging technologies for image-guided brain tumor neurosurgery. Throughout surgical interventions, AR was used to assess different surgical strategies using three-dimensional (3-D) patient-specific models of the patient's cortex, vasculature, and lesion. Ultrasound imaging was acquired intraoperatively, and preoperative images and models were registered to the intraoperative data. The quality and reliability of the AR views were evaluated with both qualitative and quantitative metrics. A pilot study of eight patients demonstrates the feasible combination of these two technologies and their complementary features. In each case, the AR visualizations enabled the surgeon to accurately visualize the anatomy and pathology of interest for an extended period of the intervention. Inaccuracies associated with misregistration, brain shift, and AR were improved in all cases. These results demonstrate the potential of combining ultrasound-based registration with AR to become a useful tool for neurosurgeons to improve intraoperative patient-specific planning by improving the understanding of complex 3-D medical imaging data and prolonging the reliable use of IGNS.

Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation

Intraoperative soft tissue deformation, referred to as brain shift, compromises the application of current image-guided surgery navigation systems in neurosurgery. A computational model driven by sparse data has been proposed as a cost-effective method to compensate for cortical surface and volumetric displacements. We present a mock environment developed to acquire stereoimages from a tracked operating microscope and to reconstruct three-dimensional point clouds from these images. A reconstruction error of 1 mm is estimated by using a phantom with a known geometry and independently measured deformation extent. The microscope is tracked via an attached tracking rigid body that facilitates the recording of the position of the microscope via a commercial optical tracking system as it moves during the procedure. Point clouds, reconstructed under different microscope positions, are registered into the same space to compute the feature displacements. Using our mock craniotomy device, realistic cortical deformations are generated. When comparing our tracked microscope stereo-pair measure of mock vessel displacements to that of the measurement determined by the independent optically tracked stylus marking, the displacement error was [Formula: see text] on average. These results demonstrate the practicality of using tracked stereoscopic microscope as an alternative to laser range scanners to collect sufficient intraoperative information for brain shift correction.

Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery

Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.

Android application for determining surgical variables in brain-tumor resection procedures

The fidelity of image-guided neurosurgical procedures is often compromised due to the mechanical deformations that occur during surgery. In recent work, a framework was developed to predict the extent of this brain shift in brain-tumor resection procedures. The approach uses preoperatively determined surgical variables to predict brain shift and then subsequently corrects the patient's preoperative image volume to more closely match the intraoperative state of the patient's brain. However, a clinical workflow difficulty with the execution of this framework is the preoperative acquisition of surgical variables. To simplify and expedite this process, an Android, Java-based application was developed for tablets to provide neurosurgeons with the ability to manipulate three-dimensional models of the patient's neuroanatomy and determine an expected head orientation, craniotomy size and location, and trajectory to be taken into the tumor. These variables can then be exported for use as inputs to the biomechanical model associated with the correction framework. A multisurgeon, multicase mock trial was conducted to compare the accuracy of the virtual plan to that of a mock physical surgery. It was concluded that the Android application was an accurate, efficient, and timely method for planning surgical variables.

A combined registration and finite element analysis method for fast estimation of intraoperative brain shift; phantom and animal model study

BACKGROUND

Finite element models for estimation of intraoperative brain shift suffer from huge computational cost. In these models, image registration and finite element analysis are two time-consuming processes.

METHODS

The proposed method is an improved version of our previously developed Finite Element Drift (FED) registration algorithm. In this work the registration process is combined with the finite element analysis. In the Combined FED (CFED), the deformation of whole brain mesh is iteratively calculated by geometrical extension of a local load vector which is computed by FED.

RESULTS

While the processing time of the FED-based method including registration and finite element analysis was about 70 s, the computation time of the CFED was about 3.2 s. The computational cost of CFED is almost 50% less than similar state of the art brain shift estimators based on finite element models.

CONCLUSIONS

The proposed combination of registration and structural analysis can make the calculation of brain deformation much faster.

Applications of Ultrasound in the Resection of Brain Tumors

Neurosurgery makes use of preoperative imaging to visualize pathology, inform surgical planning, and evaluate the safety of selected approaches. The utility of preoperative imaging for neuronavigation, however, is diminished by the well-characterized phenomenon of brain shift, in which the brain deforms intraoperatively as a result of craniotomy, swelling, gravity, tumor resection, cerebrospinal fluid (CSF) drainage, and many other factors. As such, there is a need for updated intraoperative information that accurately reflects intraoperative conditions. Since 1982, intraoperative ultrasound has allowed neurosurgeons to craft and update operative plans without ionizing radiation exposure or major workflow interruption. Continued evolution of ultrasound technology since its introduction has resulted in superior imaging quality, smaller probes, and more seamless integration with neuronavigation systems. Furthermore, the introduction of related imaging modalities, such as 3-dimensional ultrasound, contrast-enhanced ultrasound, high-frequency ultrasound, and ultrasound elastography, has dramatically expanded the options available to the neurosurgeon intraoperatively. In the context of these advances, we review the current state, potential, and challenges of intraoperative ultrasound for brain tumor resection. We begin by evaluating these ultrasound technologies and their relative advantages and disadvantages. We then review three specific applications of these ultrasound technologies to brain tumor resection: (1) intraoperative navigation, (2) assessment of extent of resection, and (3) brain shift monitoring and compensation. We conclude by identifying opportunities for future directions in the development of ultrasound technologies.

Automated alignment of perioperative MRI scans: A technical note and application in pediatric epilepsy surgery

Conventional image registration utilizing brain voxel information may be erroneous in a neurosurgical setting due to pathology and surgery-related anatomical distortions. We report a novel application of an automated image registration procedure based on skull segmentation for magnetic resonance imaging (MRI) scans acquired before, during and after surgery (i.e., perioperative). The procedure was implemented to assist analysis of intraoperative brain shift in 11 pediatric epilepsy surgery cases, each of whom had up to five consecutive perioperative MRI scans. The procedure consisted of the following steps: (1) Skull segmentation using tissue classification tools. (2) Estimation of rigid body transformation between image pairs using registration driven by the skull segmentation. (3) Composition of transformations to provide transformations between each scan and a common space. The procedure was validated using locations of three types of reference structural landmarks: the skull pin sites, the eye positions, and the scalp skin surface, detected using the peak intensity gradient. The mean target registration error (TRE) scores by skull pin sites and scalp skin rendering were around 1 mm and <1 mm, respectively. Validation by eye position demonstrated >1 mm TRE scores, suggesting it is not a reliable reference landmark in surgical scenarios. Comparable registration accuracy was achieved between opened and closed skull scan pairs and closed and closed skull scan pairs. Our procedure offers a reliable registration framework for processing intrasubject time series perioperative MRI data, with potential of improving intraoperative MRI-based image guidance in neurosurgical practice. Hum Brain Mapp 37:3530-3543, 2016. © 2016 Wiley Periodicals, Inc.

Post-operative imaging in deep brain stimulation: A controversial issue

In deep brain stimulation (DBS), post-operative imaging has been used on the one hand to assess complications, such as haemorrhage; and on the other hand, to detect misplaced contacts. The post-operative determination of the accurate location of the final electrode plays a critical role in evaluating the precise area of effective stimulation and for predicting the potential clinical outcome; however, safety remains a priority in postoperative DBS imaging. A plethora of diverse post-operative imaging methods have been applied at different centres. There is neither a consensus on the most efficient post-operative imaging methodology, nor is there any standardisation for the automatic or manual analysis of the images within the different imaging modalities. In this article, we give an overview of currently applied post-operative imaging modalities and discuss the current challenges in post-operative imaging in DBS.

Simultaneous bilateral stereotactic procedure for deep brain stimulation implants: a significant step for reducing operation time

OBJECT Currently, bilateral procedures involve 2 sequential implants in each of the hemispheres. The present report demonstrates the feasibility of simultaneous bilateral procedures during the implantation of deep brain stimulation (DBS) leads. METHODS Fifty-seven patients with movement disorders underwent bilateral DBS implantation in the same study period. The authors compared the time required for the surgical implantation of deep brain electrodes in 2 randomly assigned groups. One group of 28 patients underwent traditional sequential electrode implantation, and the other 29 patients underwent simultaneous bilateral implantation. Clinical outcomes of the patients with Parkinson's disease (PD) who had undergone DBS implantation of the subthalamic nucleus using either of the 2 techniques were compared. RESULTS Overall, a reduction of 38.51% in total operating time for the simultaneous bilateral group (136.4 ± 20.93 minutes) as compared with that for the traditional consecutive approach (220.3 ± 27.58 minutes) was observed. Regarding clinical outcomes in the PD patients who underwent subthalamic nucleus DBS implantation, comparing the preoperative off-medication condition with the off-medication/on-stimulation condition 1 year after the surgery in both procedure groups, there was a mean 47.8% ± 9.5% improvement in the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) score in the simultaneous group, while the sequential group experienced 47.5% ± 15.8% improvement (p = 0.96). Moreover, a marked reduction in the levodopa-equivalent dose from preoperatively to postoperatively was similar in these 2 groups. The simultaneous bilateral procedure presented major advantages over the traditional sequential approach, with a shorter total operating time. CONCLUSIONS A simultaneous stereotactic approach significantly reduces the operation time in bilateral DBS procedures, resulting in decreased microrecording time, contributing to the optimization of functional stereotactic procedures.

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.

More accurate neuronavigation data provided by biomechanical modeling instead of rigid registration

It is possible to improve neuronavigation during image-guided surgery by warping the high-quality preoperative brain images so that they correspond with the current intraoperative configuration of the brain. In this paper, the accuracy of registration results obtained using comprehensive biomechanical models is compared with the accuracy of rigid registration, the technology currently available to patients. This comparison allows investigation into whether biomechanical modeling provides good-quality image data for neuronavigation for a larger proportion of patients than rigid registration. Preoperative images for 33 neurosurgery cases were warped onto their respective intraoperative configurations using both the biomechanics-based method and rigid registration. The Hausdorff distance-based evaluation process, which measures the difference between images, was used to quantify the performance of both registration methods. A statistical test for difference in proportions was conducted to evaluate the null hypothesis that the proportion of patients for whom improved neuronavigation can be achieved is the same for rigid and biomechanics-based registration. The null hypothesis was confidently rejected (p < 10(-4)). Even the modified hypothesis that fewer than 25% of patients would benefit from the use of biomechanics-based registration was rejected at a significance level of 5% (p = 0.02). The biomechanics-based method proved particularly effective in cases demonstrating large craniotomy-induced brain deformations. The outcome of this analysis suggests that nonlinear biomechanics-based methods are beneficial to a large proportion of patients and can be considered for use in the operating theater as a possible means of improving neuronavigation and surgical outcomes.

Rapid brain shift, remote site hemorrhage, and a spinal hematoma after craniotomy for a large arachnoid cyst

Arachnoid cysts are prevalent among the general population. The management options of symptomatic arachnoid cysts each have their own merits and disadvantages. We report a case where a large arachnoid cyst was treated by open fenestration and marsupialization that was complicated by remote intraparenchymal and spinal subdural hemorrhage. The potential physiological changes underlying these complications as well as the related literature are reviewed.

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.

An intraoperative brain shift monitor using shear mode transcranial ultrasound: preliminary results

OBJECTIVE

Various methods of intraoperative structural monitoring during neurosurgery are used to localize lesions after brain shift and to guide surgically introduced probes such as biopsy needles or stimulation electrodes. With its high temporal resolution, portability, and nonionizing mode of radiation, ultrasound has potential advantages over other existing imaging modalities for intraoperative monitoring, yet ultrasound is rarely used during neurosurgery largely because of the craniotomy requirement to achieve sufficiently useful signals.

METHODS

Prompted by results from recent studies on transcranial ultrasound, a prototype device that aims to use the shear mode of transcranial ultrasound transmission for intraoperative monitoring was designed, constructed, and tested with 10 human participants. Magnetic resonance images were then obtained with the device spatially registered to the magnetic resonance imaging (MRI) reference coordinates. Peaks in both the ultrasound and MRI signals were identified and analyzed for both spatial localization and signal-to-noise ratio (SNR).

RESULTS

The first results aimed toward validating the prototype device with MRI showed an excellent correlation (n = 38; R(2) = 0.9962) between the structural localization abilities of the two modalities. In addition, the overall SNR of the ultrasound backscatter signals (n = 38; SNR = 25.4 +/- 5.2 dB, mean +/- SD) was statistically equivalent to that of the MRI data (n = 38; SNR = 22.5 +/- 4.8 dB).

CONCLUSIONS

A statistically significant correlation of localized intracranial structures between intraoperative transcranial ultrasound monitoring and MRI data was achieved with 10 human participants. We have shown and validated a prototype device incorporating transcranial shear mode ultrasound for clinical monitoring applications.

Nonrigid Registration of Brain Tumor Resection MR Images Based on Joint Saliency Map and Keypoint Clustering

This paper proposes a novel global-to-local nonrigid brain MR image registration to compensate for the brain shift and the unmatchable outliers caused by the tumor resection. The mutual information between the corresponding salient structures, which are enhanced by the joint saliency map (JSM), is maximized to achieve a global rigid registration of the two images. Being detected and clustered at the paired contiguous matching areas in the globally registered images, the paired pools of DoG keypoints in combination with the JSM provide a useful cluster-to-cluster correspondence to guide the local control-point correspondence detection and the outlier keypoint rejection. Lastly, a quasi-inverse consistent deformation is smoothly approximated to locally register brain images through the mapping the clustered control points by compact support radial basis functions. The 2D implementation of the method can model the brain shift in brain tumor resection MR images, though the theory holds for the 3D case.

Intraoperative cortical surface characterization using laser range scanning: preliminary results

OBJECTIVE

To present a novel methodology that uses a laser range scanner (LRS) capable of generating textured (intensity-encoded) surface descriptions of the brain surface for use with image-to-patient registration and improved cortical feature recognition during intraoperative neurosurgical navigation.

METHODS

An LRS device was used to acquire cortical surface descriptions of eight patients undergoing neurosurgery for a variety of clinical presentations. Textured surface descriptions were generated from these intraoperative acquisitions for each patient. Corresponding textured surfaces were also generated from each patient's preoperative magnetic resonance tomograms. Each textured surface pair (LRS and magnetic resonance tomogram) was registered using only cortical surface information. Novel visualization of the combined surfaces allowed for registration assessment based on quantitative cortical feature alignment.

RESULTS

Successful textured LRS surface acquisition and generation was performed on all eight patients. The data acquired by the LRS accurately presented the intraoperative surface of the cortex and the associated features within the surgical field-of-view. Registration results are presented as overlays of the intraoperative data with respect to the preoperative data and quantified by comparing mean distances between cortical features on the magnetic resonance tomogram and LRS surfaces after registration. The overlays demonstrated that accurate registration can be provided between the preoperative and intraoperative data and emphasized a potential enhancement to cortical feature recognition within the operating room environment. Using the best registration result from each clinical case, the mean feature alignment error is 1.7 +/- 0.8 mm over all cases.

CONCLUSION

This study demonstrates clinical deployment of an LRS capable of generating textured surfaces of the surgical field of view. Data from the LRS was registered accurately to the corresponding preoperative data. Visual inspection of the registration results was provided by overlays that put the intraoperative data within the perspective of the whole brain's surface. These visuals can be used to more readily assess the fidelity of image-to-patient registration, as well as to enhance recognition of cortical features for assistance in comparing the neurotopography between magnetic resonance image volume and physical patient. In addition, the feature-rich data presented here provides considerable motivation for using LRS scanning to measure deformation during surgery.

Robust nonrigid registration to capture brain shift from intraoperative MRI

We present a new algorithm to register 3-D preoperative magnetic resonance (MR) images to intraoperative MR images of the brain which have undergone brain shift. This algorithm relies on a robust estimation of the deformation from a sparse noisy set of measured displacements. We propose a new framework to compute the displacement field in an iterative process, allowing the solution to gradually move from an approximation formulation (minimizing the sum of a regularization term and a data error term) to an interpolation formulation (least square minimization of the data error term). An outlier rejection step is introduced in this gradual registration process using a weighted least trimmed squares approach, aiming at improving the robustness of the algorithm. We use a patient-specific model discretized with the finite element method in order to ensure a realistic mechanical behavior of the brain tissue. To meet the clinical time constraint, we parallelized the slowest step of the algorithm so that we can perform a full 3-D image registration in 35 s (including the image update time) on a heterogeneous cluster of 15 personal computers. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift of up to 14 mm. The results show a good ability to recover large displacements, and a limited decrease of accuracy near the tumor resection cavity.