The accuracy and reliability of 3D CT/MRI co-registration in planning epilepsy surgery

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Patient-specific solution of the electrocorticography forward problem in deforming brain

Invasive intracranial electroencephalography (iEEG), or electrocorticography (ECoG), measures electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery. Combined with numerical modeling it can further improve accuracy of epilepsy surgery planning. Accurate solution of the iEEG forward problem, which is a crucial prerequisite for solving the iEEG inverse problemin epilepsy seizure onset zone localization, requires accurate representation of the patient's brain geometry and tissue electrical conductivity after implantation of electrodes. However, implantation of subdural grid electrodes causes the brain to deform, which invalidates preoperatively acquired image data. Moreover, postoperative magnetic resonance imaging (MRI) is incompatible with implanted electrodes and computed tomography (CT) has insufficient range of soft tissue contrast, which precludes both MRI and CT from being used to obtain the deformed postoperative geometry. In this paper, we present a biomechanics-based image warping procedure using preoperative MRI for tissue classification and postoperative CT for locating implanted electrodes to perform non-rigid registration of the preoperative image data to the postoperative configuration. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. Results for the simulation of a current source in the brain show large differences in electric potential predicted by the models based on the original images and the deformed images corresponding to the brain geometry deformed by placement of invasive electrodes. Computation of the lead field matrix (useful for solution of the iEEG inverse problem) also showed significant differences between the different models. The results suggest that rapid and accurate solution of the forward problem in a deformed brain for a given patient is achievable.

Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

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.

Safety of MRI in the localization of implanted intracranial electrodes for refractory epilepsy

BACKGROUND AND PURPOSE

This is an observational study to evaluate the safety of magnetic resonance imaging (MRI) to localize subdural grids and depth electrodes in patients with refractory epilepsy using a 1.5 Tesla MR scanner.

METHODS

We implemented an optimized MRI protocol providing adequate image quality for the assessment of subdural grids and depth electrodes, while minimizing the specific absorption rate (SAR). We reviewed all MRI studies performed in patients with subdural grids and depth electrodes between January 2010 and October 2018. Image quality was graded as acceptable or nonacceptable for the assessment of intracranial device positioning. We reviewed the medical record and any imaging obtained after intracranial implant removal for adverse event or complication occurring during and after the procedure.

RESULTS

Ninety-nine patients with refractory epilepsy underwent MRI scans using a magnetization-prepared rapid acquisition of gradient echo sequence and a transmit-receive head coil with depth electrodes and subdural grids in place. Two patients underwent two separate depth electrode implantations for a total of 101 procedures and MRI scans. No clinical adverse events were reported during or immediately after imaging. Image quality was graded as acceptable for 97 MRI scans. Review of follow-up CT and MRI studies after implant removal, available for 70 patients, did not demonstrate unexpected complications in 69 patients.

CONCLUSION

In our experience, a low SAR MRI protocol can be used to safely localize intracranial subdural grids and depth electrode in patients with refractory epilepsy.

ViceCT and whiceCT for simultaneous high-resolution visualization of craniofacial, brain and ventricular anatomy from micro-computed tomography

Up to 40% of congenital diseases present disturbances of brain and craniofacial development resulting in simultaneous alterations of both systems. Currently, the best available method to preclinically visualize the brain and the bones simultaneously is to co-register micro-magnetic resonance (µMR) and micro-computed tomography (µCT) scans of the same specimen. However, this requires expertise and access to both imaging techniques, dedicated software and post-processing knowhow. To provide a more affordable, reliable and accessible alternative, recent research has focused on optimizing a contrast-enhanced µCT protocol using iodine as contrast agent that delivers brain and bone images from a single scan. However, the available methods still cannot provide the complete visualization of both the brain and whole craniofacial complex. In this study, we have established an optimized protocol to diffuse the contrast into the brain that allows visualizing the brain parenchyma and the complete craniofacial structure in a single ex vivo µCT scan (whiceCT). In addition, we have developed a new technique that allows visualizing the brain ventricles using a bilateral stereotactic injection of iodine-based contrast (viceCT). Finally, we have tested both techniques in a mouse model of Down syndrome, as it is a neurodevelopmental disorder with craniofacial, brain and ventricle defects. The combined use of viceCT and whiceCT provides a complete visualization of the brain and bones with intact craniofacial structure of an adult mouse ex vivo using a single imaging modality.

Fabrication and validation of reference structures for the localization of subdural standard- and micro-electrodes in MRI

OBJECTIVE

Report simple reference structure fabrication and validate the precise localization of subdural micro- and standard electrodes in magnetic resonance imaging (MRI) in phantom experiments.

APPROACH

Electrode contacts with diameters of 0.3 mm and 4 mm are localized in 1.5 T MRI using reference structures made of silicone and iron oxide nanoparticle doping. The precision of the localization procedure was assessed for several standard MRI sequences and implant orientations in phantom experiments and compared to common clinical localization procedures.

MAIN RESULTS

A localization precision of 0.41 ± 0.20 mm could be achieved for both electrode diameters compared to 1.46 ± 0.69 mm that was achieved for 4 mm standard electrode contacts localized using a common clinical standard method. The new reference structures are intrinsically bio-compatible, and they can be detected with currently available feature detection software so that a clinical implementation of this technology should be feasible.

SIGNIFICANCE

Neuropathologies are increasingly diagnosed and treated with subdural electrodes, where the exact localization of the electrode contacts with respect to the patient's cortical anatomy is a prerequisite for the procedure. Post-implantation electrode localization using MRI may be advantageous compared to the common alternative of CT-MRI image co-registration, as it avoids systematic localization errors associated with the co-registration itself, as well as brain shift and implant movement. Additionally, MRI provides superior soft tissue contrast for the identification of brain lesions without exposing the patient to ionizing radiation. Recent studies show that smaller electrodes and high-density electrode grids are ideal for clinical and research purposes, but the localization of these devices in MRI has not been demonstrated.

The applied research of simultaneous image acquisition of T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) in the assessment of patients with prostate cancer

We aimed to evaluate the feasibility of simultaneous image acquisition of multiple instantaneous switchable scan (MISS) for prostate magnetic resonance imaging (MRI) on 3T. Fifty-three patients were scanned with MRI due to suspected prostate cancer. Twenty-eight of them got histological results. First, two readers assessed the structure delineation and image quality based on images of conventional T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) (CTD). Second, two readers identified the index lesion together, and then, reader one evaluated the contrast of index lesion on T2WI and signal ratio on apparent diffusion coefficient map. Third, they assigned Prostate Imaging Reporting and Data System (PI-RADS) score in consensus for the index lesion. After 4 weeks, the images of MISS were reviewed by the same readers following the same process. Finally, two readers gave preference for image interpretation, respectively. Kappa coefficient, Wilcoxon signed-rank test, paired-sample t-test, Bland–Altman analysis, and receiver operating characteristic (ROC) analysis were used for statistical analysis. The acquisition time of CTD was 6 min and 10 s, while the acquisition time of MISS was 4 min and 30 s. Interobserver agreements for image evaluation were κ = 0.65 and κ = 0.80 for CTD and MISS, respectively. MISS-T2WI showed better delineation for seminal vesicles than CTD-T2WI (reader 1: P < 0.001, reader 2: P = 0.001). The index lesion demonstrated higher contrast in MISS-T2WI (P < 0.001). The PI-RADS scores based on CTD and MISS exhibited high ability in predicting clinically significant cancer (area under curve [AUC] = 0.828 vs 0.854). Readers preferred to use MISS in 41.5%–47.2% of cases. MISS showed comparable performance to conventional technique with less acquisition time.

Enhanced co-registration methods to improve intracranial electrode contact localization

Background

Electrode contact locations are important when planning tailored brain surgeries to identify pathological tissue targeted for resection and conversely avoid eloquent tissue. Current methods employ trained experts to use neuroimaging scans that are manually co-registered and localize contacts within ~2 mm. Yet, the state of the art is limited by either the expertise needed for each type of intracranial electrode or the inter-modality co-registration which increases error, reducing accuracy. Patients often have a variety of strips, grids and depths implanted; therefore, it is cumbersome and time-consuming to apply separate localization methods for each type of electrode, requiring expertise across different approaches.

New method

To overcome these limitations, a computational method was developed by separately registering an implant magnetic resonance image (MRI) and implant computed tomography image (CT) to the pre-implant MRI, then calculating an iterative closest point transformation using the contact locations extracted from the signal voids as ground truth.

Results

The implant MRI is robustly co-registered to the pre-implant MRI with a boundary-based registration algorithm. By extracting and utilizing ‘signal voids’ (the metal induced artifacts from the implant MRI) as electrode fiducials, the novel method is an all-in-one approach for all types of intracranial electrodes while eliminating inter-modality co-registration errors.

Comparison with existing methods

The distance between each electrode centroid and the brain's surface was measured, for the proposed method as well as the state of the art method using two available software packages, SPM 12 and FSL 4.1. The method presented here achieves the smallest distances to the brain's surface for all strip and grid type electrodes, i.e. contacts designed to rest directly on the brain surface.

Conclusion

We use one of the largest reported sample sizes in localization studies to validate this novel method for localizing different kinds of intracranial electrodes including grids, strips and depth electrodes.

•

Co-registration between intramodal pre- and implant images allows for accurate localization of all subdural electrode types.

•

Iterative closest point (ICP) assisted grid electrode localization is comparable to existing implant MRI based methods.

•

ICP is a novel, semi-automated method to localize grid, strip and depth electrodes with state-of-the-art accuracy

Investigation of subdural electrode displacement in invasive epilepsy surgery workup using neuronavigation and intraoperative MRI

OBJECTIVES

One of the main obstacles of electrode implantation in epilepsy surgery is the electrode shift between implantation and the day of explantation. We evaluated this possible electrode displacement using intraoperative MRI (iopMRI) data and CT/MRI reconstruction.

METHODS

Thirteen patients (nine female, four male, median age 26 ± 9.4 years) suffering from drug-resistant epilepsy were examined. After implantation, the position of subdural electrodes was evaluated by 3.0 T-MRI and thin-slice CCT for 3D reconstruction. Localization of electrodes was performed with the volume-rendering technique. Post-implantation and pre-explantation 1.5 T-iopMRI scans were coregistered with the 3D reconstructions to determine the extent of electrode dislocation.

RESULTS

Intraoperative MRI at the time of explantation revealed a relevant electrode shift in one patient (8%) of 10 mm. Median electrode displacement was 1.7 ± 2.6 mm with a coregistration error of 1.9 ± 0.7 mm. The median accuracy of the neuronavigation system was 2.2 ± 0.9 mm. Six of twelve patients undergoing resective surgery were seizure free (Engel class 1A, median follow-up 37.5 ± 11.8 months).

CONCLUSION

Comparison of pre-explantation and post-implantation iopMRI scans with CT/MRI data using the volume-rendering technique resulted in an accurate placement of electrodes. In one patient with a considerable electrode dislocation, the surgical approach and extent was changed due to the detected electrode shift.

ABBREVIATIONS

ECoG: electrocorticography; EZ: epileptogenic zone; iEEG: invasive EEG; iopMRI: intraoperative MRI; MEG: magnetoencephalography; PET: positron emission tomography; SPECT: single photon emission computed tomography; 3D: three-dimensional.

Intracranial high-γ connectivity distinguishes wakefulness from sleep

Neural synchrony in the γ-band is considered a fundamental process in cortical computation and communication and it has also been proposed as a crucial correlate of consciousness. However, the latter claim remains inconclusive, mainly due to methodological limitations, such as the spectral constraints of scalp-level electroencephalographic recordings or volume-conduction confounds. Here, we circumvented these caveats by comparing γ-band connectivity between two global states of consciousness via intracranial electroencephalography (iEEG), which provides the most reliable measurements of high-frequency activity in the human brain. Non-REM Sleep recordings were compared to passive-wakefulness recordings of the same duration in three subjects with surgically implanted electrodes. Signals were analyzed through the weighted Phase Lag Index connectivity measure and relevant graph theory metrics. We found that connectivity in the high-γ range (90-120 Hz), as well as relevant graph theory properties, were higher during wakefulness than during sleep and discriminated between conditions better than any other canonical frequency band. Our results constitute the first report of iEEG differences between wakefulness and sleep in the high-γ range at both local and distant sites, highlighting the utility of this technique in the search for the neural correlates of global states of consciousness.

Surface based electrode localization and standardized regions of interest for intracranial EEG

Intracranial recordings captured from subdural electrodes in patients with drug resistant epilepsy offer clinicians and researchers a powerful tool for examining neural activity in the human brain with high spatial and temporal precision. There are two major challenges, however, to interpreting these signals both within and across individuals. Anatomical distortions following implantation make accurately identifying the electrode locations difficult. In addition, because each implant involves a unique configuration, comparing neural activity across individuals in a standardized manner has been limited to broad anatomical regions such as cortical lobes or gyri. We address these challenges here by introducing a semi-automated method for localizing subdural electrode contacts to the unique surface anatomy of each individual, and by using a surface-based grid of regions of interest (ROIs) to aggregate electrode data from similar anatomical locations across individuals. Our localization algorithm, which uses only a postoperative CT and preoperative MRI, builds upon previous spring-based optimization approaches by introducing manually identified anchor points directly on the brain surface to constrain the final electrode locations. This algorithm yields an accuracy of 2 mm. Our surface-based ROI approach involves choosing a flexible number of ROIs with different spatial resolutions. ROIs are registered across individuals to represent identical anatomical locations while accounting for the unique curvature of each brain surface. This ROI based approach therefore enables group level statistical testing from spatially precise anatomical regions.

Objective 3D surface evaluation of intracranial electrophysiologic correlates of cerebral glucose metabolic abnormalities in children with focal epilepsy

To determine the spatial relationship between 2-deoxy-2[¹⁸ F]fluoro-D-glucose (FDG) metabolic and intracranial electrophysiological abnormalities in children undergoing two-stage epilepsy surgery, statistical parametric mapping (SPM) was used to correlate hypo- and hypermetabolic cortical regions with ictal and interictal electrocorticography (ECoG) changes mapped onto the brain surface. Preoperative FDG-PET scans of 37 children with intractable epilepsy (31 with non-localizing MRI) were compared with age-matched pseudo-normal pediatric control PET data. Hypo-/hypermetabolic maps were transformed to 3D-MRI brain surface to compare the locations of metabolic changes with electrode coordinates of the ECoG-defined seizure onset zone (SOZ) and interictal spiking. While hypometabolic clusters showed a good agreement with the SOZ on the lobar level (sensitivity/specificity = 0.74/0.64), detailed surface-distance analysis demonstrated that large portions of ECoG-defined SOZ and interictal spiking area were located at least 3 cm beyond hypometabolic regions with the same statistical threshold (sensitivity/specificity = 0.18-0.25/0.94-0.90 for overlap 3-cm distance); for a lower threshold, sensitivity for SOZ at 3 cm increased to 0.39 with a modest compromise of specificity. Performance of FDG-PET SPM was slightly better in children with smaller as compared with widespread SOZ. The results demonstrate that SPM utilizing age-matched pseudocontrols can reliably detect the lobe of seizure onset. However, the spatial mismatch between metabolic and EEG epileptiform abnormalities indicates that a more complete SOZ detection could be achieved by extending intracranial electrode coverage at least 3 cm beyond the metabolic abnormality. Considering that the extent of feasible electrode coverage is limited, localization information from other modalities is particularly important to optimize grid coverage in cases of large hypometabolic cortex. Hum Brain Mapp 38:3098-3112, 2017. © 2017 Wiley Periodicals, Inc.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.

Automatic and Precise Localization and Cortical Labeling of Subdural and Depth Intracranial Electrodes

Object: Subdural or deep intracerebral electrodes are essential in order to precisely localize epileptic zone in patients with medically intractable epilepsy. Precise localization of the implanted electrodes is critical to clinical diagnosing and treatment as well as for scientific studies. In this study, we sought to automatically and precisely extract intracranial electrodes using pre-operative MRI and post-operative CT images.

Method: The subdural and depth intracranial electrodes were readily detected using clustering-based segmentation. Depth electrodes were tracked by fitting a quadratic curve to account for potential bending during the neurosurgery. The identified electrodes can be manipulated using a graphic interface and labeled to cortical areas in individual native space based on anatomical parcellation and displayed in the volume and surface space.

Results: The electrodes' localizations were validated with high precision. The electrode coordinates were normalized to a standard space. Moreover, the probabilistic value being to a specific area or a functional network was provided.

Conclusions: We developed an integrative toolbox to reconstruct and label the intracranial electrodes implanted in the patients with medically intractable epilepsy. This toolbox provided a convenient way to allow inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature.

TIRDA Originating From Lateral Temporal Cortex in a Patient With mTLE Is Not Related to Hippocampal Activity

Electrophysiological studies have suggested that temporal intermittent rhythmic delta activity (TIRDA) has a localizing value similar to interictal spikes in patients with temporal lobe epilepsy and is associated with a favorable outcome after temporal lobectomy. However, it remains controversial whether TIRDA is an EEG marker for mesial or lateral temporal epileptogenesis. We simultaneously recorded scalp EEG and stereoencephalography in a patient with mesial temporal lobe epilepsy during epilepsy presurgical evaluation. Seizure onset was localized to the hippocampus. However, TIRDA originated from the lateral temporal cortex, and rhythmic delta activity was not observed concomitantly in the hippocampus. In addition, TIRDA was not associated with repetitive interictal spikes or subclinical seizures in the hippocampus as previously speculated. This case suggests that TIRDA can be an EEG marker that is independent of hippocampal activity and can represent temporal neocortical epileptogenesis.

Registering imaged ECoG electrodes to human cortex: A geometry-based technique

BACKGROUND

The accurate localization of implanted ECoG electrodes over the brain is of critical importance to invasive diagnostic work-up for the surgical treatment of intractable epileptic seizures. The implantation of subdural electrodes is an invasive procedure which typically introduces non-uniform deformations of a subject's brain, increasing the difficulty of determining the precise location of the electrodes vis-à-vis cortex. Formalization of this problem is used to define a novel solution for the optimal localization of subdural electrodes.

NEW METHOD

We demonstrate that nonlinear transformation is required to accurately register the implanted electrodes to the non-deformed pre-surgical cortical surface, and that this problem is accommodated by utilizing known features of electrode geometry. Techniques to register chronically implanted subdural electrodes to the undistorted brain image are described and evaluated using simulated and clinical data.

RESULTS

Principal Axis, our novel analysis method that estimates an electrode's orientation by the moment of inertia of the solid electrode volume, proved to be the most reliable measure in both the simulated and clinical datasets.

COMPARISON WITH EXISTING METHODS

This method of electrode translation along its principal axis is an improvement over other techniques, such as the limited view provided by intraoperative photography, and the image degradation inherent in post-operative MRI.

CONCLUSIONS

This technique compensates for alterations due to post-operative brain edema, and translates subdural electrodes to their original location on pre-operative MRI 3D models. This is helpful in the correct localization of seizure foci and functional mapping of epilepsy patients.

Improved localization of implanted subdural electrode contacts on magnetic resonance imaging with an elastic image fusion algorithm in an invasive electroencephalography recording

BACKGROUND

Accurate projection of implanted subdural electrode contacts in presurgical evaluation of pharmacoresistant epilepsy cases by invasive electroencephalography is highly relevant. Linear fusion of computed tomography and magnetic resonance images may display the contacts in the wrong position as a result of brain shift effects.

OBJECTIVE

A retrospective study in 5 patients with pharmacoresistant epilepsy was performed to evaluate whether an elastic image fusion algorithm can provide a more accurate projection of the electrode contacts on the preimplantation magnetic resonance images compared with linear fusion.

METHODS

An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF), and a standard linear fusion algorithm were used on preoperative magnetic resonance images and postimplantation computed tomography scans. Vertical correction of virtual contact positions, total virtual contact shift, corrections of midline shift, and brain shifts caused by pneumocephalus were measured.

RESULTS

Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7 mm (SD, 1.25 mm) was corrected to 0.4 mm (SD, 0.8 mm) after AEF and to 0.0 mm (SD, 0 mm) after GEF. Median virtual distances between contacts and cortical surface were corrected by a significant amount, from 2.3 mm after linear fusion algorithm to 0.0 mm after AEF and GEF (P < .001). Mean total relative corrections of 3.1 mm (SD, 1.85 mm) after AEF and 3.0 mm (SD, 1.77 mm) after GEF were achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumocephalus.

CONCLUSION

The technique provided a clear improvement in fusion of preimplantation and postimplantation scans, although the accuracy is difficult to evaluate.

An open-source automated platform for three-dimensional visualization of subdural electrodes using CT-MRI coregistration

OBJECTIVE

Visualizing implanted subdural electrodes in three-dimensional (3D) space can greatly aid in planning, executing, and validating resection in epilepsy surgery. Coregistration software is available, but cost, complexity, insufficient accuracy, or validation limit adoption. We present a fully automated open-source application, based on a novel method using postimplant computerized tomography (CT) and postimplant magnetic resonance (MR) images, for accurately visualizing intracranial electrodes in 3D space.

METHODS

CT-MR rigid brain coregistration, MR nonrigid registration, and prior-based segmentation were carried out on seven patients. Postimplant CT, postimplant MR, and an external labeled atlas were then aligned in the same space. The coregistration algorithm was validated by manually marking identical anatomic landmarks on the postimplant CT and postimplant MR images. Following coregistration, distances between the center of the landmark masks on the postimplant MR and the coregistered CT images were calculated for all subjects. Algorithms were implemented in open-source software and translated into a "drag and drop" desktop application for Apple Mac OS X.

RESULTS

Despite postoperative brain deformation, the method was able to automatically align intrasubject multimodal images and segment cortical subregions, so that all electrodes could be visualized on the parcellated brain. Manual marking of anatomic landmarks validated the coregistration algorithm with a mean misalignment distance of 2.87 mm (standard deviation 0.58 mm)between the landmarks. Software was easily used by operators without prior image processing experience.

SIGNIFICANCE

We demonstrate an easy to use, novel platform for accurately visualizing subdural electrodes in 3D space on a parcellated brain. We rigorously validated this method using quantitative measures. The method is unique because it involves no preprocessing, is fully automated, and freely available worldwide. A desktop application, as well as the source code, are both available for download on the International Epilepsy Electrophysiology Portal (https://www.ieeg.org) for use and interactive refinement.

Standardization of terminology in stereotactic radiosurgery: Report from the Standardization Committee of the International Leksell Gamma Knife Society

Object

This report has been prepared to ensure more uniform reporting of Gamma Knife radiosurgery treatment parameters by identifying areas of controversy, confusion, or imprecision in terminology and recommending standards.

Methods

Several working group discussions supplemented by clarification via email allowed the elaboration of a series of provisional recommendations. These were also discussed in open session at the 16th International Leksell Gamma Knife Society Meeting in Sydney, Australia, in March 2012 and approved subject to certain revisions and the performance of an Internet vote for approval from the whole Society. This ballot was undertaken in September 2012.

Results

The recommendations in relation to volumes are that Gross Target Volume (GTV) should replace Target Volume (TV); Prescription Isodose Volume (PIV) should generally be used; the term Treated Target Volume (TTV) should replace TVPIV, GTV in PIV, and so forth; and the Volume of Accepted Tolerance Dose (VATD) should be used in place of irradiated volume. For dose prescription and measurement, the prescription dose should be supplemented by the Absorbed Dose, or DV% (for example, D95%), the maximum and minimum dose should be related to a specific tissue volume (for example, D2% or preferably D1 mm3), and the median dose (D50%) should be recorded routinely. The Integral Dose becomes the Total Absorbed Energy (TAE). In the assessment of planning quality, the use of the Target Coverage Ratio (TTV/ GTV), Paddick Conformity Index (PCI = TTV2/[GTV · PIV]), New Conformity Index (NCI = [GTV · PIV]/TTV2), Selectivity Index (TTV/PIV), Homogeneity Index (HI = [D2% –D98%]/D50%), and Gradient Index (GI = PIV0.5/PIV) are reemphasized. In relation to the dose to Organs at Risk (OARs), the emphasis is on dose volume recording of the VATD or the dose/volume limit (for example, V10) in most cases, with the additional use of a Maximum Dose to a small volume (such as 1 mm3) and/or a Point Dose and Mean Point Dose in certain circumstances, particularly when referring to serial organs. The recommendations were accepted by the International Leksell Gamma Knife Society by a vote of 92% to 8%.

Conclusions

An agreed-upon and uniform terminology and subsequent standardization of certain methods and procedures will advance the clinical science of stereotactic radiosurgery.

MULTI-MODALITY IMAGE REGISTRATION FOR SUBDURAL ELECTRODE LOCALIZATION

Surgical treatment has been proved to be an effective way to control seizures for some kinds of intractable epilepsy. The electrocorticogram (ECoG) recorded from subdural electrodes has become an important technique for defining epileptogenic zones before surgery in clinical practice. The exact location of subdural electrodes has to be determined to establish the connection between electrodes and epileptogenic zones. Artifacts caused by the electrodes can severely affect the quality of CT imaging and sequentially image registration. In this paper, we discussed the performance of mean squares and the Mattes mutual information metric methods in multimodal image registration for subdural electrode localization. Since the skull can be regarded as a rigid body, rigid registration is sufficient for the purpose of subdural electrode localization. The vital parameter for the rigid registration is rotation. The translation result depends on the result of rotation. Both the methods performed well in the determination of the rotation center. Rotation angles of different image pairs of the same volume pair fluctuated a lot. Based on the image acquisition process, we assume that the images within the same volume pair should have the same transformation parameters for registration. Results show that the mean rotation angles of images within one dataset are approximate to the manual results that are considered to be the actual result for registration despite their fluctuation range.

Localizing ECoG electrodes on the cortical anatomy without post-implantation imaging

INTRODUCTION

Electrocorticographic (ECoG) grids are placed subdurally on the cortex in people undergoing cortical resection to delineate eloquent cortex. ECoG signals have high spatial and temporal resolution and thus can be valuable for neuroscientific research. The value of these data is highest when they can be related to the cortical anatomy. Existing methods that establish this relationship rely either on post-implantation imaging using computed tomography (CT), magnetic resonance imaging (MRI) or X-Rays, or on intra-operative photographs. For research purposes, it is desirable to localize ECoG electrodes on the brain anatomy even when post-operative imaging is not available or when intra-operative photographs do not readily identify anatomical landmarks.

METHODS

We developed a method to co-register ECoG electrodes to the underlying cortical anatomy using only a pre-operative MRI, a clinical neuronavigation device (such as BrainLab VectorVision), and fiducial markers. To validate our technique, we compared our results to data collected from six subjects who also had post-grid implantation imaging available. We compared the electrode coordinates obtained by our fiducial-based method to those obtained using existing methods, which are based on co-registering pre- and post-grid implantation images.

RESULTS

Our fiducial-based method agreed with the MRI-CT method to within an average of 8.24 mm (mean, median = 7.10 mm) across 6 subjects in 3 dimensions. It showed an average discrepancy of 2.7 mm when compared to the results of the intra-operative photograph method in a 2D coordinate system. As this method does not require post-operative imaging such as CTs, our technique should prove useful for research in intra-operative single-stage surgery scenarios. To demonstrate the use of our method, we applied our method during real-time mapping of eloquent cortex during a single-stage surgery. The results demonstrated that our method can be applied intra-operatively in the absence of post-operative imaging to acquire ECoG signals that can be valuable for neuroscientific investigations.

Electrode localization for planning surgical resection of the epileptogenic zone in pediatric epilepsy

PURPOSE

In planning for a potentially curative resection of the epileptogenic zone in patients with pediatric epilepsy, invasive monitoring with intracranial EEG is often used to localize the seizure onset zone and eloquent cortex. A precise understanding of the location of subdural strip and grid electrodes on the brain surface, and of depth electrodes in the brain in relationship to eloquent areas is expected to facilitate pre-surgical planning.

METHODS

We developed a novel algorithm for the alignment of intracranial electrodes, extracted from post-operative CT, with pre-operative MRI. Our goal was to develop a method of achieving highly accurate localization of subdural and depth electrodes, in order to facilitate surgical planning. Specifically, we created a patient-specific 3D geometric model of the cortical surface from automatic segmentation of a pre-operative MRI, automatically segmented electrodes from post-operative CT, and projected each set of electrodes onto the brain surface after alignment of the CT to the MRI. Also, we produced critical visualization of anatomical landmarks, e.g., vasculature, gyri, sulci, lesions, or eloquent cortical areas, which enables the epilepsy surgery team to accurately estimate the distance between the electrodes and the anatomical landmarks, which might help for better assessment of risks and benefits of surgical resection.

RESULTS

Electrode localization accuracy was measured using knowledge of the position of placement from 2D intra-operative photographs in ten consecutive subjects who underwent intracranial EEG for pediatric epilepsy. Average spatial accuracy of localization was 1.31 ± 0.69 mm for all 385 visible electrodes in the photos.

CONCLUSIONS

In comparison with previously reported approaches, our algorithm is able to achieve more accurate alignment of strip and grid electrodes with minimal user input. Unlike manual alignment procedures, our algorithm achieves excellent alignment without time-consuming and difficult judgements from an operator.

Recursive grid partitioning on a cortical surface model: an optimized technique for the localization of implanted subdural electrodes

Object

Precise localization of subdural electrodes (SDEs) is essential for the interpretation of data from intracranial electrocorticography recordings. Blood and fluid accumulation underneath the craniotomy flap leads to a nonlinear deformation of the brain surface and of the SDE array on postoperative CT scans and adversely impacts the accurate localization of electrodes located underneath the craniotomy. Older methods that localize electrodes based on their identification on a postimplantation CT scan with coregistration to a preimplantation MR image can result in significant problems with accuracy of the electrode localization. The authors report 3 novel methods that rely on the creation of a set of 3D mesh models to depict the pial surface and a smoothed pial envelope. Two of these new methods are designed to localize electrodes, and they are compared with 6 methods currently in use to determine their relative accuracy and reliability.

Methods

The first method involves manually localizing each electrode using digital photographs obtained at surgery. This is highly accurate, but requires time intensive, operator-dependent input. The second uses 4 electrodes localized manually in conjunction with an automated, recursive partitioning technique to localize the entire electrode array. The authors evaluated the accuracy of previously published methods by applying the methods to their data and comparing them against the photograph-based localization. Finally, the authors further enhanced the usability of these methods by using automatic parcellation techniques to assign anatomical labels to individual electrodes as well as by generating an inflated cortical surface model while still preserving electrode locations relative to the cortical anatomy.

Results

The recursive grid partitioning had the least error compared with older methods (672 electrodes, 6.4-mm maximum electrode error, 2.0-mm mean error, p < 10−18). The maximum errors derived using prior methods of localization ranged from 8.2 to 11.7 mm for an individual electrode, with mean errors ranging between 2.9 and 4.1 mm depending on the method used. The authors also noted a larger error in all methods that used CT scans alone to localize electrodes compared with those that used both postoperative CT and postoperative MRI. The large mean errors reported with these methods are liable to affect intermodal data comparisons (for example, with functional mapping techniques) and may impact surgical decision making.

Conclusions

The authors have presented several aspects of using new techniques to visualize electrodes implanted for localizing epilepsy. The ability to use automated labeling schemas to denote which gyrus a particular electrode overlies is potentially of great utility in planning resections and in corroborating the results of extraoperative stimulation mapping. Dilation of the pial mesh model provides, for the first time, a sense of the cortical surface not sampled by the electrode, and the potential roles this “electrophysiologically hidden” cortex may play in both eloquent function and seizure onset.

Localization of dense intracranial electrode arrays using magnetic resonance imaging

Intracranial electrode arrays are routinely used in the pre-surgical evaluation of patients with medically refractory epilepsy, and recordings from these electrodes have been increasingly employed in human cognitive neurophysiology due to their high spatial and temporal resolution. For both researchers and clinicians, it is critical to localize electrode positions relative to the subject-specific neuroanatomy. In many centers, a post-implantation MRI is utilized for electrode detection because of its higher sensitivity for surgical complications and the absence of radiation. However, magnetic susceptibility artifacts surrounding each electrode prohibit unambiguous detection of individual electrodes, especially those that are embedded within dense grid arrays. Here, we present an efficient method to accurately localize intracranial electrode arrays based on pre- and post-implantation MR images that incorporates array geometry and the individual's cortical surface. Electrodes are directly visualized relative to the underlying gyral anatomy of the reconstructed cortical surface of individual patients. Validation of this approach shows high spatial accuracy of the localized electrode positions (mean of 0.96 mm ± 0.81 mm for 271 electrodes across 8 patients). Minimal user input, short processing time, and utilization of radiation-free imaging are strong incentives to incorporate quantitatively accurate localization of intracranial electrode arrays with MRI for research and clinical purposes. Co-registration to a standard brain atlas further allows inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature.

Microelectrode recording duration and spatial density constraints for automatic targeting of the subthalamic nucleus

BACKGROUND

Accurate detection of the boundaries of the subthalamic nucleus (STN) in deep brain stimulation (DBS) surgery using microelectrode recording (MER) is considered to refine localization and may therefore improve clinical outcome. However, MER tends to extend operation time and its cost-utility balance has been debated.

OBJECTIVES

To quantify the tradeoff between accuracy of STN localization and the spatial and temporal parameters of MER that effect the operation time using an automated detection method.

METHODS

We retrospectively estimated the accuracy of STN detection on data from 100 microelectrode trajectories. Our dense (average step = 0.12 mm) and long (average duration = 22.5 s) MER data was downsampled in the spatial and temporal domains. Then, the STN borders were detected automatically on both the downsampled and original data and compared to each other.

RESULTS

With a recording duration of 16 s, average accuracy for detecting STN entry ranged from 0.06 mm for a 0.1-mm step to 0.51 mm for a 1.0-mm step. Smaller effects were found along the temporal axis. For example, a 0.1-mm recording step yielded an STN entry average accuracy ranging from 0.06 mm for a 16-second recording duration to 0.16 mm for 0.1 s.

CONCLUSIONS

STN entry detection error was about half of the step size. Sampling duration of STN activity can be minimized to 1 s/record without compromising accuracy. We conclude that bilateral DBS surgery time utilizing MER may be significantly shortened without compromising targeting accuracy.

Intracranial EEG surface renderings: new insights into normal and abnormal brain function

Intracranial electro-encephalography (icEEG) provides a unique opportunity to record directly from the human brain and is clinically important for planning epilepsy surgery. However, traditional visual analysis of icEEG is often challenging. The typical simultaneous display of multiple electrode channels can prevent an in-depth understanding of the spatial-time course of brain activity. In recent decades, advances in the field of neuroimaging have provided powerful new tools for the analysis and display of signals in the brain. These methods can now be applied to icEEG to map electrical signal information onto a three-dimensional rendering of a patient's cortex and graphically observe the changes in voltage over time. This approach provides rapid visualization of seizures and normal activity propagating over the brain surface and can also illustrate subtle changes that might be missed by traditional icEEG analysis. In addition, the direct mapping of signal information onto accurate anatomical structures can assist in the precise targeting of sites for epilepsy surgery and help correlate electrical activity with behavior. Bringing icEEG data into a standardized anatomical space will also enable neuroimaging methods of statistical analysis to be applied. As new technologies lead to a dramatic increase in the rate of data acquisition, these novel visualization and analysis techniques will play an important role in processing the valuable information obtained through icEEG.

Individualized localization and cortical surface-based registration of intracranial electrodes

In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.

Three-dimensional visualization of subdural electrodes for presurgical planning

BACKGROUND

Accurate localization and visualization of subdural electrodes implanted for intracranial electroencephalography in cases of medically refractory epilepsy remains a challenging clinical problem.

OBJECTIVE

We introduce a technique for creating accurate 3-dimensional (3D) brain models with electrode overlays, ideal for resective surgical planning.

METHODS

Our procedure uses postimplantation magnetic resonance imaging (MRI) and computed tomographic (CT) imaging to create 3D models of compression-affected brain combined with intensity-thresholded CT-derived electrode models using freely available software. Footprints, or "shadows," beneath electrodes are also described for better visualization of sulcus-straddling electrodes. Electrode models were compared with intraoperative photography for validation.

RESULTS

Realistic representations of intracranial electrode positions on patient-specific postimplantation MRI brain renderings were reliably created and proved accurate when compared with photographs. Electrodes placed interhemispherically were also visible with our rendering technique. Electrode shadows were useful in locating electrodes that straddle sulci.

CONCLUSION

We present an accurate method for visualizing subdural electrodes on brain compression effected 3D models that serves as an ideal platform for surgical planning.

3D visualization of subdural electrode shift as measured at craniotomy reopening

PURPOSE

Subdural electrodes are implanted for recording intracranial EEG (iEEG) in cases of medically refractory epilepsy as a means to locate cortical regions of seizure onset amenable to surgical resection. Without the aid of imaging-derived 3D electrode models for surgical planning, surgeons have relied on electrodes remaining stationary from the time between placement and follow-up resection. This study quantifies electrode shift with respect to the cortical surface occurring between electrode placement and subsequent reopening.

METHODS

CT and structural MRI data were gathered following electrode placement on 10 patients undergoing surgical epilepsy treatment. MRI data were used to create patient specific post-grid 3D reconstructions of cortex, while CT data were co-registered to the MRI and thresholded to reveal electrodes only. At the time of resective surgery, the craniotomy was reopened and electrode positions were determined using intraoperative navigational equipment. Changes in position were then calculated between CT coordinates and intraoperative electrode coordinates.

RESULTS

Five out of ten patients showed statistically significant overall magnitude differences in electrode positions (mean: 7.2mm), while 4 exhibited significant decompression based shift (mean: 4.7mm), and 3 showed significant shear displacement along the surface of the brain (mean: 7.1mm).

DISCUSSION

Shift in electrode position with respect to the cortical surface has never been precisely measured. We show that in 50% of our cases statistically significant shift occurred. These observations demonstrate the potential utility of complimenting electrode position measures at the reopening of the craniotomy with 3D electrode and brain surface models derived from post-implantation CT and MR imaging for better definition of surgical boundaries.

Interictal regional delta slowing is an EEG marker of epileptic network in temporal lobe epilepsy

PURPOSE

Several studies have suggested that interictal regional delta slowing (IRDS) carries a lateralizing and localizing value similar to interictal spikes and is associated with favorable surgical outcomes in patients with temporal lobe epilepsy (TLE). However, whether IRDS reflects structural dysfunction or underlying epileptic activity remains controversial. The objective of this study is to determine the cortical electroencephalography (EEG) correlates of scalp-recorded IRDS, in so doing, to further understand its clinical and biologic significances.

METHODS

We examined the cortical EEG substrates of IRDS with electrocorticography (ECoG-IRDS) and delineated the spatiotemporal relationship between ECoG-IRDS and both interictal and ictal discharges by recording simultaneously scalp and intracranial EEG in 18 presurgical candidates with TLE.

KEY FINDINGS

Our results demonstrated that ECoG-IRDS is typically a mixture of delta/theta slowing and spike-wave potentials. ECoG-IRDS was predominantly recorded from basal and anterolateral temporal cortex, occasionally in mesial, posterior temporal, and extratemporal regions. Abundant IRDS was most commonly observed in patients with neocortical temporal lobe epilepsy (NTLE), whereas infrequent to moderate IRDS was usually observed in patients with mesial temporal lobe epilepsy (MTLE). The anatomic distribution of ECoG-IRDS was highly correlated with the irritative and seizure-onset zones in 10 patients with NTLE. However, it was poorly correlated with the irritative and seizure-onset zones in the 8 patients with MTLE.

SIGNIFICANCE

These findings demonstrate that IRDS is an EEG marker of epileptic network in patients with TLE. Although IRDS and interictal/ictal discharges likely arise from the same neocortical generator in patients with NTLE, IRDS in patients with MTLE may reflect a network disease that involves temporal neocortex.

Co-registration of Sequential Multidetector Computed Tomography Studies for the Evaluation of Surgical Instrumentation following Resection of Spinal Tumors

Surgical resection of spinal tumors involves complex reconstructive procedures. The stability and integrity of the surgical construct are evaluated with multidetector computed tomography (MDCT). As coregistration, or fusion, of different imaging modalities, especially positron emission tomography/computed tomography (PET/CT), is common practice, we sought to determine if this technique could be applied to sequential, postoperative MDCT studies of the spine. Herein, we demonstrate that by utilizing the Hermes workstation, co-registration of MDCT spine studies can be performed. This technique allows sequential MDCT examinations of the post-operative spine to be viewed together as one study and may aid in evaluation of the position and integrity of the surgical construct over time. Further study and refinement of this technique will be necessary before clinical implementation.

Data-guide for brain deformation in surgery: comparison of linear and nonlinear models

Background

Pre-operative imaging devices generate high-resolution images but intra-operative imaging devices generate low-resolution images. To use high-resolution pre-operative images during surgery, they must be deformed to reflect intra-operative geometry of brain.

Methods

We employ biomechanical models, guided by low resolution intra-operative images, to determine location of normal and abnormal regions of brain after craniotomy. We also employ finite element methods to discretize and solve the related differential equations. In the process, pre- and intra-operative images are utilized and corresponding points are determined and used to optimize parameters of the models. This paper develops a nonlinear model and compares it with linear models while our previous work developed and compared linear models (mechanical and elastic).

Results

Nonlinear model is evaluated and compared with linear models using simulated and real data. Partial validation using intra-operative images indicates that the proposed models reduce the localization error caused by brain deformation after craniotomy.

Conclusions

The proposed nonlinear model generates more accurate results than the linear models. When guided by limited intra-operative surface data, it predicts deformation of entire brain. Its execution time is however considerably more than those of linear models.

A head phantom prototype to verify subdural electrode localization tools in epilepsy surgery

When planning epilepsy surgery, the position of subdural electrodes in relation to the cortex is crucial. Electrodes may dislocate after implantation. Neurosurgeons are highly interested in the accuracy of methods that visualize these electrodes. In order to determine the accuracy of an electrode visualization method, we have developed a physical head phantom and evaluated our new method of subdural electrode localization. This method projects automatically segmented electrodes of a preimplantation computed tomography (CT) data set onto the segmented brain surface of a postimplantation magnetic resonance imaging (MRI) data set within 2 to 5 min. The phantom consists of a skull, an adipose layer for skin replication, and a deformable brain. It further contains gyri and sulci structures, composed of gelatin and different additives used as phantom material for white matter, gray matter, and cerebrospinal fluid. The phantom allows a well-defined displacement of an "implanted" electrode grid perpendicular to the brain surface. By using the phantom data, we demonstrated that our electrode visualization tool did in fact function accurately. The image contrasts between different phantom materials in MRI and CT phantom data sets were similar to patient data sets. The phantom appears suitable for obtaining a more complex patient data replication, as well as for simulating different deformation scenarios.