An integrated tool for automated visualization of subdural electrodes in epilepsy surgery evaluation

Quantification of Subdural Electrode Shift Between Initial Implantation, Postimplantation Computed Tomography, and Subsequent Resection Surgery

BACKGROUND

Subdural electrodes are often implanted for localization of epileptic regions. Postoperative computed tomography (CT) is typically acquired to locate electrode positions for planning any subsequent surgical resection. Electrodes are assumed to remain stationary between CT acquisition and resection surgery.

OBJECTIVE

To quantify subdural electrode shift that occurred between the times of implantation (Crani 1), postoperative CT acquisition, and resection surgery (Crani 2).

METHODS

Twenty-three patients in this case series undergoing subdural electrode implantation were evaluated. Preoperative magnetic resonance and postoperative CT were acquired and coregistered, and electrode positions were extracted from CT. Intraoperative positions of electrodes and the cortical surface were digitized with a coregistered stereovision system. Movement of the exposed cortical surface was also tracked, and change in electrode positions was calculated relative to both the skull and the cortical surface.

RESULTS

In the 23 cases, average shift of electrode positions was 8.0 ± 3.3 mm between Crani 1 and CT, 9.2 ± 3.7 mm between CT and Crani 2, and 6.2 ± 3.0 mm between Crani 1 and Crani 2. The average cortical shift was 4.7 ± 1.4 mm with 2.9 ± 1.0 mm in the lateral direction. The average shift of electrode positions relative to the cortical surface between Crani 1 and Crani 2 was 5.5 ± 3.7 mm.

CONCLUSION

The results show that electrodes shifted laterally not only relative to the skull, but also relative to the cortical surface, thereby displacing the electrodes from their initial placement on the cortex. This has significant clinical implications for resection based upon seizure activity and functional mapping derived from intracranial electrodes.

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.

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.

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.

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.