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Sommer B, Rampp S, Doerfler A, Stefan H, Hamer HM, Buchfelder M, Roessler K. Investigation of subdural electrode displacement in invasive epilepsy surgery workup using neuronavigation and intraoperative MRI. Neurol Res 2018; 40:811-821. [PMID: 29916770 DOI: 10.1080/01616412.2018.1484588] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
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.
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Affiliation(s)
- Bjoern Sommer
- a Department of Neurosurgery , University Hospital Erlangen , Erlangen , Germany
| | - Stefan Rampp
- a Department of Neurosurgery , University Hospital Erlangen , Erlangen , Germany
| | - Arnd Doerfler
- b Department of Neuroradiology , University Hospital Erlangen , Erlangen , Germany
| | - Hermann Stefan
- c Department of Neurology , Epilepsy Center, University Hospital Erlangen , Erlangen , Germany
| | - Hajo M Hamer
- c Department of Neurology , Epilepsy Center, University Hospital Erlangen , Erlangen , Germany
| | - Michael Buchfelder
- a Department of Neurosurgery , University Hospital Erlangen , Erlangen , Germany
| | - Karl Roessler
- a Department of Neurosurgery , University Hospital Erlangen , Erlangen , Germany
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LaPlante RA, Tang W, Peled N, Vallejo DI, Borzello M, Dougherty DD, Eskandar EN, Widge AS, Cash SS, Stufflebeam SM. The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes. Int J Comput Assist Radiol Surg 2016; 12:1829-1837. [PMID: 27915398 DOI: 10.1007/s11548-016-1504-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 11/07/2016] [Indexed: 10/20/2022]
Abstract
PURPOSE Existing methods for sorting, labeling, registering, and across-subject localization of electrodes in intracranial encephalography (iEEG) may involve laborious work requiring manual inspection of radiological images. METHODS We describe a new open-source software package, the interactive electrode localization utility which presents a full pipeline for the registration, localization, and labeling of iEEG electrodes from CT and MR images. In addition, we describe a method to automatically sort and label electrodes from subdural grids of known geometry. RESULTS We validated our software against manual inspection methods in twelve subjects undergoing iEEG for medically intractable epilepsy. Our algorithm for sorting and labeling performed correct identification on 96% of the electrodes. CONCLUSIONS The sorting and labeling methods we describe offer nearly perfect performance and the software package we have distributed may simplify the process of registering, sorting, labeling, and localizing subdural iEEG grid electrodes by manual inspection.
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Affiliation(s)
- Roan A LaPlante
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 13th Street, Charlestown, MA, USA.
| | - Wei Tang
- Department of Neurobiology and Anatomy, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Noam Peled
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Deborah I Vallejo
- Cortical Physiology Laboratory, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mia Borzello
- Cortical Physiology Laboratory, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Emad N Eskandar
- Department of Neurological Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sydney S Cash
- Cortical Physiology Laboratory, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA.,Harvard-MIT Health Sciences and Technology, Cambridge, MA, USA
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Dong S, Liu Y, Cai L, Bai M, Yan H. MULTI-MODALITY IMAGE REGISTRATION FOR SUBDURAL ELECTRODE LOCALIZATION. BIOMEDICAL ENGINEERING: APPLICATIONS, BASIS AND COMMUNICATIONS 2014. [DOI: 10.4015/s1016237214500513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
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.
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Affiliation(s)
- Shuo Dong
- Department of Medical Engineering, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Yuan Liu
- Department of Medical Engineering, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Lixin Cai
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Mei Bai
- Department of Medical Engineering, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Hanmin Yan
- Department of Medical Engineering, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
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Rowland NC, Miller KJ, Starr PA. Three-Dimensional Accuracy of ECOG Strip Electrode Localization Using Coregistration of Preoperative MRI and Intraoperative Fluoroscopy. Stereotact Funct Neurosurg 2014; 92:8-16. [DOI: 10.1159/000350027] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2012] [Accepted: 02/19/2013] [Indexed: 11/19/2022]
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Taimouri V, Akhondi-Asl A, Tomas-Fernandez X, Peters JM, Prabhu SP, Poduri A, Takeoka M, Loddenkemper T, Bergin AMR, Harini C, Madsen JR, Warfield SK. Electrode localization for planning surgical resection of the epileptogenic zone in pediatric epilepsy. Int J Comput Assist Radiol Surg 2013; 9:91-105. [PMID: 23793723 DOI: 10.1007/s11548-013-0915-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Accepted: 06/10/2013] [Indexed: 10/26/2022]
Abstract
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.
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Yang AI, Wang X, Doyle WK, Halgren E, Carlson C, Belcher TL, Cash SS, Devinsky O, Thesen T. Localization of dense intracranial electrode arrays using magnetic resonance imaging. Neuroimage 2012; 63:157-165. [PMID: 22759995 PMCID: PMC4408869 DOI: 10.1016/j.neuroimage.2012.06.039] [Citation(s) in RCA: 90] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2012] [Revised: 06/17/2012] [Accepted: 06/20/2012] [Indexed: 10/28/2022] Open
Abstract
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.
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Affiliation(s)
- Andrew I. Yang
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
| | - Xiuyuan Wang
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
| | - Werner K. Doyle
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
- Department of Neurosurgery, New York University School of Medicine, New York, NY 10016, USA
| | - Eric Halgren
- Department of Radiology, University of California at San Diego, San Diego, CA 92093, USA
- Department of Neurosciences, University of California at San Diego, San Diego, CA 92093, USA
- Department of Psychiatry, University of California at San Diego, San Diego, CA 92093, USA
| | - Chad Carlson
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
| | - Thomas L. Belcher
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
| | - Sydney S. Cash
- Department of Neurology, Epilepsy Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Orrin Devinsky
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
- Department of Neurosurgery, New York University School of Medicine, New York, NY 10016, USA
| | - Thomas Thesen
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016, USA
- Department of Radiology, University of California at San Diego, San Diego, CA 92093, USA
- Department of Neurosciences, University of California at San Diego, San Diego, CA 92093, USA
- Department of Psychiatry, University of California at San Diego, San Diego, CA 92093, USA
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