Literature DB >> 23793723

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

Vahid Taimouri1, Alireza Akhondi-Asl, Xavier Tomas-Fernandez, Jurriaan M Peters, Sanjay P Prabhu, Annapurna Poduri, Masanori Takeoka, Tobias Loddenkemper, Ann Marie R Bergin, Chellamani Harini, Joseph R Madsen, Simon K Warfield.   

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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Mesh:

Year:  2013        PMID: 23793723      PMCID: PMC3955988          DOI: 10.1007/s11548-013-0915-6

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  43 in total

1.  Digital photography and 3D MRI-based multimodal imaging for individualized planning of resective neocortical epilepsy surgery.

Authors:  Jörg Wellmer; Joachim von Oertzen; Carlo Schaller; Horst Urbach; Roy König; Guido Widman; Dirk Van Roost; Christian E Elger
Journal:  Epilepsia       Date:  2002-12       Impact factor: 5.864

2.  3-D reconstructed magnetic resonance imaging in localization of subdural EEG electrodes. Case illustration.

Authors:  Arto Immonen; Leena Jutila; Mervi Könönen; Esa Mervaala; Juhani Partanen; Matti Puranen; Jaakko Rinne; Aarne Ylinen; Matti Vapalahti
Journal:  Epilepsy Res       Date:  2003-04       Impact factor: 3.045

3.  Rapid and fully automated visualization of subdural electrodes in the presurgical evaluation of epilepsy patients.

Authors:  Dimitri Kovalev; Joachim Spreer; Jürgen Honegger; Josef Zentner; Andreas Schulze-Bonhage; Hans-Jürgen Huppertz
Journal:  AJNR Am J Neuroradiol       Date:  2005-05       Impact factor: 3.825

4.  Multi-modal volume registration by maximization of mutual information.

Authors:  W M Wells; P Viola; H Atsumi; S Nakajima; R Kikinis
Journal:  Med Image Anal       Date:  1996-03       Impact factor: 8.545

5.  Effectiveness of first antiepileptic drug.

Authors:  P Kwan; M J Brodie
Journal:  Epilepsia       Date:  2001-10       Impact factor: 5.864

6.  Simultaneous truth and performance level estimation through fusion of probabilistic segmentations.

Authors:  Alireza Akhondi-Asl; Simon K Warfield
Journal:  IEEE Trans Med Imaging       Date:  2013-06-04       Impact factor: 10.048

7.  How common are the "common" neurologic disorders?

Authors:  D Hirtz; D J Thurman; K Gwinn-Hardy; M Mohamed; A R Chaudhuri; R Zalutsky
Journal:  Neurology       Date:  2007-01-30       Impact factor: 9.910

8.  Intracranial Electrode Visualization in Invasive Pre-surgical Evaluation for Epilepsy.

Authors:  Yunhua Wang; Rajeev Agarwal; Dang Nguyen; Virgil Domocos; Jean Gotman
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2005

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

Authors:  James X Tao; Susan Hawes-Ebersole; Maria Baldwin; Sona Shah; Robert K Erickson; John S Ebersole
Journal:  Clin Neurophysiol       Date:  2009-03-04       Impact factor: 3.708

10.  Prevalence of epilepsy in Rochester, Minnesota: 1940-1980.

Authors:  W A Hauser; J F Annegers; L T Kurland
Journal:  Epilepsia       Date:  1991 Jul-Aug       Impact factor: 5.864

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  13 in total

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

Authors:  Xiaoyao Fan; David W Roberts; Yasmin Kamal; Jonathan D Olson; Keith D Paulsen
Journal:  Oper Neurosurg (Hagerstown)       Date:  2019-01-01       Impact factor: 2.703

Review 2.  Biomechanical modeling and computer simulation of the brain during neurosurgery.

Authors:  Karol Miller; Grand R Joldes; George Bourantas; Simon K Warfield; Damon E Hyde; Ron Kikinis; Adam Wittek
Journal:  Int J Numer Method Biomed Eng       Date:  2019-09-05       Impact factor: 2.747

3.  Passive fMRI mapping of language function for pediatric epilepsy surgical planning: validation using Wada, ECS, and FMAER.

Authors:  Ralph O Suarez; Vahid Taimouri; Katrina Boyer; Clemente Vega; Alexander Rotenberg; Joseph R Madsen; Tobias Loddenkemper; Frank H Duffy; Sanjay P Prabhu; Simon K Warfield
Journal:  Epilepsy Res       Date:  2014-09-28       Impact factor: 3.045

4.  Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning.

Authors:  John A Onofrey; Lawrence H Staib; Xenophon Papademetris
Journal:  IEEE Trans Med Imaging       Date:  2018-08-30       Impact factor: 10.048

5.  The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes.

Authors:  Roan A LaPlante; Wei Tang; Noam Peled; Deborah I Vallejo; Mia Borzello; Darin D Dougherty; Emad N Eskandar; Alik S Widge; Sydney S Cash; Steven M Stufflebeam
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-12-03       Impact factor: 2.924

6.  Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy.

Authors:  Margherita A G Matarrese; Alessandro Loppini; Saeed Jahromi; Eleonora Tamilia; Lorenzo Fabbri; Joseph R Madsen; Phillip L Pearl; Simonetta Filippi; Christos Papadelis
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2021-11

7.  iEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes.

Authors:  Guangye Li; Shize Jiang; Chen Chen; Peter Brunner; Zehan Wu; Gerwin Schalk; Liang Chen; Dingguo Zhang
Journal:  J Neural Eng       Date:  2019-12-23       Impact factor: 5.379

8.  Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients.

Authors:  John A Onofrey; Lawrence H Staib; Xenophon Papademetris
Journal:  Neuroimage Clin       Date:  2015-12-10       Impact factor: 4.881

9.  3D interactive tractography-informed resting-state fMRI connectivity.

Authors:  Maxime Chamberland; Michaël Bernier; David Fortin; Kevin Whittingstall; Maxime Descoteaux
Journal:  Front Neurosci       Date:  2015-08-11       Impact factor: 4.677

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

Authors:  Alejandro O Blenkmann; Holly N Phillips; Juan P Princich; James B Rowe; Tristan A Bekinschtein; Carlos H Muravchik; Silvia Kochen
Journal:  Front Neuroinform       Date:  2017-03-02       Impact factor: 4.081

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