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SPEL – SOFTWARE PLATFORM FOR ELECTRODES LOCALIZATION. A TOOL TO AUTOMATICALLY LOCALIZE SUBDURAL ELECTRODES IN THE PRE-SURGICAL EVALUATION OF EPILEPSY PATIENTS

Luigi Pavone1*, Giancarlo Di Gennaro2, Vincenzo Esposito2 and Fabio Sebastiano1
  • 1 IRCCS Istituto Neurologico Mediterraneo Neuromed, Bioengineering, Italy
  • 2 IRCCS Istituto Neurologico Mediterraneo Neuromed, Epilepsy Surgery Unit, Italy

Patients with drug-resistant epilepsy often require intracranial EEG investigations by using subdural electrodes implanted directly over their cortical surface. These electrodes allow the recording of ElectroCorticoGraphic (ECoG) activity, the mapping of brain functions, the localization of epileptic foci and the planning of the surgery. To ensure a correct understanding of the ECoG data, it is necessary to know the exact position of the electrodes on the brain, in order to identify the area to be removed, minimizing the volume of tissue that is removed and avoiding the possibility of removing tissue belong to eloquent cortex. Over the years, various techniques for the localization of subdural electrodes have been developed. Such methods include the use of lateral and anterior–posterior X-rays1, pre-operative MRI coregistered with a post-implantation CT2,4, fusion of post-implant MRI scan and CT scan3 and pre- and post-implantation MRI5. All the above techniques are semi-automatic, because require manual intervention of an expert user for image processing and often they require the use of external software for the detection and/or the visualization of the electrodes on the brain rendering. Wu et al.6 presented a fully automated open-source application, based upon a novel method using post-implant CT and post-implant MR images, for accurately visualizing intracranial electrodes in 3D space. This method uses post-implant MRI and this results in a further examination which the patient has to undergo during the pre-surgical process and in a subsequently higher amount of exposure to radiation, higher costs for the hospital and poor results in terms of usability. Furthermore, external software is required to visualize electrodes or to load images to be processed. We present here a software for subdural electrodes localization that allows to localize subdural electrodes, starting from pre-operative MRI and post-implant CT in DICOM (Digital Imaging and COmmunications in Medicine) format, retrieved directly from PACS (Picture Archiving and Communication System) system of the hospital. Our software consists of three different modules: one module that allows users to visualize and retrieve DICOM images from PACS server, one module that allows users to retrieve general informations and medical reports of the patient directly from RIS (Radiology Information System), and one module to perform image processing for electrodes localization. With respect to image processing module, the corresponding image processing pipeline consists of conversion of DICOM images to NIFTI (Neuroimaging Informatics Technology Initiative) format, correction of MR and CT images by means of Gaussian filters, coregistration of MRI and CT using Mutual Information8,9, the segmentation of MRI using Unified Segmentation10 in order to extract brain surface, automatic thresholding of CT image for electrodes extraction, creation of rendered brain surface using isosurface extraction method and the projection of extracted electrodes into brain surface. All these steps are fully automated, the user must query only the PACS database to retrieve DICOM images that will be used for image processing. If the user is not satisfied of electrodes extraction or if he want to visualize only a subset of implanted electrodes, there is also an optional step, with which user can select manually the electrodes he want to visualize on patient’s brain or simply refine electrodes extraction using a seed-based extraction. We have tested the software at Epilepsy Surgery Unit at IRCCS INM Neuromed, Pozzilli, Italy on six patients with medically-intractable epilepsy underwent invasive monitoring of the seizure focus prior to its surgical removal. Patients gave their informed consent, and all procedures were approved by the local Ethics Committee. Prior to electrode implantation, each patient underwent high resolution T1-weighted MRI. In each patient, arrays of platinum–iridium electrodes (Ad-Tech, Racine, WI, USA) embedded in a thin (0.5 mm) flexible silastic plate were placed over temporal, frontal, and parietal cortex. The implanted units had between 4 and 64 contacts in different configurations. After the craniotomy, each patient underwent post-operative CT in order to assess electrode placement. Once the images are stored in the local PACS database, user can connect to PACS, retrieve images and start image processing. The time required for the localization of all the electrodes, independently from the number of them, was about 15 minutes, using a workstation equipped with 8GB RAM and a Xeon E5-1620 3,6 GHz CPU. In order to assess the accuracy of image processing module in terms of localization, we compared 3D images of the brain with projected electrodes with digital intraoperative photos. We were able to localize all the electrodes on the cortex, except the ones under the bone flap and those implanted on the basal and medial cortical regions, which are impossible to visualize by means of intraoperative digital photography. The quantitative evaluation of the mismatch between the intraoperative photos and the 3D images was done by two expert neurologists and yielded a value of 1.8±0.13 mm. The software presented is totally automated and allows also to an unexpert user to perform electrodes localization without the intervention of expert users or the use of external softwares. In fact, the PACS module allows physician to directly query the PACS database and retrieve the images he needs for electrodes localization. It represents a useful tool for physicians, that can have access also to other informations, such as medical reports and general informations about the patient. Further improvements will be focused on so called “brain shift” problem due to leakage of CSF after opening of the dura, that may cause the exposed brain to move away from the skull and assume an unpredictable shape and also on automatic electrodes extraction from CT, in order to remove the presence of other material different from the electrodes, such as wires or other metal materials.

References

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6. Azarion AA, Wu J, Pearce A, Krish VT, Wagenaar J, Chen W, Zheng Y, Wang H, Lucas TH, Litt B, Gee JC, Davis KA. An open-source automated platform for three-dimensional visualization of subdural electrodes using CT-MRI coregistration. Epilepsia. 2014 Dec;55(12):2028-37. doi: 10.1111/epi.12827. Epub 2014 Nov 6.
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Keywords: subdural electrodes, electrodes localization, CT-MRI coregistration, electrocorticography, epilepsy surgery

Conference: SAN2016 Meeting, Corfu, Greece, 6 Oct - 9 Oct, 2016.

Presentation Type: Poster Presentation in SAN2016 Conference

Topic: Posters

Citation: Pavone L, Di Gennaro G, Esposito V and Sebastiano F (2016). SPEL – SOFTWARE PLATFORM FOR ELECTRODES LOCALIZATION. A TOOL TO AUTOMATICALLY LOCALIZE SUBDURAL ELECTRODES IN THE PRE-SURGICAL EVALUATION OF EPILEPSY PATIENTS. Conference Abstract: SAN2016 Meeting. doi: 10.3389/conf.fnhum.2016.220.00115

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Received: 29 Jul 2016; Published Online: 01 Aug 2016.

* Correspondence: Dr. Luigi Pavone, IRCCS Istituto Neurologico Mediterraneo Neuromed, Bioengineering, Pozzilli (IS), Isernia, 86077, Italy, pavone_luigi@hotmail.com