Computational Intergration of Electrophysiological and Imaging Data Obtained During Invasive Pre-Surgical Assesment in Children.
Abstract number :
2.057
Submission category :
Year :
2000
Submission ID :
3216
Source :
www.aesnet.org
Presentation date :
12/2/2000 12:00:00 AM
Published date :
Dec 1, 2000, 06:00 AM
Authors :
Alki Liasis, Maureen Mills, Michael Owen, Stewart Boyd, Helen Cross, Great Ormond Street Hosp, London, United Kingdom; Great Ormond Street Hosp, Lonon, United Kingdom.
RATIONALE: Studies of neural information processing span a range of spatial and temporal scales, with no single methodology providing adequate functional organisation and dynamic information. Although techniques in computational intergrational have been available for some time due to their complex nature, have not become standard practice. In this study we describe the methodology used to achieve the co-registration of imaging and electrophysiological data that is obtained during pre-surgical assesment in children undergoing invasive elctroencephalographic (EEG) recordings. METHODS: Three patients undergoing invasive EEG sub-dural monitoring prior to epilepsy surgery were studied. Magnetic resonance images (MRI) were obtained prior to implantation of the sub-dural electrode arrays (SEA)and were used to reconstruct high spatial resolution three dimensional (3D) images of the individual patient's cortex. After implantation of the SEAs the contacts were co-registered to the 3D MRI images by extraction of their 3D co-ordinates from a post implantation computed tomography (CT). In addition to the CT, ictal and interictal single photon emission computed tomography (SPECT) image data sets were co-registered to the 3D MRI image. In all patients evoked potentials were recorded in order to confirm function of underlying cortex. RESULTS: Intracranial EEG recordings of seizures were used to established the epileptogenic and irrative zone in all patients while the recording of the evoked potentials and electrical stimulation was able to identify functional cortex. Co-registration of the electrophysiological findings to the structural and functional images enabled a direct correlation between the cortical function and physiology. All of the patients underwent successful localised cortical resections of the epileptogenic zones. CONCLUSIONS: This study has demonstrated that computational integration techniques can exploit the complimentary strengths of various structural and functional methodologies while overcoming their limitations.