Abstracts

PREDICTING POST-SURGICAL LANGUAGE OUTCOME WITH ECOG-BASED REAL-TIME FUNCTIONAL MAPPING (RTFM)

Abstract number : 2.255
Submission category : 5. Neuro Imaging
Year : 2014
Submission ID : 1868337
Source : www.aesnet.org
Presentation date : 12/6/2014 12:00:00 AM
Published date : Sep 29, 2014, 05:33 AM

Authors :
Milena Korostenskaja, Po Ching Chen, Christine Salinas, Michael Westerveld, J. Seo, Eduardo Castillo, Alex Schaal, Benjamin Edmonds, Gerwin Schalk, Peter Brunner, Mohammed Elsayed, James Baumgartner and Ki Hyeong Lee

Rationale: An electrocorticography (ECoG)-based functional mapping approaches recently showed great promise for guiding localization of eloquent cortex and/or supplementing currently utilized methods for functional language mapping in patients undergoing epilepsy surgery [1,2]. However, there are only limited data available determining the association between post-surgical language outcomes and ECoG-based functional mapping results [3]. Therefore, in this preliminary study we aimed to determine the predictive value of applied in real-time ECoG-based batteries (real-time functional mapping - RTFM) for post-surgical language outcomes. Methods: The RTFM, electrical cortical stimulation mapping (ESM) and neuropsychological post-surgical language outcome data of five patients who underwent surgical treatment for pharmaco-resistant epilepsy were reviewed. During RTFM procedure, patients' baseline ECoG activity was first recorded (g.USBamp, g.tec, Austria, sampling frequency 1200 Hz) for 6 minutes followed by administration of paradigms, assessing receptive and expressive language function. Sites of language-associated significant activity were determined. After that, surgical resection margins were established. A decision was made on whether RTFM results predicted post-surgical language outcome. The decision was based on whether brain tissue located underneath RTFM positive (RTFM(+)) electrodes was resected. The same decision was made based on ESM results. Afterwards, the predicted outcome (deficit/no deficit) was compared with real post-surgical language outcomes that became available after post-operative neuropsychological evaluation (3-12 month after surgery). Results: Our preliminary results with the simplistic prediction model indicate the following: (1) equal predictive value of ESM and RTFM for overall post-surgical language function; (2) higher ESM predictive value for expressive post-surgical language function (ESM/RTFM 50%/25%); and (3) higher RTFM predictive value for receptive post-surgical language function (ESM/RTFM 40%/60%). Conclusions: Our data suggest that RTFM may predict overall post-surgical language outcome to the similar extent as ESM. Importantly, RTFM may be a better predictor of post-surgical receptive language outcome than ESM. Conversely, ESM may be a better predictor of post-surgical expressive language outcome. Larger scale studies are needed to confirm or disproof these findings. Refinement of the simplistic prediction model is recommended. It may focus on magnitude of the significance of the RTFM(+) or ESM(+) electrodes in the resection zone, as well as their number. Moreover, not only physiological, but also clinical threshold must be taken into consideration, for example, when evaluating post-surgical language outcome values. Finally, relative risk of type 1 and 2 errors must be considered. References: 1. Korostenskaja M, et al. (2013) Clin EEG Neurosci 2013 Nov 28;45(3):205-211. 2. Prueckl R, et al. (2013) Conf Proc IEEE Eng Med Biol Soc 2013:6365-6368. 3. Korostenskaja M, et al. (2014) J Neurosurge​ry: Pediatrics (Accepted).
Neuroimaging