HYPERACUTE STROKE EVOLUTION MAPPED BY INDIVIDUALIZED TOMOGRAPHIC qEEG

Abstract

Tomographic qEEG (qEEGt) has recently been introduced for the 3D in vivo visualization of the sources of abnormal EEG oscillations, including those induced by cerebral ischemia[1]. The cross-spectrum of the EEG is used to estimate source spectra at each voxel by means of Brain Electrical Tomography (BET), a Bayesian EEG inverse solution based on anatomical constraints and a suitable smoothness prior[2,3]. In turn the source spectra are log transformed and compared to age regressed population means and standard deviations by calculating the z score for each voxel and frequency. These values are then imaged using thresholded SPM procedures to map either excess or defect of oscillations at each frequency with respect to the normative database. qEEGT has been shown to correctly identify the anatomical locus of hyper-acute, acute and chronic stroke[1,4]. It was also shown that the use of statistical images in BET is mandatory due to a depth bias that is only compensated for by mapping statistics rather than raw values of source spectra. The studies just described however used the MNI probabilistic atlas as an anatomical constraint instead of the subjects own MRI and were not compared to either perfusion weighted (PWI) or diffusion weighted (DWI) images. The present study was designed to explore the feasibility of using the subject’s individual anatomy as a basis for qEEGT methods and compares the resulting electrophysiological image to DWI and PWI MRI. A major obstacle to be overcome is the lack of normative data for individual anatomy based BET. This was dealt with in this work by constructing SPM images of statistics that compare the EEG source spectra of the same subject at different time instants. More specifically: the log EEG source spectra for successive recordings were tested for equality by means of a voxel-wise t test. An example of this type of analysis is shown below. The patient was a woman who suffered from an acute ischemic stroke of the left Middle Cerebral Artery territory. She was seen to stumble and fall at home with a profound right-sided weakness, neglect and almost total aphasia. Her motor power improved in few hours, she was able to walk in 2 days. She had a mild to moderate dysphasia on discharge. EEGs recordings were obtained at 7 and 13 hours of the first symptoms, EEG cross-spectrum was estimated by means of multi-taper windows[5]; T2, DWI and PWI images were obtained at hospital admission and discharge. An MPRAGE image at discharge was used for brain segmentation and the construction of the forward model. The qEEGt images obtained (figure 1) indicate a highly significant increase of pathological delta oscillations (1.95 Hz), having excellent co localization with the area of increased transit time in the PWI.