Summary: The diagnosis of nonconvulsive status epilepticus (NCSE) relies largely on electroencephalography (EEG) findings. The lack of a unified EEG terminology, and of evidence‐based EEG criteria, leads to varying criteria for and ability to diagnose NCSE. We propose a unified terminology and classification system for NCSE, using, as a template, the Standardised Computer‐based Organised Reporting of EEG (SCORE). This approach integrates the terminology recently proposed for the rhythmic and periodic patterns in critically ill patients, the electroclinical classification of NCSE (type of NCSE) and the context for the pathologic conditions and age‐related epilepsy syndromes. We propose flexible EEG criteria that employ the SCORE system to assemble a database for determining evidence‐based EEG criteria for NCSE.

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database. In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE is a useful clinical tool, with potential impact on clinical care, quality assurance, data-sharing, research and education.

Glioblastoma (GBM) is a highly aggressive brain tumour, where patients respond poorly to radiotherapy and exhibit dismal survival outcomes. The mechanisms of radioresistance are not completely understood. However, cancer cells with an immature stem-like phenotype are hypothesised to play a role in radioresistance. Since the progenitor marker neuron-glial-2 (NG2) has been shown to regulate several aspects of GBM progression in experimental systems, we hypothesised that its expression would influence the survival of GBM patients. Quantification of NG2 expression in 74 GBM biopsies from newly diagnosed and untreated patients revealed that 50% express high NG2 levels on tumour cells and associated vessels, being associated with significantly shorter survival. This effect was independent of age at diagnosis, treatment received and hypermethylation of the O⁶-methylguanine methyltransferase (MGMT) DNA repair gene promoter. NG2 was frequently co-expressed with nestin and vimentin but rarely with CD133 and the NG2 positive tumour cells harboured genetic aberrations typical for GBM. 2D proteomics of 11 randomly selected biopsies revealed upregulation of an antioxidant, peroxiredoxin-1 (PRDX-1), in the shortest surviving patients. Expression of PRDX-1 was associated with significantly reduced products of oxidative stress. Furthermore, NG2 expressing GBM cells showed resistance to ionising radiation (IR), rapidly recognised DNA damage and effectuated cell cycle checkpoint signalling. PRDX-1 knockdown transiently slowed tumour growth rates and sensitised them to IR in vivo. Our data establish NG2 as an important prognostic factor for GBM patient survival, by mediating resistance to radiotherapy through induction of ROS scavenging enzymes and preferential DNA damage signalling.

Peer reviewed article authored by (Naess H, Lunde L, Brogger J). Read article or submit your manuscript for publishing.

Summary: The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free‐text format. The purpose of our endeavor was to create a computer‐based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video‐EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan‐European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer‐based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, “episodes” (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer‐assisted analysis into the report, it will make possible the build‐up of a multinational database, and it will help in training young neurophysiologists.