BACKGROUND Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.)

In 1999, a Task Force on Mild Traumatic Brain Injury (MTBI) was set up under the auspices of the European Federation of Neurological Societies. Its aim was to propose an acceptable uniform nomenclature for MTBI and definition of MTBI, and to develop a set of rules to guide initial management with respect to ancillary investigations, hospital admission, observation and follow‐up.

Traumatic brain injury (TBI) is one among the most frequent neurological disorders. Of all TBIs 90% are considered mild with an annual incidence of 100-300/100 000. Intracranial complications of mild traumatic brain injury (MTBI) are infrequent (10%), requiring neurosurgical intervention in a minority of cases (1%), but potentially life threatening (case fatality rate 0.1%). Hence, a true health management problem exists because of the need to exclude the small chance of a life-threatening complication in a large number of individual patients. The 2002 EFNS guideline used the best evidence approach based on the literature until 2001 to guide initial management with respect to indications for computed tomography (CT), hospital admission, observation and follow-up of MTBI patients. This updated EFNS guideline for initial management in MTBI proposes a more selective strategy for CT when major [dangerous mechanism, Glasgow Coma Scale (GCS) < 15, 2 points deterioration on the GCS, clinical signs of (basal) skull fracture, vomiting, anticoagulation therapy, post-traumatic seizure] or minor (age, loss of consciousness, persistent anterograde amnesia, focal deficit, skull contusion, deterioration on the GCS) risk factors are present based on published decision rules with a high level of evidence. In addition, clinical decision rules for CT now exist for children as well. Since 2001, recommendations, although with a lower level of evidence, have been published for clinical observation in hospitals to prevent and treat other potential threats to the patient including behavioural disturbances (amnesia, confusion and agitation) and infection.

This paper considers valuable visual assessment criteria for distinguishing between tumorous and non-tumorous tissues, intraoperatively, using cross-polarization OCT (CP OCT)—OCT with a functional extension, that enables detection of the polarization properties of the tissues in addition to their conventional light scattering. Materials and Methods: The study was performed on 176 ex vivo human specimens obtained from 30 glioma patients. To measure the degree to which the typical parameters of CP OCT images can be matched to the actual histology, 100 images of tumors and white matter were selected for visual analysis to be undertaken by three “single-blinded” investigators. An evaluation of the inter-rater reliability between the investigators was performed. Application of the identified visual CP OCT criteria for intraoperative use was performed during brain tumor resection in 17 patients. Results: The CP OCT image parameters that can typically be used for visual assessment were separated: (1) signal intensity; (2) homogeneity of intensity; (3) attenuation rate; (4) uniformity of attenuation. The degree of match between the CP OCT images and the histology of the specimens was significant for the parameters “signal intensity” in both polarizations, and “homogeneity of intensity” as well as the “uniformity of attenuation” in co-polarization. A test based on the identified criteria showed a diagnostic accuracy of 87–88%. Intraoperative in vivo CP OCT images of white matter and tumors have similar signals to ex vivo ones, whereas the cortex in vivo is characterized by indicative vertical striations arising from the “shadows” of the blood vessels; these are not seen in ex vivo images or in the case of tumor invasion. Conclusion: Visual assessment of CP OCT images enables tumorous and non-tumorous tissues to be distinguished. The most powerful aspect of CP OCT images that can be used as a criterion for differentiation between tumorous tissue and white matter is the signal intensity. In distinguishing white matter from tumors the diagnostic accuracy using the identified visual CP OCT criteria was 87–88%. As the CP OCT data is easily associated with intraoperative neurophysiological and neuronavigation findings this can provide valuable complementary information for the neurosurgeon tumor resection.