The burden of traumatic brain injury (TBI) poses a large public health and societal problem, but the characteristics of patients and their care pathways in Europe are poorly understood. We aimed to characterise patient case-mix, care pathways, and outcomes of TBI. CENTER-TBI is a Europe-based, observational cohort study, consisting of a core study and a registry. Inclusion criteria for the core study were a clinical diagnosis of TBI, presentation fewer than 24 h after injury, and an indication for CT. Patients were differentiated by care pathway and assigned to the emergency room (ER) stratum (patients who were discharged from an emergency room), admission stratum (patients who were admitted to a hospital ward), or intensive care unit (ICU) stratum (patients who were admitted to the ICU). Neuroimages and biospecimens were stored in repositories and outcome was assessed at 6 months after injury. We used the IMPACT core model for estimating the expected mortality and proportion with unfavourable Glasgow Outcome Scale Extended (GOSE) outcomes in patients with moderate or severe TBI (Glasgow Coma Scale [GCS] score ≤12). The core study was registered with ClinicalTrials.gov, number NCT02210221, and with Resource Identification Portal (RRID: SCR_015582). Data from 4509 patients from 18 countries, collected between Dec 9, 2014, and Dec 17, 2017, were analysed in the core study and from 22 782 patients in the registry. In the core study, 848 (19%) patients were in the ER stratum, 1523 (34%) in the admission stratum, and 2138 (47%) in the ICU stratum. In the ICU stratum, 720 (36%) patients had mild TBI (GCS score 13-15). Compared with the core cohort, the registry had a higher proportion of patients in the ER (9839 [43%]) and admission (8571 [38%]) strata, with more than 95% of patients classified as having mild TBI. Patients in the core study were older than those in previous studies (median age 50 years [IQR 30-66], 1254 [28%] aged >65 years), 462 (11%) had serious comorbidities, 772 (18%) were taking anticoagulant or antiplatelet medication, and alcohol was contributory in 1054 (25%) TBIs. MRI and blood biomarker measurement enhanced characterisation of injury severity and type. Substantial inter-country differences existed in care pathways and practice. Incomplete recovery at 6 months (GOSE <8) was found in 207 (30%) patients in the ER stratum, 665 (53%) in the admission stratum, and 1547 (84%) in the ICU stratum. Among patients with moderate-to-severe TBI in the ICU stratum, 623 (55%) patients had unfavourable outcome at 6 months (GOSE <5), similar to the proportion predicted by the IMPACT prognostic model (observed to expected ratio 1·06 [95% CI 0·97-1·14]), but mortality was lower than expected (0·70 [0·62-0·76]). Patients with TBI who presented to European centres in the core study were older than were those in previous observational studies and often had comorbidities. Overall, most patients presented with mild TBI. The incomplete recovery of many patients should motivate precision medicine research and the identification of best practices to improve these outcomes. European Union 7th Framework Programme, the Hannelore Kohl Stiftung, OneMind, and Integra LifeSciences Corporation.

In cerebral gliomas, rCBV correlates with tumor grade and histologic findings of vascular proliferation. Moreover, ADC assesses water diffusivity and is inversely correlated with tumor grade. In the present work, we have studied whether combined rCBV and ADC values improve the diagnostic accuracy of MR imaging in the preoperative grading of gliomas. One hundred sixty-two patients with histopathologically confirmed diffuse gliomas underwent DWI and DSC. Mean rCBV and ADC values were compared among the tumor groups with the Student t test or ANOVA. ROC analysis was used to determine rCBV and ADC threshold values for glioma grading. rCBV had significantly different values between grade II and IV gliomas and between grade III and IV tumors, but there were no significant differences between grade II and III gliomas (P > .05). Grade II and III tumors also did not differ when astrocytomas, oligodendrogliomas, and oligoastrocytomas were considered separately. ADC values were significantly different for all 3 grades. The ADC threshold value of 1.185 × 10(-3) mm(2)/s and the rCBV cutoff value of 1.74 could be used with high sensitivity in the characterization of high-grade gliomas. The area under the ROC curve for the maximum rCBV and minimum ADC was 0.72 and 0.75, respectively. The combination of rCBV and ADC values increased the area under the ROC curve to 0.83. ADC measurements are better than rCBV values for distinguishing the grades of gliomas. The combination of minimum ADC and maximum rCBV improves the diagnostic accuracy of glioma grading.

The increase in the volume of a traumatic intracerebral hemorrhage (TICH) is a widely studied phenomenon that has a direct impact on the prognosis of patients. The objective of this study was to identify the risk factors associated with the progression of TICH. We retrospectively analyzed the records of 1970 adult patients >15 years of age who were consecutively admitted after sustaining a closed severe traumatic brain injury (TBI) between January 1987 and November 2013 at a single center. Beginning in 2007, patients with moderate TBIs were also included. A total of 782 patients exhibited one or more TICH on the initial CT scan, and met the selection criteria. The main outcome variable was the presence or absence of progression of the TICH. Univariate and multivariate statistical analyses were performed. Factors independently associated with the growth of TICH obtained through logistic regression included the following: an initial volume <5 cc (odds ratio [OR] 2.42, p <0.001), cisternal compression (OR 1.95, p <0.001), decompressive craniectomy (OR 2.18, p <0.001), age (mean 37.67 vs. 42.95 years; OR 1.01, p <0.001), falls as mechanism of trauma (OR 1.72, p =0.001), multiple TICHs (OR 1.56, p =0.007), and hypoxia (OR 1.56, p =0.02). TICH progression occurred with a frequency of 63% in our study. We showed that there was a correlation between TICH growth and some variables, such as multiple TICHs, a lower initial volume, acute subdural hematoma, cisternal compression, older patient age, hypoxia, falls, and decompressive craniectomy.

Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy ($OACC$) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the $OACC$ is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.