We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks proposed for similar applications. To overcome the computational burden of processing 3D medical scans, we have devised an efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data. Further, we analyze the development of deeper, thus more discriminative 3D CNNs. In order to incorporate both local and larger contextual information, we employ a dual pathway architecture that processes the input images at multiple scales simultaneously. For post-processing of the network's soft segmentation, we use a 3D fully connected Conditional Random Field which effectively removes false positives. Our pipeline is extensively evaluated on three challenging tasks of lesion segmentation in multi-channel MRI patient data with traumatic brain injuries, brain tumours, and ischemic stroke. We improve on the state-of-the-art for all three applications, with top ranking performance on the public benchmarks BRATS 2015 and ISLES 2015. Our method is computationally efficient, which allows its adoption in a variety of research and clinical settings. The source code of our implementation is made publicly available.

A concerted effort to tackle the global health problem posed by traumatic brain injury (TBI) is long overdue. TBI is a public health challenge of vast, but insufficiently recognised, proportions. Worldwide, more than 50 million people have a TBI each year, and it is estimated that about half the world's population will have one or more TBIs over their lifetime. TBI is the leading cause of mortality in young adults and a major cause of death and disability across all ages in all countries, with a disproportionate burden of disability and death occurring in low-income and middle-income countries (LMICs). It has been estimated that TBI costs the global economy approximately $US400 billion annually. Deficiencies in prevention, care, and research urgently need to be addressed to reduce the huge burden and societal costs of TBI. This Commission highlights priorities and provides expert recommendations for all stakeholders—policy makers, funders, health-care professionals, researchers, and patient representatives—on clinical and research strategies to reduce this growing public health problem and improve the lives of people with TBI.Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Söderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbüchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigator

We investigated large-scale systems organization of the whole human brain using functional magnetic resonance imaging (fMRI) data acquired from healthy volunteers in a no-task or 'resting' state. Images were parcellated using a prior anatomical template, yielding regional mean time series for each of 90 regions (major cortical gyri and subcortical nuclei) in each subject. Significant pairwise functional connections, defined by the group mean inter-regional partial correlation matrix, were mostly either local and intrahemispheric or symmetrically interhemispheric. Low-frequency components in the time series subtended stronger inter-regional correlations than high-frequency components. Intrahemispheric connectivity was generally related to anatomical distance by an inverse square law; many symmetrical interhemispheric connections were stronger than predicted by the anatomical distance between bilaterally homologous regions. Strong interhemispheric connectivity was notably absent in data acquired from a single patient, minimally conscious following a brainstem lesion. Multivariate analysis by hierarchical clustering and multidimensional scaling consistently defined six major systems in healthy volunteers-- corresponding approximately to four neocortical lobes, medial temporal lobe and subcortical nuclei- - that could be further decomposed into anatomically and functionally plausible subsystems, e.g. dorsal and ventral divisions of occipital cortex. An undirected graph derived by thresholding the healthy group mean partial correlation matrix demonstrated local clustering or cliquishness of connectivity and short mean path length compatible with prior data on small world characteristics of non-human cortical anatomy. Functional MRI demonstrates a neurophysiological architecture of the normal human brain that is anatomically sensible, strongly symmetrical, disrupted by acute brain injury, subtended predominantly by low frequencies and consistent with a small world network topology.

Background Concerns regarding potential neurological complications of COVID-19 are being increasingly reported, primarily in small series. Larger studies have been limited by both geography and specialty. Comprehensive characterisation of clinical syndromes is crucial to allow rational selection and evaluation of potential therapies. The aim of this study was to investigate the breadth of complications of COVID-19 across the UK that affected the brain. Methods During the exponential phase of the pandemic, we developed an online network of secure rapid-response case report notification portals across the spectrum of major UK neuroscience bodies, comprising the Association of British Neurologists (ABN), the British Association of Stroke Physicians (BASP), and the Royal College of Psychiatrists (RCPsych), and representing neurology, stroke, psychiatry, and intensive care. Broad clinical syndromes associated with COVID-19 were classified as a cerebrovascular event (defined as an acute ischaemic, haemorrhagic, or thrombotic vascular event involving the brain parenchyma or subarachnoid space), altered mental status (defined as an acute alteration in personality, behaviour, cognition, or consciousness), peripheral neurology (defined as involving nerve roots, peripheral nerves, neuromuscular junction, or muscle), or other (with free text boxes for those not meeting these syndromic presentations). Physicians were encouraged to report cases prospectively and we permitted recent cases to be notified retrospectively when assigned a confirmed date of admission or initial clinical assessment, allowing identification of cases that occurred before notification portals were available. Data collected were compared with the geographical, demographic, and temporal presentation of overall cases of COVID-19 as reported by UK Government public health bodies.

Traumatic brain injury (TBI) is a critical public health and socio-economic problem throughout the world. Reliable quantification of the burden caused by TBI is difficult owing to inadequate standardization and incomplete capture of data on the incidence and outcome of brain injury, with variability in the definition of TBI being partly to blame. Reports show changes in epidemiological patterns of TBI: the median age of individuals who experience TBI is increasing, and falls have now surpassed road traffic incidents as the leading cause of this injury. Despite claims to the contrary, no clear decrease in TBI-related mortality or improvement of overall outcome has been observed over the past two decades. In this Perspectives article, we discuss the strengths and limitations of epidemiological studies, address the variability in its definition, and highlight changing epidemiological patterns. Taken together, these analyses identify a great need for standardized epidemiological monitoring in TBI.

Subarachnoid hemorrhage (SAH) is an acute cerebrovascular event which can have devastating effects on the central nervous system as well as a profound impact on several other organs. SAH patients are routinely admitted to an intensive care unit and are cared for by a multidisciplinary team. A lack of high quality data has led to numerous approaches to management and limited guidance on choosing among them. Existing guidelines emphasize risk factors, prevention, natural history, and prevention of rebleeding, but provide limited discussion of the complex critical care issues involved in the care of SAH patients. The Neurocritical Care Society organized an international, multidisciplinary consensus conference on the critical care management of SAH to address this need. Experts from neurocritical care, neurosurgery, neurology, interventional neuroradiology, and neuroanesthesiology from Europe and North America were recruited based on their publications and expertise. A jury of four experienced neurointensivists was selected for their experience in clinical investigations and development of practice guidelines. Recommendations were developed based on literature review using the GRADE system, discussion integrating the literature with the collective experience of the participants and critical review by an impartial jury. Recommendations were developed using the GRADE system. Emphasis was placed on the principle that recommendations should be based not only on the quality of the data but also tradeoffs and translation into practice. Strong consideration was given to providing guidance and recommendations for all issues faced in the daily management of SAH patients, even in the absence of high quality data.

No abstract

For patients with H1N1-related ARDS, referral and transfer to an ECMO center was associated with lower hospital mortality compared with matched non-ECMO-referred patients.