† People involved in the organization of the challenge. ‡ People contributing data from their institutions.§ Equal senior authors.

Multiple sclerosis (MS) is a disease of the central nervous system characterized by widespread demyelination, axonal loss and gliosis, and neurodegeneration; susceptibility-weighted imaging (SWI), through the use of phase information to enhance local susceptibility or T2* contrast, is a relatively-new and simple MRI application that can directly image cerebral veins by exploiting venous blood oxygenation. Here, we use high-field SWI at 3.0 T to image fifteen patients with clinically definite relapsing-remitting (RR) MS and to assess cerebral venous oxygen level changes. We demonstrate significantly reduced visibility of periventricular white matter venous vasculature as compared to control subjects, supporting the concept of a widespread hypometabolic MS disease process. SWI may afford a noninvasive and relatively simple method to assess venous oxygen saturation in order to closely monitor disease severity, progression, and response to therapy.

Abstract. Gene expression profiling of metastatic brain tumors from primary lung adenocarcinoma, using a 17k-expression array, revealed that 1561 genes were consistently altered. Further functional classification placed the genes into seven categories: cell cycle and DNA damage repair, apoptosis, signal transduction molecules, transcription factors, invasion and metastasis, adhesion, and angiogenesis. Genes involved in apoptosis, such as caspase 2 (CASP2), transforming growth factor-ß inducible early gene (TIEG), and neuroprotective heat shock protein 70 (Hsp70) were underexpressed in metastatic brain tumors. Alterations in Rho GTPases (ARHGAP26, ARHGAP1), as well as down-regulation of the metastasis suppressor gene KiSS-1 were noted, which may contribute to tumor aggression. Overexpression of the invasion-related gene neurofibromatosis 1 (NF1), and angiogenesis-related genes vascular endothelial growth factor-B (VEGF-B) and placental growth factor (PGF) was also evidenced. Brain-specific angiogenesis inhibitors 1 and 3 (BAI1 and BAI3) were underexpressed as well. Examination of cell-adhesion and migration-related genes revealed an increased expression of integrins and extracellular matrices collagen and laminin. The study also showed alterations in p53 protein-associated genes, among these increased gene expression of p53, up-regulation of Reprimo or candidate mediator of the p53-dependent G2-arrest, down-regulation of p53-regulated apoptosis-inducing protein 1 (p53AIP1), decreased expression of tumor protein inducible nuclear protein 1 (p53DINP1), and down-regulation of Mdm4 (MDMX). The results demonstrated that genes involved in adhesion, motility, and angiogenesis were consistently upregulated in metastatic brain tumors, while genes involved in apoptosis, neuroprotection, and suppression of angiogenesis were markedly down-regulated, collectively making these cancer cells prone to metastasis.

I ntracranial hemorrhage is a potentially life-threatening problem that has many direct and indirect causes. Accuracy in diagnosing the presence and type of intracranial hemorrhage is a critical part of effective treatment. Diagnosis is often an urgent procedure requiring review of medical images by highly trained specialists and sometimes necessitating confirmation through clinical history, vital signs, and laboratory examinations. The process is complicated and requires immediate identification for optimal treatment.Intracranial hemorrhage is a relatively common condition that has many causes, including trauma, stroke, aneurysm, vascular malformation, high blood pressure, illicit drugs, and blood clotting disorders (1). Neurologic consequences can vary extensively from headache to death depending upon the size, type, and location of the hemorrhage. The role of the radiologist is to detect the hemorrhage, characterize the type and cause of the hemorrhage, and to determine if the hemorrhage could be jeopardizing critical areas of the brain that might require immediate surgery.While all acute hemorrhages appear attenuated on CT images, the primary imaging features that help radiologists determine the cause of hemorrhage are the location, shape, and proximity to other structures. Intraparenchymal hemorrhage is blood that is located completely within the brain itself. Intraventricular or subarachnoid hemorrhage is blood that has leaked into the spaces of the brain that normally contain cerebrospinal fluid (the ventricles or subarachnoid cisterns, respectively). Extra-axial hemorrhage is blood that collects in the tissue coverings that surround the brain (eg, subdural or epidural subtypes). It is important to note that patients may exhibit more than one type of cerebral hemorrhage, which may appear on the same image or imaging study. Although small hemorrhages are typically less morbid than large hemorrhages, even a small hemorrhage can lead to death if it is in a critical location. Small hemorrhages also may herald future hemorrhages that could be fatal (eg, ruptured cerebral aneurysm). The presence or absence of hemorrhage may guide specific treatments (eg, stroke).Detection of cerebral hemorrhage with brain CT is a popular clinical use case for machine learning (2-5). Many of these early successful investigations were based upon relatively small datasets (hundreds of examinations) from single institutions. Chilamkurthy et al created a diverse brain CT dataset that was selected from 20 geographically distinct centers in India (more than 21 000 unique examinations). This was used to create smaller randomly selected subsets for validation and testing on common acute brain abnormalities (6). The ability for machine learning algorithms to generalize to "real-world" clinical imaging data from disparate institutions is paramount to successful use in the clinical environment.The intent for this challenge was to provide a large multiinstitutional and multinational dataset to help develop machine learning algorithms that ca...

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