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

5Noncontrast CT is used in initial evaluation of AIS, in part, because of fast acquisition time, widespread availability, and ease of interpretation in the emergency setting. The introduction of multislice technology has expanded the CT armamentarium to make multimodal CT that includes CT angiography and whole-brain coverage perfusion CT feasible in the acute stroke setting. This technology has dramatically increased the speed and simplicity of CT techniques and has set a high standard for alternative imaging modalities. A comprehensive CT stroke algorithm, including parenchymal imaging (noncontrast head CT), CT angiography, and perfusion/penumbral Background and Purpose-If magnetic resonance imaging (MRI) is to compete with computed tomography for evaluation of patients with acute ischemic stroke, there is a need for further improvements in acquisition speed. Methods-Inclusion criteria for this prospective, single institutional study were symptoms of acute ischemic stroke within 24 hours onset, National Institutes of Health Stroke Scale ≥3, and absence of MRI contraindications. A combination of echo-planar imaging (EPI) and a parallel acquisition technique were used on a 3T magnetic resonance (MR) scanner to accelerate the acquisition time. Image analysis was performed independently by 2 neuroradiologists. Results-A total of 62 patients met inclusion criteria. A repeat MRI scan was performed in 22 patients resulting in a total of 84 MRIs available for analysis. Diagnostic image quality was achieved in 100% of diffusion-weighted imaging, 100% EPI-fluid attenuation inversion recovery imaging, 98% EPI-gradient recalled echo, 90% neck MR angiography and 96% of brain MR angiography, and 94% of dynamic susceptibility contrast perfusion scans with interobserver agreements (k) ranging from 0.64 to 0.84. Fifty-nine patients (95%) had acute infarction. There was good interobserver agreement for EPI-fluid attenuation inversion recovery imaging findings (k=0.78; 95% confidence interval, 0.66-0.87) and for detection of mismatch classification using dynamic susceptibility contrast-Tmax (k=0.92; 95% confidence interval, 0.87-0.94). Thirteen acute intracranial hemorrhages were detected on EPI-gradient recalled echo by both observers. A total of 68 and 72 segmental arterial stenoses were detected on contrast-enhanced MR angiography of the neck and brain with k=0.93, 95% confidence interval, 0.84 to 0.96 and 0.87, 95% confidence interval, 0.80 to 0.90, respectively. Conclusions-A 6-minute multimodal MR protocol with good diagnostic quality is feasible for the evaluation of patients with acute ischemic stroke and can result in significant reduction in scan time rivaling that of the multimodal computed tomographic protocol. (Stroke. 2014;45:1985-1991.)

Skull base osteomyelitis is a relatively rare condition, generally occurring as a complication of advanced otologic or sinus infection in immunocompromised patients. Skull base osteomyelitis is generally divided into 2 broad categories: typical and atypical. Typical skull base osteomyelitis occurs secondary to uncontrolled infection of the temporal bone region, most often from necrotizing external otitis caused by Pseudomonas aeruginosa in a patient with diabetes. Atypical skull base osteomyelitis occurs in the absence of obvious temporal bone infection or external auditory canal infection. It may be secondary to advanced sinusitis or deep face infection or might occur in the absence of a known local source of infection. Atypical skull base osteomyelitis preferentially affects the central skull base and can be caused by bacterial or fungal infections. Clinically, typical skull base osteomyelitis presents with signs and symptoms of otitis externa or other temporal bone infection. Both typical and atypical forms can produce nonspecific symptoms including headache and fever, and progress to cranial neuropathies and meningitis. Early diagnosis can be difficult both clinically and radiologically, and the diagnosis is often delayed. Radiologic evaluation plays a critical role in the diagnosis of skull base osteomyelitis, with CT and MR imaging serving complementary roles. CT best demonstrates cortical and trabecular destruction of bone. MR imaging is best for determining the overall extent of disease and best demonstrates involvement of marrow space and extraosseous soft tissue. Nuclear medicine studies can also be contributory to diagnosis and follow-up. The goal of this article was to review the basic pathophysiology, clinical findings, and key radiologic features of skull base osteomyelitis. ABBREVIATIONS: ASBO ¼ atypical skull base osteomyelitis; EAC ¼ external auditory canal; Ga-67 ¼ gallium-67 citrate; IgG4 ¼ immunoglobulin G4; Tc99m MDP ¼ technetium Tc99m methylene diphosphonate; NEO ¼ necrotizing external otitis; SBO ¼ skull base osteomyelitis; TSBO ¼ typical skull base osteomyelitis S kull base osteomyelitis (SBO) is a rare, potentially life-threatening infection that can present a diagnostic challenge clinically and radiologically. [1][2][3][4] While reports differ in terminology, there are generally 2 categories of SBO: typical and atypical. Typical SBO (TSBO) is the most common and classically occurs in elderly patients with diabetes as a result of necrotizing external otitis (NEO) caused by Pseudomonas species. (Fig 1). 1,3 Atypical SBO (ASBO), also called central SBO, predominantly involves the basisphenoid and basiocciput and occurs without preceding otologic infection (Fig 2). 2,5 Recognition of SBO is increasing, and it is clear that radiologic evaluation plays a critical role in diagnosis and management. The goal of this article was to review the pathophysiology, clinical presentation, and detailed radiologic findings using multiple modalities including CT, MR imaging, and nuclear medicine.

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...