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

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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Carotid artery dissection is a cause of stroke, especially in young and middle-aged patients. A dissection occurs when there is an intimal tear or rupture of the vasa vasorum, leading to an intramural hematoma, which is thought to result from trauma or can occur spontaneously, and is likely multifactorial, involving environmental and intrinsic factors. The clinical diagnosis of carotid artery dissection can be challenging, with common presentations including pain, partial Horner syndrome, cranial nerve palsies, or cerebral ischemia. With the use of noninvasive imaging, including magnetic resonance and computed tomography angiography, the diagnosis of carotid dissection has increased in frequency. Treatment options include thrombolysis, antiplatelet or anticoagulation therapy, endovascular or surgical interventions. The choice of appropriate therapy remains controversial as most carotid dissections heal on their own and there are no randomized trials to compare treatment options.

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Neuromyelitis optica is a neurotropic autoimmune inflammatory disease of the central nervous system traditionally thought to exclusively involve the optic nerves and spinal cord. With the discovery of the disease-specific aquaporin-4 antibody and the increasing recognition of clinical and characteristic imaging patterns of brain involvement in what is now termed neuromyelitis optica spectrum disorder (NMOSD), MRI now plays a greater role in diagnosis of NMOSD based on the 2015 consensus criteria and in distinguishing it from other inflammatory disorders, particularly multiple sclerosis (MS). Several brain lesion patterns are highly suggestive of NMOSD, whereas others may serve as red flags. Specifically, long corticospinal lesions, hemispheric cerebral white matter lesions and periependymal lesions in the diencephalon, dorsal brainstem and white matter adjacent to lateral ventricles are typical of NMOSD. In contrast, juxtacortical, cortical, or lesions perpendicularly oriented to the surface of the lateral ventricle suggests MS as the diagnosis. Ultimately, a strong recognition of the spectrum of MRI brain findings in NMOSD is essential for accurate diagnosis, and particularly in differentiating from MS. This pictorial review highlights the spectrum of characteristic brain lesion patterns that may be seen in NMOSD and further delineates findings that may help distinguish it from MS.

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