Clinical imaging
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Artificial intelligence (AI) is a fast-growing research area in computer science that aims to mimic cognitive processes through a number of techniques. Supervised machine learning, a subfield of AI, includes methods that can identify patterns in high-dimensional data using labeled 'ground truth' data and apply these learnt patterns to analyze, interpret, or make predictions on new datasets. Supervised machine learning has become a significant area of interest within the medical community. ⋯ One devastating disease for which neuroimaging plays a significant role in the clinical management is stroke. Within this context, AI techniques can play pivotal roles for image-based diagnosis and management of stroke. This overview focuses on the recent advances of artificial intelligence methods - particularly supervised machine learning and deep learning - with respect to workflow, image acquisition and reconstruction, and image interpretation in patients with acute stroke, while also discussing potential pitfalls and future applications.
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The coronavirus disease 2019 (COVID-19) outbreak, first reported in Wuhan, China, is gradually spreading worldwide. For diagnosis, chest computed tomography is a conventional, noninvasive imaging modality that is very accurate for detection and evaluation of pneumonia and is an important adjunct to real-time reverse transcription polymerase chain reaction diagnosis of the virus. Previous studies have reported typical computed tomography imaging features indicative of COVID-19, such as multifocal ground-glass opacities with or without consolidation. ⋯ Thus, advanced training and education in standardized infection control and prevention practice are essential. The purpose of this brief review is to summarize such training and education for clinical management of this outbreak for radiology department personnel. We will describe standard transmission-based precautions, workflow for computed tomography examination of fever patients, and decontamination management of a radiology department.
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Coronavirus disease 2019 (COVID-19), a clinical manifestation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was declared a global pandemic by the World Health Organization on March 11, 2020. Hypercoagulable state has been described as one of the hallmarks of SARS-CoV-2 infection and has been reported to manifest as pulmonary embolisms, deep vein thrombosis, and arterial thrombosis of the abdominal small vessels. Here we present cases of arterial and venous thrombosis pertaining to the head and neck in COVID-19 patients.
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The purpose of this study was to investigate the chest CT imaging features and clinical outcome of coronavirus disease 2019 (COVID-19) in Ningbo, China. ⋯ The most common chest CT features are multiple bilateral and peripheral GGOs with mixed consolidations or not in the lungs of patients with COVID-19. Chest CT plays an important role in the diagnosis and monitoring treatment response of this disease. There was no reported death in our cases.
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Editorial
Beyond business as usual: Radiology residency educational response to the COVID-2019 pandemic.
The COVID-19 pandemic has disrupted standard hospital operations and diagnostic radiology resident education at academic medical centers across the country. Deferment of elective surgeries and procedures coupled with a shift of resources toward increased inpatient clinical needs for the care of COVID-19 patients has resulted in substantially decreased imaging examinations at many institutions. Additionally, both infection control and risk mitigation measures have resulted in minimal on-site staffing of both trainees and staff radiologists at many institutions. ⋯ We describe our experience adapting to the challenges in educational interruptions and clinical work reassignments of 41 interventional and diagnostic radiology residents at a large academic center. We highlight opportunities for collaboration and teamwork in creatively adjusting and planning for the short and long-term impact of the pandemic on resident education. This experience shows how the residency educational paradigm was shifted during a pandemic and can serve as a template to address future disruptions.