Treatment of low-flow vascular malformations of the extremities using MR-guided high intensity focused ultrasound: preliminary experience

Five patients with painful vascular malformations of the extremities that were refractory to standard treatment and were confirmed as low-flow malformations on dynamic contrast-enhanced magnetic resonance (MR) imaging were treated with MR imaging-guided high intensity focused ultrasound. Daily maximum numeric rating scale scores for pain improved from 8.4 ± 1.5 to 1.6 ± 2.2 (P = .004) at a median follow-up of 9 months (range, 4-36 mo). The size of the vascular malformations decreased on follow-up MR imaging (median enhancing volume, 8.2 mL [0.7-10.1 mL] before treatment; 0 mL [0-2.3 mL] after treatment; P = .018) at a median follow-up of 5 months (range, 3-36 mo). No complications occurred

The RSNA International COVID-19 Open Radiology Database (RICORD)

The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19-positive thoracic CT scans. The labeling schema was coordinated with other international consensus panels and COVID-19 data annotation efforts, the European Society of Medical Imaging Informatics, the American College of Radiology, and the American Association of Physicists in Medicine. Study-level COVID-19 classification labels for chest radiographs were annotated by three radiologists, with majority vote adjudication by board-certified radiologists. RICORD consists of 240 thoracic CT scans and 1000 chest radiographs contributed from four international sites. It is anticipated that RICORD will ideally lead to prediction models that can demonstrate sustained performance across populations and health care systems. (C) RSNA, 202

Education in Global Health Radiology

Radiologists and radiology professionals have noted the gaps in diagnostic and interventional imaging access worldwide as documented by the World Health Organization. Since global health focuses on issues that transcend national boundaries, emphasizes solutions that often require global cooperation, and is multidisciplinary, then the concept of radiology education in global health should consider this broader context of international partnership and collaboration. There are several models in place for education in the global health setting with emphasis on radiology. This chapter discusses faculty exchanges, scholarly collaboration, partnership, formal education, online education as a tool, integration of global health concepts into radiology curricula, and socially responsible collaboration. Regardless of the type of model used, educational goals and objectives should be based on initial assessment data and address the appropriate needs. Curricula should be established in partnership with all stakeholders and with consideration for ethical best practices, continuous evaluation and improvement of the program, and open communication among stakeholders