Contributing Editor Greg Freiherr offers an overview of computed tomography (CT) advances at the Radiological Society of North America (RSNA) 2015. The video includes Freiherr during his booth tours with some of the key vendors who were featuring new technology.
Computed Tomography (CT)
Images in a 41-year-old woman who presented with fever and positive polymerase chain reaction assay for the 2019 novel coronavirus (2019-nCoV). Three representative axial thin-section chest CT images show multifocal ground glass opacities without consolidation. Three-dimensional volume-rendered reconstruction shows the distribution of the ground-glass opacities (arrows). Image courtesy of the Radiological Society of North America (RSNA)
Examples of typical chest CT findings compatible with COVID-19 pneumonia in patients with epidemiological and clinical presentation suspicious for COVID-19 infection. This image is part of the original research, Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR, published Feb. 19, 2020, in Radiology Online.
An image from the Radiology article showing a baseline CT image of a 75 year old male with multiple patchy areas of pure ground glass opacity (GGO) and GGO with reticular and/or interlobular septal thickening. Follow-up CT images on day 3 after admission show an overlap of organizing pneumonia with diffuse alveolar damage in that it is more diffuse and associated with underlying reticulation. Read more and see 15 more images from novel coronavirus patients in the article.
CT lung imaging from a 41-year-old woman who tested positive for the 2019 novel coronavirus (2019-nCoV). This 3-D reconstruction shows multifocal ground glass opacities without consolidation. See also three-dimensional VIDEO of this rendering.
Infervision’s deep learning medical imaging platform is helping screen patients for the coronavirus in China. It acts as second pair of eyes to identify multiple diseases from one set of chest scans. The artificial intelligence (AI) can provide a complete view of the nodule, including volume and density.
Figure A: CT scan of a coronavirus from a patient in China showing ground glass lesions in the lungs. Images courtesy of the Radiological Society of North America. For larger images and more details on the scan, view the original article at https://pubs.rsna.org/doi/10.1148/radiol.2020200236
Axial unenhanced inspiratory CT images of the lungs in 51-year-old woman (a) before and (b) 6 months after bariatric surgery with 31-kg weight loss (body mass index decrease, 36.1%). The mosaic attenuation seen before surgery resolved after surgery. Image courtesy of Radiological Society of North America (RSNA)
This is a lung X-ray reviewed automatically by artificial intelligence (AI) to identify a collapsed lung (pneumothorax) in the color coded area. This AI app from Lunit is awaiting final FDA review and in planned to be integrated into several vendors' mobile digital radiography (DR) systems. Fujifilm showed this software integrated as a work-in-progress into its mobile X-ray system at RSNA 2019. GE Healthcare has its own version of this software for its mobile r=ray systems that gained FDA in 2019.