Bone Marrow Edema at Dual-Energy CT: A Game Changer in the Emergency Department.
Babina GosangiJacob C MandellMichael J WeaverJennifer W UyedaStacy E SmithAaron D SodicksonBharti KhuranaPublished in: Radiographics : a review publication of the Radiological Society of North America, Inc (2021)
Dual-energy CT is increasingly being used in the emergency department to help diagnose acute conditions. Its applications include demonstrating bone marrow edema (BME) seen in the setting of occult fractures and other acute conditions. Dual-energy CT acquires data with two different x-ray energy spectra and is able to help differentiate materials on the basis of their differential energy-dependent x-ray absorption behaviors. Virtual noncalcium (VNCa) techniques can be used to suppress the high attenuation of trabecular bone, thus enabling visualization of subtle changes in the underlying attenuation of the bone marrow. Visualization of BME can be used to identify occult or mildly displaced fractures, pathologic fractures, metastases, and some less commonly visualized conditions such as ligamentous injuries or inflammatory arthritis. The authors' major focus is use of dual-energy CT as a diagnostic modality in the setting of trauma and to depict subtle or occult fractures. The authors also provide some scenarios in which dual-energy CT is used to help diagnose other acute conditions. The causes and pathophysiology of BME are reviewed. Dual-energy CT image acquisition and VNCa postprocessing techniques are also discussed, along with their applications in emergency settings. The authors present potential pitfalls and limitations of these techniques and their possible solutions.©RSNA, 2020.
Keyphrases
- dual energy
- computed tomography
- bone marrow
- emergency department
- image quality
- liver failure
- mesenchymal stem cells
- contrast enhanced
- magnetic resonance imaging
- respiratory failure
- healthcare
- bone mineral density
- public health
- rheumatoid arthritis
- radiation therapy
- deep learning
- climate change
- squamous cell carcinoma
- aortic dissection
- mass spectrometry
- machine learning
- high resolution
- body composition
- molecular dynamics
- artificial intelligence
- trauma patients
- virtual reality