A recent preprint study in France underpins the debate on whether lung ultrasound (LUS) should be used to triage COVID-19 patients better at the hospital as well as in primary care. The eChoVid study, published as a preliminary report of work on medTrix, shows that LUS enables identification of lung lesions as well as chest CT in COVID-19 patients. A team of French researchers compared routinely…
Researchers at the University of Notre Dame are developing a new technique using artificial intelligence (AI) that would improve CT screening to more quickly identify patients with the coronavirus. The new technique will reduce the burden on the radiologists tasked with screening each image. Testing challenges have led to an influx of patients hospitalized with COVID-19 requiring CT scans which…
Rapid first aid during cardiac arrest makes the difference between life and death. But what happens to the heart and the internal organs when people come running and begin to give well-meaning but heavy-handed heart massage as they attempt to keep the person who has suffered a cardiac arrest alive? A research collaboration between the Department of Forensic Medicine at Aarhus University and the…
Injuries in the nervous system of patients with severe COVID-19 are revealed by magnetic resonance imaging (MRI) and computed tomography (CT). In a study of 185 patients, researchers at Karolinska Institutet (KI) and Karolinska University Hospital show an affection of microscopic blood vessels and inflammation in the brain, meninges and nerves. The results are published in Radiology.
Researchers have designed a fluid that works like a luminous ink to obtain very sharp images of damaged tissues, organs and cartilages in diagnostic tests. This new compound, still in the laboratory phase, reduces adverse effects on the human body because it allows lower amounts to be injected and the dose to be targeted only at the affected area.
CT has a critical role to play in management of mass casualty incidents with the ability to image patients from head to toe, offering a rapid overview for clinicians. The benefits of CT were outlined by Dr Elizabeth Dick during an ECR session examining the role of radiology in the management of mass casualty incidents, terror attacks and assaults.
The complex form of machine learning DLIR (Deep Learning Image Reconstruction) is based on a deep neuronal network which is similar to the human brain. The artificial neurons of this network learn according to their biological model through intensive training. For the DLIR image reconstruction, the network is fed with sample data from phantom images on the one hand and high-resolution images of…
Computed tomography (CT) is one of the most important imaging options for the diagnostics of patients. For a long time, in clinical routine CT technology mostly showed the Hounsfield Units (HU) that are indicated in the grayscale. However, the Dual Energy CT (DECT) enables colored X-ray images, therefore significantly improving examination methods. “We can also do material separation and get a…
Researchers at the University of Zurich have developed a new X-ray contrast agent which is easier to use and distributes into all blood vessels more reliably, increasing the precision of vascular imaging. This reduces the number of animals required in research experiments. Various diseases in humans and animals – such as tumors, strokes or chronic kidney disease – damage the blood vessels.…
The organ of balance in the inner ear is surrounded by the hardest bone in the body. Using synchrotron X-rays, researchers at Uppsala University have discovered a drainage system that may be assumed to play a major role in the onset of Ménière's disease, a common and troublesome disorder. These results are published in the journal Scientific Reports. Ménière's disease is manifested in sudden…
Machine learning and AI are highly unstable in medical image reconstruction, and may lead to false positives and false negatives, a new study suggests. A team of researchers, led by the University of Cambridge and Simon Fraser University, designed a series of tests for medical image reconstruction algorithms based on AI and deep learning, and found that these techniques result in myriad…
Computed tomography (CT) is one of the most effective medical tests for analysing the effects of many illnesses, including COVID-19, on the lungs. An international team led by the Universitat Oberta de Catalunya (UOC) has developed a new method that improves the quality of the images obtained from CT scans. The algorithm, which has been tested on simulated data, enables them to distinguish…
Although the clinical symptoms of new pediatric lung disorders such as severe acute respiratory syndrome (SARS), swine-origin influenza A (H1N1), Middle East respiratory syndrome (MERS), e-cigarette or vaping product use-associated lung injury (EVALI), and coronavirus disease (COVID-19) pneumonia may be nonspecific, some characteristic imaging findings "have emerged or are currently…
Hospitals and organizations worldwide joined forces with AI imaging company icometrix in a global initiative to leverage artificial intelligence (AI) in the fight against COVID-19. The multinational collaboration resulted in the development of an AI algorithm, icolung, which received CE-marking for clinical use in Europe. icolung is the first CE-marked AI solution for CT resulting from a…
A computational lung model can be used to reduce damage caused by mechanical ventilation – and could increase survival rates for patients significantly.
As radiologists worldwide continue to share their knowledge of COVID-19 to help fight the pandemic, two chest experts from France and Spain talked about their country perspectives and the practical experience at their hospital in a dedicated online session organized by the European Society of Radiology (ESR).
Chest X-ray is the first imaging method to diagnose COVID-19 coronavirus infection in Spain, but in the light of new evidence this may change soon, according to Milagros Martí de Gracia, Vice President of the Spanish Society of Radiology (SERAM) and head of the emergency radiology unit at La Paz Hospital in Madrid, one of the hot spots for viral re-production of COVID-19.
As a highly innovative medical specialisation, radiology increasingly takes advantage of the possibilities offered by artificial intelligence (AI). Yet, there is no risk for the future of the specialty. Demands on this discipline are too complex, too communicative. Thus, machines will not replace a radiologist any time soon – of that Uwe Joseph Schöpf, professor of radiology, cardiology and…
In a study of more than 1,000 patients published in Radiology, chest CT outperformed lab testing in the diagnosis of 2019 novel coronavirus disease (COVID-19). Researchers at Tongji Hospital in Wuhan, China, concluded that CT should be used as the primary screening tool for COVID-19. In the absence of specific therapeutic drugs or vaccines for COVID-19, it is essential to detect the disease at an…
Computed tomography (CT) plays an increasingly important role in assessing pelvic disease, particularly when patients present with acute abdominal pain. In addition, radiomic approaches on CT are being developed to increase the characterisation of ovarian cancer for optimising treatment planning.
Cystic lesions of the pancreas can occur in many forms, not all of which pose a serious threat to the patient. A thorough diagnosis using multi-modality imaging is therefore indispensable to differentiate between benign and malignant lesions.
A deep learning method with a convolutional neural network (CNN) can support the evaluation of small solid renal masses in dynamic CT images with acceptable diagnostic performance, according to an article published ahead-of-print in the March issue of the American Journal of Roentgenology (AJR). Between 2012 and 2016, researchers at Japan’s Okayama University studied 1807 image sets from 168…
Bringing the power of AI to routine imaging, Advanced intelligent Clear-IQ Engine (AiCE), Canon Medical’s Deep Learning Reconstruction (DLR) technology, is now being integrated across a broader portfolio of scanners with a wider range of clinical applications across modalities. Advanced intelligent Clear-IQ Engine (AiCE) was trained using vast amounts of high-quality image data, and features a…
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Researchers at National Jewish Health and dozens of leading institutions around the nation have proposed new criteria for diagnosing chronic obstructive pulmonary disease (COPD), the fourth leading cause of death in the United States. The proposal expands diagnostic criteria from a single measure of lung function to include environmental exposure, symptoms, and abnormal CT scans.