Here's what to expect this week on Diagnostic Imaging.
In this week’s preview, here are some highlights of what you can expect to see coming soon:
Smoking can make changes to the airways early and in ways that are likely to go unnoticed. Quantitative CT (QCT) has become the gold standard for imaging these alterations in patients with chronic obstructive pulmonary disease (COPD) because it is non-invasive, but there has been little research into whether it can pinpoint changes in smokers who appear to have a normal CT. Look for an article later this week that discusses how well QCT works with this subclinical population.
For more lung CT coverage, click here.
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Even as vaccine rates increase, there is still a need for rapid, accurate COVID-19 diagnosis. Chest X-ray, bolstered by artificial intelligence (AI), could be a near-perfect option – especially when chest CT is not readily available or swab and saliva test results are delayed. Keep your eyes open for an article later this week.
For more coverage of chest X-rays and COVID-19, click here.
Last week, Diagnostic Imaging published an article on the use of a triaging model to better prioritize mammography screenings during times of crisis, such as the COVID-19 pandemic. This week, be on the lookout for interview with study lead Diana L. Miglioretti, Ph.D., from the University of California at Davis about why such a system is important and the impacts it could have downstream.
For additional mammography and COVID-19 coverage, click here.
New Study Examines Agreement Between Radiologists and Referring Clinicians on Follow-Up Imaging
November 18th 2024Agreement on follow-up imaging was 41 percent more likely with recommendations by thoracic radiologists and 36 percent less likely on recommendations for follow-up nuclear imaging, according to new research.
FDA Clears Updated AI Platform for Digital Breast Tomosynthesis
November 12th 2024Employing advanced deep learning convolutional neural networks, ProFound Detection Version 4.0 reportedly offers a 50 percent improvement in detecting cancer in dense breasts in comparison to the previous version of the software.