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:
Much research and many conversations have centered on the ability of tomosynthesis to increase the breast cancer detection rate. But, there has been no consensus about whether that improvement is enough to warrant any changes to screening guidelines. In a study published recently in the American Journal of Roentgenology, investigators sought to answer that question. Look for our coverage of it later this week.
For additional coverage about breast cancer screening, click here.
fMRI has long been considered the gold standard for brain imaging, but researchers and clinicians have still sought to improve upon it. Recently, investigators from the Keck School of Medicine at the University of Southern California succeeded in that endeavor. By using photoacoustics, they created functional photoacoustic computed tomography (fPACT). In the coming days, look for a more in-depth article on what this scan is and what makes it different – and better.
For more content on fMRI, click here.
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Cybersecurity threats are ubiquitous with more and more attacks happening across all industries – and radiology is not immune. In recent years, vendors have created and launched products designed to keep images and the attached personal health information safe, but vulnerabilities still exist. This week, in the Journal of the American College of Radiology, investigators offer solutions to the cybersecurity threats radiology practices face. Look for our coverage later this week.
For more cybersecurity coverage, click here.
FDA Clears AI-Powered Qualitative Perfusion Mapping for Cone-Beam CT
May 6th 2024Reportedly validated in more than 10 clinical trials, the AngioFlow perfusion imaging software enables timely identification of brain regions with cerebral blood flow reduction and those with significant hypoperfusion.
Can a CT-Based Radiomics Model Bolster Detection of Malignant Thyroid Nodules?
May 3rd 2024A computed tomography (CT)-based radiomics model that includes 28 radiomic features showed significantly higher accuracy, sensitivity, and specificity than conventional CT in differentiating benign and malignant thyroid nodules, according to newly published research.