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1 month ago | 
rsna.org | Nick Klenske
Image Courtesy of Suyash Gunjal, MBBS, MD (Art of Imaging 2024)
Make the SwitchDrs. Scheel and Carver recommended that departments consider switching to less energy intensive imaging tests, such as US or radiography. “When more than one imaging test is appropriate to answer a clinical question, imaging tests with lower emissions should be prioritized,” Dr. Scheel noted.
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1 month ago | 
rsna.org | Nick Klenske
For male patients increased left-ventricular mass (LVM) was predictive of a cardiovascular event, while LVM-to-volume ratio was predictive in female patients
Cardiovascular disease (CVD) is a major cause of death in people worldwide. CVD is characterized by structural alterations in the size and shape of the myocardium over the course of the disease, termed left ventricular (LV) remodeling.
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Oct 28, 2024 | 
rsna.org | Nick Klenske
Imaging’s Role in Managing Sinonasal Tumors When it comes to managing sinonasal tumors, imaging is primarily used for mapping—a task that involves determining the involvement of the sinonasal cavity subsites, surrounding soft tissues, orbital contents, intracranial compartment, perineural structures and lymph nodes.
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Oct 15, 2024 | 
rsna.org | Nick Klenske
The Anatomy of a Virtual Imaging TrialVirtual imaging trials are based on the simulation of human anatomy, imaging modalities and image interpretation, which parallel the components of real-life imaging trials. Depending on the imaging task to be assessed, each component will include various models to be simulated.
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Sep 26, 2024 | 
rsna.org | Nick Klenske
The Liver Imaging Reporting and Data System (LI-RADS) is an established standardized interpretation and reporting system that is specific for the imaging diagnosis of hepatocellular carcinoma (HCC) in high-risk patients.
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Aug 21, 2024 | 
rsna.org | Nick Klenske
Whether we’re aware of them or not, biases are everywhere—and AI is no exception. “An AI algorithm reflects the data it is trained on,” said Bradley J. Erickson, MD, PhD, professor of radiology at the Mayo Clinic in Rochester, MN. “This means that if a use case doesn’t have the same statistics as the training data, the algorithm tends to give answers that reflect the latter.” This isn’t the result of some desire to intentionally harm a particular group.
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May 7, 2024 | 
rsna.org | Nick Klenske
This is the final story in a series of RSNA News articles addressing issues facing private radiology practices. Read the first and second story of the series. Private equity investment in radiology practices is nothing new. But the impact such investments have on the practice and on the radiologists is very much open to debate. “Investor-backed entities can be a good idea if done correctly and for the right reasons,” said Gavin P.
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Apr 2, 2024 | 
rsna.org | Nick Klenske
Thyroid nodules are a common clinical problem. While most aren’t serious, a small percentage are cancerous. The challenge is to determine what’s benign and what’s malignant. “Ultrasound is the imaging technique most often used to assess the probability of malignancy, as well as to guide biopsy,” said Terry S. Desser, MD, professor of radiology at Stanford University School of Medicine in Stanford, CA.
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Feb 28, 2024 | 
rsna.org | Nick Klenske
Algorithm Based on Multi-Ethnic Study of AtherosclerosisIn this study, researchers developed a deep learning algorithm using the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study designed to investigate characteristics and risk factors for progression of subclinical cardiovascular disease to clinical manifestation.
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Jan 23, 2024 | 
rsna.org | Nick Klenske
According to the Alzheimer’s Association, amnestic mild cognitive impairment(aMCI), the subtype of MCI that primarily affects memory, may cause a person to begin forgetting important information they would previously have easily recalled, such as appointments, conversations, or recent events. Not all aMCI patients will progress to dementia, and those that do have heterogeneous clinical progression, making it difficult to identify individual patients at highest risk.
