COVID-19 Damage, but No Virus in the Brain; Non-Ferromagnetic Bullets and the MRI; Six Trends to Watch in 2021; and AI and Ethics
Welcome to the first Diagnostic Imaging Weekly Scan for 2021. I’m senior editor, Whitney Palmer, and we’re looking forward to an exciting New Year with you.
Before we get to our featured full interview this week with Dr. David Larson from Stanford University Medical Center about the ethics of using artificial intelligence in medical imaging, here are the top stories from this week.
It’s well understood now that COVID-19 can cause neurological problems that accompany the characteristic pulmonary damage. But, researchers from the National Institutes of Health published a story in the New England Journal of Medicine this week that revealed the blood vessel damage and inflammation in the brain that happens with COVID-19-positive patients can occur even if the SARS-CoV-2 virus never infiltrates the brain tissue. Using MRI scanners that were 4-to-10 times more sensitive than the traditional ones used, the team examined brain tissue from 19 patients between the ages of 5 and 73 who died within hours to two months of being diagnosed. They concentrated on tissue from the olfactory bulb and brain stems because those are two areas believed to be susceptible to the virus, but they found no evidence of SARS-CoV-2 in the tissue. They did see hyperintensities and hypointensities that revealed bleeding that could trigger an immune response, however. The team said they hope their results help other researchers in their investigative efforts.
Patients who have bullet fragments embedded in their bodies – either from new or old injuries – are often denied MRI studies due to ferromagnetic fears. However, new research published in the American Journal of Roentgenology from investigators at Emory University shows that X-ray and CT can be used to identify which fragments are safe for MRI. According to the team, non-ferromagnetic bullets have certain characteristics that show up on imaging that can allay radiologists’ worries. Specifically, bullets that leave a debris trail or appeared deformed on X-ray or CT are non-ferromagnetic. Typically, they are made of copper, copper alloy, a lead composition with a partial jacketed composition, or shotgun shot. They also did not produce heat or any detectable force or torque when tested in an MRI scanner in ballistic gel that mimicked human tissue. As a result of their work, the team created an algorithm providers can follow to help them ensure safe imaging.
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So much happened in 2020, but it was difficult to focus on much other than COVID-19. Still, radiology has a bright new year ahead of it. This week, we spoke with Dr. Mina Makary, an interventional radiologist with The Ohio State University Wexner Medical Center about what he sees as trends to watch throughout the next 12 months. Yes, he acknowledged that the pandemic is still the specialty’s top priority, but he also pointed to artificial intelligence, reimbursement cuts, 3D printing, interventional radiology, and policy and culture as areas to watch, as well. You can see all the details he shared in the article on www.diagnosticimaging.com.
And, finally, this week, we are sharing our full interview with David Larson, M.D., professor of radiology at Stanford. Larson is nationally recognized as an expert in radiology ethics, and in our discussion he outlines the main points radiologists must consider and remember in order to use artificial intelligence ethically in medical imaging, as well as the challenges that exist to doing so.
Here’s what he had to say.
Mammography News: FDA Grants Expanded 510(k) Clearance for AI-Powered SmartMammo Dx DBT Software
November 29th 2024Originally cleared by the FDA in 2021, the SmartMammo Dx software for digital breast tomosynthesis (DBT) can now be utilized with the Senographe Pristina mammography systems from GE HealthCare.
The Reading Room Podcast: Emerging Trends in the Radiology Workforce
February 11th 2022Richard Duszak, MD, and Mina Makary, MD, discuss a number of issues, ranging from demographic trends and NPRPs to physician burnout and medical student recruitment, that figure to impact the radiology workforce now and in the near future.
New Study Examines Short-Term Consistency of Large Language Models in Radiology
November 22nd 2024While GPT-4 demonstrated higher overall accuracy than other large language models in answering ACR Diagnostic in Training Exam multiple-choice questions, researchers noted an eight percent decrease in GPT-4’s accuracy rate from the first month to the third month of the study.