Tag: computed tomography

CT First for Chest Pain

Posted on by Brian Casey

CT should be used first to evaluate patients with stable chest pain who are suspected of having a heart attack. That’s the message of a paper being presented this week at the American College of Cardiology Cardiovascular Summit in Washington, DC.

CT is proving itself useful for a variety of applications in cardiac imaging, from predicting heart disease risk through coronary calcium scores to assessing whether people with chest pain need treatment like invasive angiography – or can be sent home and monitored.

  • But cardiac CT often runs up against decades of clinical practice that relies on tools like stress testing or diagnostic invasive coronary angiography for evaluating patients, with the CT-first strategy reserved for a limited number of people, such as those with unestablished coronary artery disease. 

But the new study suggests that the CT-first approach could be used for the vast majority of patients presenting with stable chest pain. 

  • A research team led by senior author Markus Scherer, MD, of Atrium Health-Sanger Heart & Vascular Institute in Charlotte, North Carolina tested the strategy in 786 patients seen from October 2022 to June 2023 who had no prior diagnosis of coronary artery disease and underwent elective invasive angiography to evaluate suspected angina.

The CT-first strategy compared CT angiography with provisional FFRCT testing to traditional evaluation pathways, which included stress echo, stress myocardial perfusion imaging, stress MRI, or no invasive testing before direct referral to angiography. Revascularization rates by strategy were as follows … 

  • 62% for CT-first
  • 50% for stress MRI
  • 40% for stress echo
  • 34% for no prior test
  • 31% for stress MPI

The Takeaway

The results presented this week offer real-world evidence that support recent clinical studies backing broader use of CT for patients with chest pain. Given CT’s advantages in terms of cost and noninvasiveness, the findings raise the question of whether more can be done to get clinicians to adhere to established guidelines calling for a CT-first protocol. 

AI Powers Opportunistic Screening

Posted on by Brian Casey

The growing power of AI is opening up new possibilities for opportunistic screening – the detection of pathology using data acquired for other clinical indications. The potential of CT-based opportunistic screening – and AI’s role in its growth – was explored in a session at RSNA 2023.

What’s so interesting about opportunistic screening with CT? 

  • As one of imaging’s most widely used modalities, CT scans are already being acquired for many clinical indications, collecting body composition data on muscle, fat, and bone that can be biomarkers for hidden pathology. 

What’s more, AI-based tools are replacing many of the onerous manual measurement tasks that previously required radiologist involvement. There are four primary biomarkers for opportunistic screening, which are typically related to several major pathologies, said Perry Pickhardt, MD, of the University of Wisconsin-Madison, who led off the RSNA session:

  • Skeletal muscle density (sarcopenia)
  • Hard calcified plaque, either coronary or aortic (cardiovascular risk)
  • Visceral fat (cardiovascular risk)
  • Bone mineral density (osteoporosis and fractures) 

But what about the economics of opportunistic screening? 

  • A recent study in Abdominal Radiology found that in a hypothetical cohort of 55-year-old men and women, AI-assisted opportunistic screening for cardiovascular disease, osteoporosis, and sarcopenia was more cost-effective compared to both “no-treatment” and “statins for all” strategies – even assuming a $250/scan charge for use of AI.

But there are barriers to opportunistic screening, despite its potential. In a follow-up talk, Arun Krishnaraj, MD, of UVA Health in Virginia said he believes fully automated AI algorithms are needed to avoid putting the burden on radiologists. 

And the regulatory environment for AI tools is complex and must be navigated, said Bernardo Bizzo, MD, PhD, of Mass General Brigham.

Ready to take the plunge? The steps for setting up a screening program using AI were described in another talk by John Garrett, PhD, Pickhardt’s colleague at UW-Madison. This includes: 

  • Normalizing your data for AI tools
  • Identifying the anatomical landmarks you want to focus on
  • Automatically segmenting areas of interest
  • Making the biomarker measurements
  • Plugging your data into AI models to predict outcomes and risk-stratify patients

The Takeaway

Opportunistic screening has the potential to flip the script in the debate over radiology utilization, making imaging exams more cost-effective while detecting additional pathology and paving the way to more personalized medicine. With AI’s help, radiologists have the opportunity to place themselves at the center of modern healthcare. 

How COVID Crashed CT Scanners in China

Posted on by Brian Casey

In the early days of the COVID-19 pandemic in China, hospitals were performing so many lung scans of infected patients that CT scanners were crashing. That’s according to an article based on an interview with a Wuhan radiologist that provides a chilling first-hand account of radiology’s role in what’s become the biggest public health crisis of the 21st century.

The interview was originally published in 2022 by the Chinese-language investigative website Caixin and was translated and published this month by U.S. Right to Know, a public health advocacy organization. 

In a sign of the information’s sensitivity, the original publication on Caixin’s website has been deleted, but U.S. Right to Know obtained the document from the US State Department under the Freedom of Information Act. 

Radiologists at a Wuhan hospital noticed how COVID cases began doubling every 3-4 days in early January 2020, the article states, with many patients showing signs of ground-glass opacities on CT lung scans – a telltale sign of COVID infection. But Chinese authorities suppressed news about the rapid spread of the virus, and by January 11 the official estimate was that there were only 41 COVID cases in the entire country.

In reality, COVID cases were growing rapidly. CT machines began crashing in the fourth week of January due to overheating, said the radiologist, who estimated the number of cases in Wuhan at 10,000 by January 21. Hospitals were forced to turn infected patients away, and many people were so sick they were unable to climb onto X-ray tables for exams. Other details included: 

  • Chinese regulatory authorities denied that human-to-human transmission of the SARS CoV-2 virus was occurring even as healthcare workers began falling ill
  • Many workers at Chinese hospitals were discouraged from wearing masks in the pandemic’s early days to maintain the charade that human-to-human contact was not possible – and many ended up contracting the virus
  • Radiologists and other physicians lived in fear of retaliation if they spoke up about the virus’ rapid spread

The Takeaway

The article provides a stunning behind-the-scenes look at the early days of a pandemic that would go on to reshape the world in 2020. What’s more, it demonstrates the vital role of radiology as a front-line service that’s key to the early identification and treatment of disease – even in the face of bureaucratic barriers to delivering quality care.

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