Tag: teleradiology

Teleradiology AI’s Mixed Bag

Posted on by Brian Casey

An AI algorithm that examined teleradiology studies for signs of intracranial hemorrhage had mixed performance in a new study in Radiology: Artificial Intelligence. AI helped detect ICH cases that might have been missed, but false positives slowed radiologists down. 

AI is being touted as a tool that can detect unseen pathology and speed up the workflow of radiologists facing an environment of limited resources and growing image volume.

  • This dynamic is particularly evident at teleradiology practices, which frequently see high volumes during off-hour shifts; indeed, a recent study found that telerad cases had higher rates of patient death and more malpractice claims than cases read by traditional radiology practices.

So teleradiologists could use a bit more help. In the new study, researchers from the VA’s National Teleradiology Program assessed Avicenna.ai’s CINA v1.0 algorithm for detecting ICH on STAT non-contrast head CT studies.

  • AI was used to analyze 58.3k CT exams processed by the teleradiology service from January 2023 to February 2024, with a 2.7% prevalence of ICH.

Results were as follows…

  • AI flagged 5.7k studies as positive for acute ICH and 52.7k as negative
  • Final radiology reports confirmed that 1.2k exams were true positives for a sensitivity of 76% and a positive predictive value of 21%
  • There were 384 false negatives (missed ICH cases), for a specificity of 92% and a negative predictive value of 99.3%
  • The algorithm’s performance at the VA was a bit lower than in previously published literature
  • Cases that the algorithm falsely flagged as positive took over a minute longer to interpret than prior to AI deployment
  • Overall, case interpretation times were slightly lower after AI than before

One issue to note is that the CINA algorithm is not intended for small hemorrhages with volumes < 3 mL; the researchers did not exclude these cases from their analysis, which could have reduced its performance.

  • Also, at 2.7% the VA’s teleradiology program ICH prevalence was lower than the 10% prevalence Avicenna has used to rate its performance.

The Takeaway

The new findings aren’t exactly a slam dunk for AI in the teleradiology setting, but in terms of real-world results they are exactly what’s needed to assess the true value of the technology compared to outcomes in more tightly controlled environments.

Teleradiology Malpractice Risk

Posted on by Brian Casey

A new study in Radiology comes to an explosive conclusion: medical malpractice cases involving teleradiology interpretation of medical images more frequently involved patient death and had higher payment amounts. 

Perhaps no technology has wrought greater changes on the field of medical imaging than teleradiology. 

  • By leveraging radiology’s conversion to digital imaging and the rapid expansion of Internet bandwidth, teleradiology makes it possible for medical images to be interpreted independent of the radiologist’s location, with studies sometimes literally sent around the world. 

But teleradiology has had its share of unintended consequences, such as the emergence of nighthawk and specialty teleradiology firms that have seized hospital contracts from traditional radiology groups. 

But this week’s study in Radiology adds a new wrinkle, suggesting that teleradiology could actually have an additional malpractice risk. Researchers analyzed 3,609 malpractice claims, of which 135 involved teleradiology, finding that teleradiology cases…

  • Saw patient death occur more often (36% vs. 20%)
  • More frequently saw communication problems among providers (26% vs. 13%)
  • More often closed with indemnity payments (59% vs. 41%)
  • Had higher median indemnity payments ($339k vs. $214k) 

Why might problems be more frequent in teleradiology? The authors offered several reasons, including …

  • Teleradiologists may not have access to EMR and other patient data
  • Teleradiology interpretations are often provided at night and on weekends/holidays
  • Claims involving neurology and the emergency setting were more common, illustrating the challenges in these areas

Potential solutions could involve making sure that teleradiologists have access to EMR data, and by performing overreads of interpretations delivered on nights and weekends. 

The Takeaway
The findings have disturbing implications, not only for dedicated teleradiology providers but also for traditional radiology practices that use teleradiology as part of their service offerings. And as noted in an accompanying editorial, they could provide ammunition to teleradiology’s opponents, who continue to rail against the technology that has done so much to change radiology. 

Is Head CT Overused in the ED?

Posted on by Brian Casey

A new study suggests that head CT could be overused in the emergency department for patients presenting with conditions like headache and dizziness. Writing in a paper in Internal and Emergency Medicine, researchers looking at CT angiography use at a large medical center found a big increase in CTA utilization – even as the rate of positive findings dropped. 

CTA is a powerful tool that can quickly and efficiently give clinicians information to guide treatment of acute neurovascular conditions like aneurysm and stroke. 

  • As such, many emergency departments have been installing their own CT scanners to enable them to scan emergent patients without transporting them to the radiology department. 

But with great power comes great responsibility, and there is always the temptation to scan first and ask questions later. 

  • To better understand changing CTA use in the emergency setting, researchers from the Harvey L. Neiman Health Policy Institute analyzed CTA exams at a level 1 trauma center that sees about 110k emergency patients a year.

Researchers analyzed 25k ED visits from 2017 to 2021 and correlated them to head and neck CTA exams for headache and/or dizziness, finding …

  • The rate of CTA exams rose 64%, from 7.9% of ED visits to 13%
  • Symptomatic patients were 15% more likely to have a CTA in 2021 versus 2017
  • The rate of positive CTA findings fell 38%, from 17% to 10%
  • Patients with private insurance were more likely to have CTA (OR=1.44)
  • Black patients were less likely to be scanned (OR=0.69)

The researchers said the findings indicate the need for better clinical decision support tools, which they believe can help emergency physicians provide an accurate diagnosis without exposing patients to unnecessary radiation and incurring additional cost. 

The Takeaway

This study further confirms widespread accounts that head and neck CTA is overused and on the rise. As the US government backs off on its attempt to force clinical decision support on referring physicians, it may be up to health systems and providers themselves to ensure more appropriate utilization – in a way that doesn’t rely on heavy-handed tools like prior authorization. 

RadNet’s UK Lung Cancer Screening Acquisition

Posted on by Jake Fishman

RadNet advanced its AI-led cancer screening strategy, acquiring a 75% stake in Heart & Lung Health, a UK-based teleradiology network with a direct connection to the NHS’ lung cancer screening program.

Heart & Lung Health (HLH) has a network of over 70 cardiothoracic radiologists, and provides teleradiology reporting services for the NHS and a variety of UK hospitals and academic institutions.

Acquiring a UK telerad company might seem out of character for RadNet, which has historically focused its M&A on US-based imaging centers (and more recently global AI developers), only mentioned Europe once in its 2021 annual report, and exited the teleradiology business in 2020. However…

  • HLH is the leading reporting provider for NHS England Targeted Lung Health Check (TLHC), an AI-enabled lung cancer screening pilot program that might pave the way for a UK-wide program. 
  • TLHC requires all radiologists to use AI with their LDCT screening interpretations, suggesting that AI might also be required in a future UK-wide program.
  • HLH uses RadNet’s Aidence subsidiary’s lung cancer AI tools, and HLH will work with Aidence to further develop its solutions.

The Takeaway

RadNet started 2022 by acquiring two major cancer screening AI companies (Aidence and Quantib), which combined with its DeepHealth breast cancer AI business to support its ambitious new strategy to become a population-scale cancer screening leader. 

That goal might have seemed like a longshot to some, given AI’s uncertain path forward and RadNet’s geographic concentration in just seven US states. However, last week’s HLH acquisition showed that RadNet remains very committed to AI-driven cancer screening leadership, and its strategy might not be as geographically-challenged as some initially thought.

Sirona Medical Acquires Nines AI, Talent

Posted on by Jake Fishman

Sirona Medical announced its acquisition of Nines’ AI assets and personnel, representing notable milestones for Sirona’s integrated RadOS platform and the quickly-changing imaging AI landscape.

Acquisition Details – Sirona acquired Nines’ AI portfolio (data pipeline, ML engines, workflow/analytics tools, AI models) and key team members (CRO, Direct of Product, AI engineers), while Nines’ teleradiology practice was reportedly absorbed by one of its telerad customers. Terms of the acquisition weren’t disclosed, although this wasn’t a traditional acquisition considering that Sirona and Nines had the same VC investor.

Sirona’s Nines Strategy – Sirona’s mission is to streamline radiologists’ overly-siloed workflows with its RadOS radiology operating system (unifies: worklist, viewer, reporting, AI, etc.), and it’s a safe bet that any acquisition or investment Sirona makes is intended to advance this mission. With that…

  • Nine’s most tangible contributions to Sirona’s strategy are its FDA-cleared AI models: NinesMeasure (chest CT-based lung nodule measurements) and NinesAI Emergent Triage (head CT-based intracranial hemorrhage and mass effect triage). The AI models will be integrated into the RadOS platform, bolstering Sirona’s strategy to allow truly-integrated AI workflows. 
  • Nine’s personnel might have the most immediate impact at Sirona, given the value/scarcity of experienced imaging software engineers and the fact that Nines’ product team arguably has more hands-on experience with radiologist workflows than any other imaging AI firm (at least AI firms available for acquisition).
  • Nine’s other AI and imaging workflow assets should also help support Sirona’s future RadOS and AI development, although it’s harder to assess their impact for now.

The AI Shakeup Angle – This acquisition has largely been covered as another example of 2022’s AI shakeup, which isn’t too surprising given how active this year has been (MaxQ’s shutdown, RadNet’s Aidence/Quantib acquisitions, IBM shedding Watson Health). However, Nines’ strategy to combine a telerad practice with in-house AI development was quite unique and its decision to sell might say more about its specific business model (at its scale) than it does about the overall AI market.

The Takeaway

Since the day Sirona emerged from stealth, it’s done a masterful job articulating its mission to solve radiology’s workflow problems by unifying its IT infrastructure. Acquiring Nines’ AI assets certainly supports Sirona’s unified platform messaging, while giving it more technology and personnel resources to try to turn that message into a reality.

Meanwhile, Nines becomes the latest of surely many imaging AI startups to be acquired, pivoted, or shut down, as AI adoption evolves at a slower pace than some VC runways. Nines’ strategy was really interesting, they had some big-name founders and advisors, and now their work and teams will live on through Sirona.

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