More Backing for CT Lung Screening

Yet another study is showing support for CT lung cancer screening. In a real-world study in Cancer, researchers tracked screening’s impact on military veterans, finding that it contributed to more early-stage diagnoses as well as lower all-cause mortality. 

It’s no secret that uptake of CT lung screening has been disappointing since the USPSTF in 2013 endorsed the test for high-risk people – mostly those with smoking histories. 

  • Uptake rates have been estimated to be under 10% by some studies, although recent research has shown that targeted interventions can improve that figure.

In the new study, researchers described results from the Veterans Health Administration’s effort to provide low-dose CT lung cancer screening to veterans from 2011 to 2018.

  • The researchers noted that smoking rates are higher among veterans, resulting in lung cancer incidence rates that are 76% higher than the general population. 

Researchers tracked outcomes retrospectively for 2.2k veterans who got screening before a lung cancer diagnosis and compared them to those with lung cancer who weren’t screened, finding that screening led to…

  • Higher rates of stage I diagnosis (52% vs. 27%)
  • Lower rates of stage IV diagnosis (11% vs. 32%)
  • Lower rates of cancer mortality (41% vs. 70%)
  • Lower rates of all-cause mortality (50% vs. 72%)

The sharp reduction in all-cause mortality is particularly striking. 

  • As we’ve discussed in the past, most population-based cancer screening tests have been shown to reduce cancer-specific deaths, but it’s been harder to show a decline in deaths from all causes. 

The study also illustrates the advantage of providing lung screening within a large, integrated healthcare system, where it’s easier to track at-risk individuals and direct them to screening if necessary.

The Takeaway

Of all the positive studies published so far this year on CT lung cancer screening, this one is the most exciting. The findings show that even in an environment of low lung screening uptake, dramatic benefits can be realized with the right approach.

Radiology’s Private-Practice Squeeze

It’s no secret that US radiology’s traditional private-practice model has been slowly fading away, but new numbers published in AJR illustrate the magnitude of the shift. The number of radiologist-affiliated and radiologist-only practices has dropped, even as the total number of US radiologists has gone up. 

Radiology has long prided itself on a cozy business model in which radiologists banded together as owner-operators of small private-practice groups that contracted their services with hospitals. 

  • This model has had many benefits for radiologists, but it’s begun to fray in the face of competitive threats like teleradiology providers, health system consolidation, and large national radiology groups like Radiology Partners.

Many radiologists have chosen to switch rather than fight, selling out to national groups or taking positions as employees within health systems.

  • Meanwhile, some practices that want to stay independent are finding strength in numbers by joining with other like-minded groups or seeking out multi-specialty medical groups. 

In the new study, researchers from the ACR’s Harvey L. Neiman Health Policy Institute analyzed CMS data from 2014 to 2023, tracking not only changes in the number of US radiologists but also their type of employment, finding …

  • The number of radiologists grew 17%, from 30.7k to 36k
  • But the number of radiologist-affiliated practices fell 15%, from 5.1k to 4.3k
  • The number of radiology-only practices fell 32%
  • The number of small radiology practices fell, with the decline varying by practice size: 1-2 radiologists -19%, 3-9 radiologists -34%, and 10-24 radiologists -25%
  • The number of large practices jumped, with the biggest increase – 349% – at very large practices (over 100 radiologists)
  • The mean number of radiologists per practice shot up 84%, from 9.7 to 17.9

Why the shift? The researchers theorized that much of it was driven by federal policy and reimbursement changes that incentivize consolidation, mostly to spread the risk and cost of compliance with various regulations like ACA and MACRA.

The Takeaway

There’s no question that radiology is changing – the question is what impact the changes will have on how radiologists perceive their work. The old guard may choose to rage against the dying of the light, while younger generations embrace the new model and its benefits for both professional careers and patient care. 

Radiologist Pay Rebounds

Radiologist pay grew 5.6% and radiology moved up one notch on Doximity’s list of highest-paid US medical specialties for 2023. Physician salaries generally rebounded last year after a decline in 2022.

The Doximity survey of 33k doctors found that overall physician pay grew 5.9% last year, a welcome rebound after a decline of 2.4% in 2022. 

  • In other good news, medicine’s gender pay gap narrowed in the new survey, with women making 23% less than men, down from 26% in 2022 and 28% in 2021.

For radiologists, their average annual compensation was $532k, up from $504k a year ago, and radiology jumped ahead of urology on the top 10 list to occupy the ninth spot. 

  • Still, radiology lagged a number of other specialties in terms of salary growth, ranging from hematology (+12.4%) to psychiatry (+7.2%). 

Other findings in the survey include …

  • Some 81% of physicians reported they are overworked, a number that’s actually down from 86% in 2022
  • 88% of respondents said their clinical practice has been affected by the physician shortage
  • 86% of those surveyed said they are concerned about the US healthcare system’s ability to care for its aging population

The Doximity results roughly track recently released salary data from Medscape, which pegged radiologist salaries at $498k in 2023, up 3.1% and ranking sixth on the list of highest-paid specialties. 

The Takeaway

Say what you want about rising workload and burnout in radiology – radiologists are still among the best-compensated physicians in medicine. And the situation in the US is in sharp contrast to Japan, where radiology is one of the lowest-paid specialties (see our article in The Wire section below).

Is Radiology’s AI Edge Fading?

Is radiology’s AI edge fading, at least when it comes to its share of AI-enabled medical devices being granted regulatory authorization by the FDA? The latest year-to-date figures from the agency suggest that radiology’s AI dominance could be declining. 

Radiology was one of the first medical specialties to go digital, and software developers have targeted the field for AI applications like image analysis and data reconstruction.

  • Indeed, FDA data from recent years shows that radiology makes up the vast majority of agency authorizations for AI- and machine learning-enabled medical devices, ranging from 86% in 2020 and 2022 to 79% in 2023

But in the new data, radiology devices made up only 73% of authorizations from January-March 2024. Other data points indicate that the FDA …

  • Authorized 151 new devices since August 2023
  • Reclassified as AI/ML-enabled 40 devices that were previously authorized 
  • Authorized a total of 882 devices since it began tracking the field 

      In an interesting wrinkle, many of the devices on the updated list are big-iron scanners that the FDA has decided to classify as AI/ML-enabled devices. 

      • These include CT and MRI scanners from Siemens Healthineers, ultrasound scanners from Philips and Canon Medical Systems, an MRI scanner from United Imaging, and the recently launched Butterfly iQ3 POCUS scanner. 

      The additions could be a sign that imaging OEMs increasingly are baking AI functionality into their products at a basic level, blurring the line between hardware and software. 

      The Takeaway

      It should be no cause for panic that radiology’s share of AI/ML authorizations is declining as other medical specialties catch up to the discipline’s head start. The good news is that the FDA’s latest figures show how AI is becoming an integral part of medicine, in ways that clinicians may not even notice.

      Doctors Work Harder for Less

      Medicare reimbursement to physicians per beneficiary has declined over the last 16 years, with radiologists among the biggest losers. That’s according to a new study by the ACR’s Harvey L. Neiman Health Policy Institute, which confirms what many physicians already knew: they are working harder for less money.

      It’s no secret that the US government has been struggling to rein in healthcare costs for decades. 

      CMS has a number of tools at its disposal for controlling Medicare and Medicaid costs, one of which is the relative value unit (RVU) scale. 

      • RVUs – when multiplied by monetary conversion factors – basically set the amount of money the agency pays physicians per unit of work, with CMS typically reducing the conversion factor when it needs to cut Medicare spending. 

      In the new study in the journal Inquiry, Neiman HPI researchers analyzed trends in RVU and conversion factor levels per Medicare beneficiary from 2005 to 2021, analyzing changes to calculate how much work providers have to do to deliver a unit of care. Findings included …

      • Reimbursement per Medicare beneficiary after inflation adjustment fell 2.3% for physicians as a whole
      • Radiology saw one of the biggest declines in MPFS reimbursement per beneficiary, ranking 31st on a list of 39 medical specialties, with a 25% decrease
      • Reimbursement has risen 207% for non-physician practitioners

      What’s driving the declines? The Neiman HPI researchers identified the federal government’s budget neutrality rules for Medicare, which stipulate that increases in one area have to be offset by declines elsewhere.

      The Takeaway

      The new findings confirm what many physicians have suspected – they are not only working harder for less, but non-physician practitioners seem to be getting a bigger piece of the pie. Combined with a recent report showing that radiologist salaries didn’t keep pace with inflation in 2023, it’s not a pretty picture. 

      Teleradiology Malpractice Risk

      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. 

      Imaging and US Healthcare Costs

      In the debate over rising US healthcare costs, medical imaging is often painted as a bad guy. But a new study in Health Affairs Scholar claims that since 2010, spending on imaging services has not grown at the same rate as other medical services. 

      It’s no secret that the US spends far more on healthcare per capita than other developed countries, spending 16.6% of GDP as of 2022 according to OECD data. 

      • For point of reference, Germany spends 12.7%, France spends 12.1%, and most other developed countries spend under 12% of GDP. 

      Reasons why the US is such an outlier have been blamed on a variety of factors, such as pharmaceutical prices, physician salaries, administrative costs, and the fragmented nature of the US healthcare system. 

      • But medical imaging is often singled out for criticism, perhaps due to the high cost of scanners and the explosion of imaging volume since the advent of cross-sectional technologies like CT and MRI in the 1970s and 1980s. 

      This has led the US government to exert major pressure on imaging reimbursement in the Medicare and Medicaid systems, starting with the Deficit Reduction Act of 2005 and continuing to the present day, while private insurers have employed tools like prior authorization. 

      The new study indicates that these efforts may have accomplished their mission. Researchers from the ACR’s Harvey L. Neiman Health Policy Institute analyzed imaging’s contribution to overall growth of medical costs from 2010 to 2021 in employer-sponsored insurance plans, finding …

      • Spending on medical imaging grew 36% 
      • Spending for all other healthcare services grew 64% 
      • Two-thirds of the growth in imaging spending was due to general price inflation
      • Only one-fifth was due to increased utilization
      • Imaging’s share of total US healthcare spending fell from 10.5% to 8.9%

      The findings indicate that efforts by the US government and private payors to drive down imaging utilization are working … but at the price of overworked radiology staff.

      • Imaging cuts could also be leading to patient access issues, as the study found that the percentage of patients undergoing imaging fell from 46% in 2010 to 40% in 2021. 

      The Takeaway

      The new study reinforces what imaging advocates have been saying for years – that medical imaging isn’t a major cause for runaway healthcare spending in the US. The question is whether anyone outside of radiology is listening.

      AI Dominates at RSNA 2023

      Take a deep breath. You survived another RSNA conference.

      While a few hardy souls are still enjoying educational sessions in the cozy confines of McCormick Place, the final day of the exhibit floor yesterday marks the end of RSNA 2023 for most attendees. And what a show it was. 

      Predictions were that AI would dominate the scientific sessions at RSNA 2023, a forecast that largely panned out. A November 28 session was a case in point, in which a series of top-quality papers were presented on one of the most promising use cases of AI, for breast screening:

      • A homegrown AI algorithm that analyzed screening breast ultrasound exams in addition to FFDM and DBT mammograms boosted sensitivity for detecting cancer in 12.5k patients, with better sensitivity for women with dense breasts (71% vs. 60%) and non-dense breasts (79% vs. 63%)
      • AI did a good job of detecting breast arterial calcification (BAC) when used prospectively to analyze screening mammograms in 16k women across 15 sites.  It found 15% of women had BAC, a possible marker for atherosclerotic disease
      • Swedish researchers used their VAI-B validation platform to compare three AI algorithms (Therapixel, Lunit, and Vara) in 34k women, finding that using AI with a single radiologist boosted sensitivity 10-30% compared to double reading, with a slight loss in specificity (2-7%). VAI-B could be used to validate AI implementation and guide purchasing decisions
      • Why does AI miss some breast cancers? South Korean researchers addressed this question by analyzing 1.1k patients with invasive cancers in which AI had a miss rate of 14%. Luminal cancers were missed most often
      • Adding AI analysis of prior images to current studies with FFDM and DBT boosted sensitivity for cancer detection in 30k patients, with sensitivity the highest for two years of priors compared to no priors (74% vs. 70%)

      The Takeaway

      This week’s research points to an exciting near-term future in which AI will help make mammography screening more accurate while helping breast radiologists perform their jobs more efficiently. Landmark studies toward this end were published in 2023 – this week’s RSNA conference shows that we can expect the momentum to continue in 2024. 

      Welcome to RSNA 2023

      It’s off to the races at RSNA 2023 as radiology’s showcase conference kicked off on Sunday. 

      “Leading Through Change” is the theme of this year’s meeting, and it’s an appropriate slogan for a specialty that seems on the cusp of disruption with the growing use of AI, deep learning, and other tools. 

      • AI is being featured prominently in scientific presentations and vendor exhibits in McCormick Place, with a particular focus on whether large language models like ChatGPT can find practical application in radiology. Early research is promising but still inconclusive.

      Another major focus at RSNA 2023 has been lung cancer screening, with Sunday afternoon sessions investigating how screening can be expanded

      • Researchers mined a database of 32k women who got screening mammography to find eligible candidates for lung screening, finding 5% who met screening criteria. 
      • Using the USPTSF’s 2021 guideline revision to find screening candidates led to shorter smoking histories (42 vs. 29 pack-years) and slightly more women being eligible (48% vs. 46%). 
      • ChatGPT gave more correct answers than Google Bard to non-expert questions on lung screening (71% vs. 52%).
      • ChatGPT, GPT-4, and Bard needed multiple iterations to produce reports readable by patients. 

      AI is also proving its value for selecting screening candidates and identifying lung pathology: 

      • An AI algorithm analyzed chest X-rays to determine whether an individual would benefit from CT lung cancer screening – even if they don’t smoke. In 17.4k patients, the model classified 28% as high risk, 2.9% of whom were later diagnosed with lung cancer, a higher level than the 1.3% six-year threshold at which guidelines recommend CT lung screening.
      • A deep learning algorithm analyzed chest X-rays in a cohort of 10k patients to predict who would develop type 2 diabetes, turning in better accuracy than a model that only looked at clinical factors like age, BMI and HbA1c levels (AUCs:  0.84 vs. 0.79). 

      Looking for more coverage of RSNA 2023? Be sure to check out our videos from the technical exhibit floor, which you can find on our new Shows page

      The Takeaway
      The RSNA has always been known as the Super Bowl of radiology, and this year’s meeting is off to a great start. Be sure to check back on our Twitter/X, LinkedIn, and YouTube pages for more coverage of this week’s events in Chicago.

      Predicting the Future of Radiology AI

      Making predictions is a messy business (just ask Geoffrey Hinton). So we’re always appreciative whenever key opinion leaders stick their necks out to offer thoughts on where radiology is headed and the major trends that will shape the specialty’s future. 

      Two of radiology’s top thought leaders on AI and imaging informatics – Curtis Langlotz, MD, PhD, and Paul Chang, MD – gaze into the crystal ball in two articles published this week in Radiology as part of the journal’s centennial celebration. 

      Langlotz offers 10 predictions on radiology AI’s future, briefly summarized below:

      • Radiology will continue its leadership position when it comes to AI adoption in medicine, as evidenced by its dominance of FDA marketing authorizations
      • Virtual assistants will help radiologists draft reports – and reduce burnout
      • Radiology workstations will become cloud-based cockpits that seamlessly unify image display, reporting, and AI
      • Large language models like ChatGPT will help patients better understand their radiology reports
      • The FDA will reform its regulation of AI to be more flexible and speed AI authorizations (see our article in The Wire below)
      • Large databases like the Medical Imaging and Data Resource Center (MIDRC) will spur data sharing and, in turn, more rapid AI development

      Langlotz’s predictions are echoed by Chang’s accompanying article in Radiology in which he predicts the future of imaging informatics in the coming age. Like Langlotz, Chang sees the new array of AI-enabled tools as beneficial agents that will help radiologists manage growing workloads through dashboards, enhanced radiology reports, and workflow automation. 

      The Takeaway

      This week’s articles are required reading for anyone following the meteoric growth of AI in radiology. Far from Hinton’s dystopian view of a world without radiologists, Langlotz and Chang predict a future in which AI and IT technologies assist radiologists to do their jobs better and with less stress. We know which vision we prefer.

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