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).

Lung Screening Narrows Disparities

New research confirms that not only does low-dose CT screening reduce lung cancer mortality, it can also narrow health disparities. Researchers found that screening’s beneficial impact was greater at lower socioeconomic levels in a new study published in Lancet Regional Health – Europe.

As we mentioned in our last issue, CT lung cancer screening is gaining momentum globally; at the same time, researchers have documented greater mortality and morbidity for a variety of diseases among racial minorities and at lower socioeconomic levels.

  • This difference can be especially profound when it comes to lung disease, given higher smoking rates among some minority groups and economically disadvantaged populations.

In the original UK Lung Cancer Screening Trial (UKLS) in 2021, researchers found that a single CT screening round produced a 16% lung cancer mortality reduction. 

  • The new study is a secondary analysis of UKLS to investigate whether CT lung screening’s impact differed by socioeconomic status, which is important given that smoking occurs in England at higher rates in the most deprived neighborhoods compared to wealthier ones (24% vs. 6.8%).

UKLS researchers compared lung cancer mortality rates in 4k individuals in different groups classified by a widely used socioeconomic barometer. They found that … 

  • CT lung screening had the same lung cancer mortality benefit in both low and high socioeconomic groups (-19% vs. -20%)
  • But there was a bigger reduction in death from COPD in lower socioeconomic groups (-34% vs. +4%)
  • And fewer deaths from other lung diseases (-32% vs. +10%)
  • While cardiovascular mortality was also lower (-30% vs. -13%)
  • All-cause mortality was lower in lower socioeconomic groups – a benefit not seen at higher levels

Lung screening’s reduction in all-cause mortality is particularly intriguing, as this is an accomplishment that has eluded most other cancer screening tests – a point that has been repeatedly hammered home by screening skeptics.

The Takeaway

The new findings highlight how – to a greater degree than other major cancer screening tests – CT lung screening has the potential to address ongoing racial and socioeconomic healthcare disparities. It’s yet another reason to press for broader adoption of lung screening.

CT Lung Screening Shows Progress at ATS 2024

Making CT lung cancer screening more effective has been a hot topic at the American Thoracic Society meeting, which convened this weekend in San Diego. Presentations at ATS 2024 have ranged from improving screening compliance rates to eliminating racial disparities in screening attendance.

After years of fits and starts, low-dose CT lung cancer screening appears to be finally making progress. 

  • While the US still struggles with overly restrictive screening criteria and convoluted reimbursement rules, the rest of the world – including Australia, Germany, and Taiwan – is moving ahead with population-based screening programs designed to counter the tobacco epidemic’s deadly scourge.

At ATS 2024, investigators are presenting research to ensure that the benefits of CT lung cancer screening are delivered to those who need it, with the following highlights …

  • Researchers at the University of Minnesota saw a 7.2% completion rate for screening-specific low-dose CT among 91k eligible individuals – an indication of “overall poor uptake of screening” 
  • To improve uptake, another group implemented a centralized nurse coordinator for lung screening, resulting in a 23-day reduction in time from initial consultation to report delivery as well as better adherence to eligibility criteria
  • Patients who self-identify as Black are more likely to miss a scheduled CT screening appointment (OR=2.05), while Hispanic patients also have high miss rates (OR=1.92) as do those with limited English proficiency (OR=1.72). The numbers highlight the need for patient conversations to boost completion rates
  • Incidence rates of lung and bronchus cancer dropped from 2007-2019 compared to 1999-2006, underscoring the importance of smoking cessation and supporting current USPSTF age criteria for lung screening
  • Pulmonary physicians significantly overestimated their patients’ lung screening completion rates, with almost half thinking the rate was higher than 60% when it was actually 17%. Researchers suggested interventions for improving completion rates

The Takeaway

The fact that ATS 2024 has seen so many presentations on CT lung cancer screening – the vast majority presented by US authors – indicates that low screening rates haven’t discouraged American researchers and clinicians. The presentations underscore the progress being made toward making the benefits of lung screening available to Americans who would benefit from it.

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.

      Slashing CT Radiation Dose

      Cutting CT radiation dose should be the goal of every medical imaging facility. A new paper in European Radiology offers a promising technique that slashed CT dose to one-tenth of conventional CT – and just twice that of a standard chest X-ray.

      CT’s wide availability, excellent image quality, and relatively low cost make it an invaluable modality for many clinical applications.

      • CT proved particularly useful during the COVID-19 pandemic for diagnosing lung pathology caused by the virus, and it continues to be used to track cases of long COVID.

      But patient monitoring can involve multiple CT scans, leading to cumulative radiation exposure that can be concerning, especially for younger people.

      • Researchers in Austria wanted to see if they could use commercially available tools to produce ultra-low-dose CT scans, and then assess how they compared to conventional CT for tracking patients with long COVID.

      Using Siemens Healthineers’ Somatom Drive third-generation dual-source CT scanner, they adjusted the parameters on the system’s CAREDose automated exposure control and ADMIRE iterative reconstruction to drive down dose as much as possible.

      • Other ultra-low-dose CT settings versus conventional CT included fixed tube voltage (100 kVp vs. 110 kVp), tin filtration (enabled vs. disabled), and CAREDose tube current modulation (enabled – weak vs. enabled – normal). 

      They then tested the settings in a group of 153 patients with long COVID seen from 2020 to 2021; both ultra-low-dose and conventional CT scans were compared by radiologists, finding … 

      • Mean entrance-dose radiation levels with ultra-low-dose CT were less than one-tenth those of conventional CT in (0.21 mSv vs. 2.24 mSv); a two-view chest X-ray is 0.1 mSv
      • Image quality was rated 40% lower on a five-point scale (3.0 vs. 5.0)
      • But all ultra-low-dose scans were rated as diagnostic quality
      • Intra-reader agreement between the two techniques was “excellent,” at 93%

      The findings led the researchers to conclude that ultra-low-dose CT could be a good option for tracking long COVID, such as in younger patients. 

      The Takeaway

      The study demonstrates that CT radiation dose can be driven down dramatically through existing commercially available tools. While this study covers just one niche clinical application, such tools could be applied to a wider range of uses, ensuring that the benefits of CT will continue to be made available at lower radiation doses than ever.

      Fine-Tuning AI for Breast Screening

      AI has shown in research studies it can help radiologists interpret breast screening exams, but for routine clinical use many questions remain about the optimal AI parameters to catch the most cancers while generating the fewest callbacks. Fortunately, a massive new study out of Norway in Radiology: Artificial Intelligence provides some guidance. 

      Recent research such as the MASAI trial has already demonstrated that AI can help reduce the number of screening mammograms radiologists have to review, and for many low-risk cases eliminate the need for double-reading, which is commonplace in Europe. 

      • But growing interest in breast screening AI is tempered by the field’s experience with computer-aided detection, which was introduced over 20 years ago but generated many false alarms that slowed radiologists down. 

      Fast forward to 2024. The new generation of breast AI algorithms seems to have addressed CAD’s shortcomings, but it’s still not clear exactly how they can best be used. 

      • Researchers from Norway’s national breast screening program tested one mammography AI tool – Lunit’s Insight MMG – in a study with data obtained from 662k women screened with 2D mammography from 2004 to 2018. 

      Researchers tested AI with a variety of specificity and sensitivity settings based on AI risk scores; in one scenario, 50% of the highest risk scores were classified as positive for cancer, while in another that threshold was set to 10%. The group found …

      • At the 50% cutoff, AI would correctly identify 99% of screen-detected cancers and 85% of interval cancers. 
      • At the 10% cutoff, AI would detect 92% of screen-detected cancers and 45% of interval cancers 
      • AI understandably performed better in identifying false-positive cases as negative at the 10% threshold than 50% (69% vs. 17%)
      • AI had a higher AUC than double-reading for screen-detected cancers (0.97 vs. 0.88)

      How generalizable is the study? It’s worth noting that the research relied on AI of 2D mammography, which is prevalent in Europe (most mammography in the US employs DBT). In fact, Lunit is targeting the US with its recently cleared Insight DBT algorithm rather than Insight MMG. 

      The Takeaway

      As with MASAI, the new study offers an exciting look at AI’s potential for breast screening. Ultimately, it may turn out that there’s no single sensitivity and specificity threshold at which mammography AI should be set; instead, each breast imaging facility might choose the parameters they feel best suit the characteristics of their radiologists and patient population. 

      Headwinds Slow AI Funding

      Venture capital funding of medical imaging AI developers continues to slow. A new report from Signify Research shows that funding declined 19% in 2023, and is off to a slow start in 2024 as well. 

      Signify tracks VC funding on an annual basis, and previous reports from the UK firm showed that AI investment peaked in 2021 and has been declining ever since. 

      • The report’s author, Signify analyst Ellie Baker, sees a variety of factors behind the decline, chief among them macroeconomic headwinds such as tighter access to capital due to higher interest rates. 

      Total Funding Value Drops – Total funding for 2023 came in at $627M, down 19% from $771M in 2022. Funding hit a peak in 2021 at $1.1B.

      Deal Volume Declines – The number of deals in 2023 fell to 35, down 30% from 50 the year before. Deal volume peaked in 2021 at 63. And 2024 isn’t off to a great start, with only five deals recorded in the first quarter. 

      Deals Are Getting Bigger – Despite the declines, the average deal size grew last year, to $19M, up 23% versus $15M in 2022. 

      HeartFlow Rules the Roost – HeartFlow raised the most in 2023, fueled by a massive $215M funding round in April 2023, while Cleerly held the crown in 2022.

      US Funding Dominates – On a geographic basis, funding is shifting away from Europe (-46%) and Asia-Pacific (no 2023 deals) and back to the Americas, which generated over 70% of the funding raised last year. This may be due to the US providing faster technology uptake and more routes to reimbursement.

      Early Bird Gets the Worm – Unlike past years in which later-stage funding dominated, 2024 has seen a shift to early-stage deals with seed funding and Series A rounds, such as AZmed’s $16M deal in February 2024. 

      $100M Club Admits New Members – Signify’s exclusive “$100M Club” of AI developers has expanded to include Elucid and RapidAI. 

      The Takeaway

      Despite the funding drop, Signify still sees a healthy funding environment for AI developers ($627M is definitely a lot of money). That said, AI software developers are going to have to make a stronger case to investors regarding revenue potential and a path to ROI. 

      USPSTF’s Mammography Letdown?

      Last year’s relief that the USPSTF would lower its recommended starting age for breast screening to 40 gave way to frustration this week that the group did not go farther in its final decision on mammography recommendations. 

      In a series of papers in JAMA journals this week, the USPSTF tackled a range of breast screening issues, from the age at which screening should start to whether modalities like ultrasound and MRI should be used to supplement conventional mammography.

      That was the good news. The bad news is that breast screening advocates mostly got shut out on a variety of other issues, with the USPSTF … 

      • Advising that breast screening be conducted biennially (every two years), rather than annually as most women’s imaging advocates would prefer
      • Declining to raise the recommended upper limit for screening from 74 to 79
      • Declining to recommend supplemental screening with MRI or ultrasound for women with dense breast tissue, even as women express frustration with the lack of reimbursement for these exams

      On the positive side, the USPSTF finally weighed in on DBT, stating that the 3D mammography technology is equivalent to digital mammography for breast screening. 

      • But in another disappointment, the group said it couldn’t find any studies stating that DBT was better than 2D digital mammography. 

      Given the fierce battles that have been fought over screening guidelines in the last 15 years, what made the USPSTF change its mind on mammography’s starting age? 

      • One big factor is the 2% annual rise in breast cancer incidence in women in their 40s from 2015 to 2019; the higher mortality rates among Black women was another issue (see story below in The Wire).

      The Takeaway

      The USPSTF’s move to lower its recommended starting age for screening mammography is a welcome – if overdue – change for women, who for 15 years have borne the brunt of the group’s conservative approach to guideline formation. The question remains, is the USPSTF making the same mistake all over again when it comes to supplemental imaging and annual screening? And how long will women have to wait this time until it sees the light?

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