Author: Brian Casey

Uneven Success Against Breast Cancer

Posted on by Brian Casey

The decline in breast cancer mortality has been one of public health’s major success stories. But when you look at it from a global perspective, it’s the best of times and the worst of times. 

That’s because success in fighting breast cancer has been uneven around the world. While countries in North America, Western Europe, and Oceania have seen dramatic declines in breast cancer mortality and advanced-stage disease, other regions continue to be plagued by what really is becoming a survivable disease for most women. 

A new study in JAMA Oncology points out these disparities, documenting major differences in rates of advanced breast disease between countries in what researchers said was the most comprehensive review to date of global differences in breast cancer stage at diagnosis. 

  • Researchers conducted a meta-analysis of 133 studies covering 2.4M women across 81 nations over the past two decades, documenting differences in rates of advanced breast disease at diagnosis both over time and between countries. 

While most high-income nations have seen declines in rates of distant metastatic disease over the past 20 years, advanced-stage disease remains stubbornly common in lower middle-income countries. Researchers found: 

  • Rates of distant metastatic disease varied across countries by region, with sub-Saharan Africa the highest and North America the lowest (6-31% vs. 0-6%)
  • Lower socioeconomic status was tied to more advanced disease when women in the most disadvantaged group were compared to least disadvantaged (3-11% vs. 2-8%)
  • There were pronounced disparities even in high-resource countries with established screening programs, as rates of metastatic disease were twice as high in women of low socioeconomic status (SES) compared to high SES women, such as in the US (8% vs. 4%) 
  • Older women had a much higher prevalence of advanced disease across different countries compared to younger women (range of 4-34% vs. 2-16%), a phenomenon that could be because most screening programs stop at age 75
  • 40% of countries did not meet the Global Breast Cancer Initiative goal of having 60% or more of patients diagnosed at stage I or II

The Takeaway

The new findings indicate that it’s too soon to take a victory lap in the battle against breast cancer. While progress at higher socioeconomic levels in high-income countries has been impressive, breast cancer remains a scourge among more disadvantaged women and across wide regions of the world.

Lung Screening’s Long-Term Benefits

Posted on by Brian Casey

CT lung cancer screening produced lung cancer-specific survival over 80% in the most recent data from the landmark I-ELCAP study, a remarkable testament to the effectiveness of screening. 

The findings were published this week in Radiology from I-ELCAP, one of the first large-scale CT lung screening trials, and are the latest in a series of studies pointing to lung screening’s benefits. The findings were originally presented at RSNA 2022. 

The I-ELCAP study is ongoing and has enrolled 89k participants at over 80 sites worldwide from 1992-2022 who have been exposed to tobacco smoke and who received annual low-dose CT (≤ 3mGy) scans. Periodic I-ELCAP follow-up studies have documented the survival rates of those whose cancers were detected with LDCT, and the new numbers offer a 20-year follow-up, finding: 

  • Primary lung cancers were detected on LDCT in 1,257 individuals who had lung cancer-specific survival of 81%, matching the 10-year survival rate of 81%
  • 1,017 patients with clinical stage I lung cancer underwent surgical resection and saw a lung cancer-specific survival rate of 87%
  • The I-ELCAP survival rate is much higher than another landmark screening study, NLST, in which it was 73% for stage I cancer at 10 years
  • Lung cancer-specific survival hit a plateau after 10 years of follow-up, at a cure rate of about 80%

I-ELCAP is unique for a variety of reasons, one of which is that it continues to screen people beyond a baseline scan and 2-3 annual follow-up rounds – perhaps the reason for its higher survival rate relative to NLST. 

  • It also has included people who were exposed to tobacco smoke but who weren’t necessarily smokers – an important distinction in the debate over how broad to expand lung screening criteria.  

The findings come as CT lung cancer screening is generating growing momentum. Studies this year from Germany, Taiwan, and Hungary have demonstrated screening’s value, and several countries are ramping up national population-based screening programs. 

The Takeaway

The 20-year I-ELCAP data show that CT lung cancer screening works if you can get people to do it. But achieving survival rates over 80% also requires work on the part of healthcare providers, in terms of defined protocols for working up findings, data management for screening programs, and patient outreach to ensure adherence to annual screening. Fortunately, I-ELCAP offers a model for how it’s done.

More Support for CT Lung Cancer Screening

Posted on by Brian Casey

Yet another study supporting CT lung cancer screening has been published, adding to a growing body of evidence that population-based CT screening programs will be effective in reducing lung cancer deaths. 

The new study comes from European Radiology, where researchers from Hungary describe findings from HUNCHEST-II, a population-based program that screened 4.2k high-risk people at 18 institutions. 

  • Screening criteria were largely similar to other studies: people between the ages of 50 and 75 who were current or former smokers with at least 25 pack-year histories. Former smokers had quit within the last 15 years. 

Recruitment for HUNCHEST-II took place from September 2019 to January 2022. Participants received a baseline low-dose CT (LDCT) scan, with the study protocol calling for annual follow-up scans (more on this later). Researchers found: 

  • The prevalence of baseline screening exams positive for lung cancer was 4.1%, comparable to the NELSON trial (2.3%) but much lower than the NLST (27%)
  • 1.8% of participants were diagnosed with lung cancer throughout screening rounds
  • 1.5% of participants had their cancer found with the baseline exam
  • Positive predictive value was 58%, at the high end of population-based lung screening programs
  • 79% of screen-detected cancers were early stage, making them well-suited for treatment
  • False-positive rate was 42%, a figure the authors said was “concerning”

Taking a deeper dive into the data produces interesting revelations. Overdiagnosis is a major concern with any screening test; it was a particular problem with NLST but was lower with HUNCHEST-II. 

  • Researchers said they used a volume-based nodule evaluation protocol, which reduced the false-positive rate compared to the nodule diameter-based approach in NLST.

Also, a high attrition rate occurred between the baseline scan and annual screening rounds, with only 12% of individuals with negative baseline LDCT results going on to follow-up screening (although the COVID-19 pandemic may have affected these results). 

The Takeaway

The HUNCHEST-II results add to the growing momentum in favor of national population-based CT lung screening programs. Germany is planning to implement a program in early 2024, and Taiwan is moving in the same direction. The question is, does the US need to step up its game as screening compliance rates remain low?

Unpacking the Biden Administration’s New AI Order

Posted on by Brian Casey

It seems like watershed moments in AI are happening on a weekly basis now. This time, the big news is the Biden Administration’s sweeping executive order that directs federal regulation of AI across multiple industries – including healthcare. 

The order comes as AI is becoming a clinical reality for many applications. 

  • The number of AI algorithms cleared by the FDA has been surging, and clinicians – particularly radiologists – are getting access to new tools on an almost daily basis.

But AI’s rapid growth – and in particular the rise of generative AI technologies like ChatGPT – have raised questions about its future impact on patient care and whether the FDA’s existing regulatory structure is suitable for such a new technology. 

The executive order appears to be an effort to get ahead of these trends. When it comes to healthcare, its major elements are summarized in a succinct analysis of the plan by Health Law Advisor. In short, the order: 

  • Calls on HHS to work with the VA and Department of Defense to create an HHS task force on AI within 90 days
  • Requires the task force to develop a strategic plan within a year that could include regulatory action regarding the deployment and use of AI for applications such as healthcare delivery, research, and drug and device safety
  • Orders HHS to develop a strategy within 180 days to determine if AI-enabled technologies in healthcare “maintain appropriate levels of quality” – basically, a review of the FDA’s authorization process
  • Requires HHS to set up an AI safety program within a year, in conjunction with patient safety organizations
  • Tells HHS to develop a strategy for regulating AI in drug development

Most analysts are viewing the executive order as the Biden Administration’s attempt to manage both risk and opportunity. 

  • The risk is that AI developers lose control of the technology, with consequences such as patients potentially harmed by inaccurate AI. The opportunity is for the US to become a leader in AI development by developing a long-term AI strategy. 

The Takeaway

The question is whether an industry that’s as fast-moving as AI – with headlines changing by the week – will lend itself to the sort of centralized long-term planning envisioned in the Biden Administration’s executive order. Time will tell.

Canada’s Breast Screening Push

Posted on by Brian Casey

As Canada examines revisions to its breast cancer screening guidelines, a new study adds support to the proposal of lowering its screening age to 40 – a move made in the US earlier this year. 

When to start breast screening has long been one of the most controversial aspects of mammography. 

  • In the US, a firestorm erupted in 2009 when the USPSTF withdrew its recommendation that women start in their 40s … a policy that wasn’t rescinded until May. 

In Canada, the Canadian Task Force on Preventive Health Care is reviewing its 2018 screening guidelines, which currently advise women to wait until 50 to start routine breast screening, and then be screened every 2-3 years after that. 

  • The Canadian task force’s 2018 guidelines also don’t mention dense breast tissue, a known risk factor for breast cancer (the FDA earlier this year said it would begin requiring breast density reporting). 

Canadian breast specialists have been pushing for the task force to lower the screening age, and their efforts got a boost with a new study that found starting breast screening at age 40 and continuing with it annually saved the greatest number of lives.

Researchers in MDPI used the OncoSim-Breast microsimulation model to simulate various screening regimens in a cohort of 1.5M Canadian women born in 1975. They assessed the earlier screening strategy by various metrics, including impact on breast cancer mortality, number needed to be screened to avert one breast cancer death, and stage at diagnosis, finding …

  • Annual screening starting at age 40 had the biggest mortality reduction compared to no screening, at 7.9 fewer deaths per 1,000 women, compared to biennial 40-74 (5.9) and biennial 50-74 (4.6) 
  • Annual screening from 40-74 had the lowest number of women who must be screened to avert one death (127) compared to biennial 40-74 (169) and biennial 50-74 (220)
  • Earlier annual screening would produce the greatest stage shift to more early invasive (stage 1 and stage 2a) cancers detected compared to other regimens 

The Takeaway

The Canadian task force is expected to complete its review by the end of the year – where it will land on the issue is anyone’s guess. It’s hoped that the new study – as well as other research on mammography’s effectiveness in Canada published in the last couple years – will spur the group to lower the screening age. But breast imaging experts we spoke with are skeptical given the task force’s preference for randomized clinical trials, which haven’t been performed in Canada on breast screening in decades.

Predicting the Future of Radiology AI

Posted on by Brian Casey

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.

FDA Data Show AI Approval Boom

Posted on by Brian Casey

In the previous issue of The Imaging Wire, we discovered how venture capital investment in AI developers is fueling rapid growth in new AI applications for radiologists (despite a slowdown this year). 

This trend was underscored late last week with new data from the FDA showing strong growth in the number of regulatory authorizations of AI and machine learning-enabled devices in calendar 2023 compared to the year before. The findings show:

  • A resurgence of AI/ML authorizations this year, with over 30% growth compared to 14% in 2022 and 15% in 2021 – The last time authorizations grew this fast was in 2020 (+39%)
  • The FDA authorized 171 AI/ML-enabled devices in the past year. Of the total, 155 had final decision dates between August 1, 2022 to July 30, 2023, while 16 were reclassifications from prior periods 
  • Devices intended for radiology made up 79% of the total (122/155), an impressive number but down slightly compared to 87% in 2022 
  • Other medical specialities include cardiology (9%), neurology (5%), and gastroenterology/urology (4%)

One interesting wrinkle in the report was the fact that despite all the buzz around large language models for generative AI, the FDA has yet to authorize a device that uses generative AI or that is powered by LLMs. 

The Takeaway

The FDA’s new report confirms that radiology AI shows no sign of slowing down, despite a drop in AI investment this year. 

The data also offer perspective on a JACR report last week predicting that by 2035 radiology could be seeing 350 new AI/ML product approvals for the year. Product approvals would only have to grow at about a 10% annual rate to hit that number – a figure that seems perfectly achievable given the new FDA report.

What’s Fueling AI’s Growth

Posted on by Brian Casey

It’s no secret that the rapid growth of AI in radiology is being fueled by venture capital firms eager to see a payoff for early investments in startup AI developers. But are there signs that VCs’ appetite for radiology AI is starting to wane?

Maybe. And maybe not. While one new analysis shows that AI investments slowed in 2023 compared to the year before, another predicts that over the long term, VC investing will spur a boom in AI development that is likely to transform radiology. 

First up is an update by Signify Research to its ongoing analysis of VC funding. The new numbers show that through Q3 2023, the number of medical imaging AI deals has fallen compared to Q3 2022 (24 vs. 40). 

  • Total funding has also fallen for the second straight year, to $501M year-to-date in 2023. That compares to $771M through the third quarter of 2022, and $1.1B through the corresponding quarter of 2021. 

On the other hand, the average deal size has grown to an all-time high of $20.9M, compared to 2022 ($15.4M) and 2021 ($18M). 

  • And one company – Rapid AI – joined the exclusive club of just 14 AI vendors that have raised over $100M with a $75M Series C round in July 2023. 

In a look forward at AI’s future, a new analysis in JACR by researchers from the ACR Data Science Institute (DSI) directly ties VC funding to healthcare AI software development, predicting that every $1B in funding translates into 11 new product approvals, with a six-year lag between funding and approval. 

  • And the authors forecast long-term growth: In 2022 there were 69 FDA-approved products, but by 2035, funding is expected to reach $31B for the year, resulting in the release of a staggering 350 new AI products that year.

Further, the ACR DSI authors see a virtuous cycle developing, as increasing AI adoption spurs more investment that creates more products available to help radiologists with their workloads. 

The Takeaway

The numbers from Signify and ACR DSI don’t match up exactly, but together they paint a picture of a market segment that continues to enjoy massive VC investment. While the precise numbers may fluctuate year to year, investor interest in medical imaging AI will fuel innovation that promises to transform how radiology is practiced in years to come.

PET’s Milestone Moment

Posted on by Brian Casey

In a milestone moment for PET, CMS has ended its policy of only paying for PET scans of dementia patients if they are enrolled in a clinical trial. The move paves the way for broader use of PET for conditions like Alzheimer’s disease as new diagnostic and therapeutic agents become available. 

CMS said it was rescinding its coverage with evidence development (CED) requirement for PET payments within Medicare and Medicaid. 

  • Advocates for PET have chafed at the policy since it was established in 2013, claiming that it restricted use of PET to detect buildup of amyloid and tau in the brain – widely considered to be precursors to Alzheimer’s disease. The policy limits PET payments to one scan per lifetime for patients enrolled in clinical trials. 

But the landscape began changing with the arrival of new Alzheimer’s treatments like Leqembi, approved in January 2023. CMS telegraphed its changing position in July, when it announced a review of the CED policy, and followed through with the change on October 13. The new policy…

  • Eliminates the requirement that patients be enrolled in clinical trials
  • Ends the limit of one PET scan per Alzheimer’s patient per lifetime
  • Allows Medicare Administrative Contractors (MACs) to make coverage decisions on Alzheimer’s PET
  • Rejects requests to have the policy applied retroactively, such as to when Leqembi was approved

CMS specifically cited the introduction of new anti-amyloid treatments as one of the reasons behind its change in policy. 

  • The lifetime limit is “outdated” and “not clinically appropriate” given the need for PET for both patient selection and to potentially discontinue treatment if it’s ineffective or if it’s worked to clear amyloid from the brain – a key need for such expensive therapies. 

The news was quickly applauded by groups like SNMMI and MITA, which have long advocated for looser reimbursement rules.

The Takeaway

The CMS decision is great news for the PET community as well as for patients facing a diagnosis of Alzheimer’s disease. The question remains as to what sort of reimbursement rates providers will see from the various MACs around the US, and whether commercial payers will follow suit.

Making Screening Better

Posted on by Brian Casey

While population-based cancer screening has demonstrated its value, there’s no question that screening could use improvement. Two new studies this week show how to improve on one of screening’s biggest challenges: getting patients to attend their follow-up exams.

In the first study in JACR, researchers from the University of Rochester wanted to see if notifying people about actionable findings shortly after screening exams had an impact on follow-up rates. Patients were notified within one to three weeks after the radiology report was completed. 

They also examined different methods for patient communication, including snail-mail letters, notifications from Epic’s MyChart electronic patient portal, and phone calls. In approximately 2.5k patients within one month of due date, they found that follow-up adherence rates varied for each outreach method as follows:

  • Phone calls – 60%
  • Letters – 57%
  • Controls – 53%
  • MyChart notifications – 36%

(The researchers noted that the COVID-19 pandemic may have disproportionately affected those in the MyChart group.) 

Fortunately, the university uses natural language processing-based software called Backstop to make sure no follow-up recommendations fall through the cracks. 

  • Backstop includes Nuance’s mPower technology to identify actionable findings from unstructured radiology reports; it triggers notifications to both primary care providers and patients about the need to complete follow-up.

Once the full round of Backstop notifications had taken place, compliance rates rose and there was no statistically significant difference between how patients got the early notification: letter (89%), phone (91%), MyChart (90%), and control (88%). 

In the second study, researchers in JAMA described how they used automated algorithms to analyze EHR data from 12k patients to identify those eligible for follow-up for cancer screening exams.

  • They then tested three levels of intervention to get people to their exams, ranging from EHR reminders to outreach to patient navigation to all three. 

Patients who got EHR reminders, outreach, and navigation or EHR reminders and outreach had the highest follow-up completion rates at 120 days compared to usual care (31% for both vs. 23%). Rates were similar to usual care for those who only got EHR reminders (23%).

The Takeaway

This week’s studies indicate that while health technology is great, it’s how you use it that matters. While IT tools can identify the people who need follow-up, it’s up to healthcare personnel to make sure patients get the care they need.

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