Why the FDA’s Density Rule Matters

The FDA’s new rules on reporting breast density to women getting mammograms went into effect on September 10. The implementation has been expected for some time, but this week’s rollout generated a wave of positive press coverage that highlights the importance both of breast density awareness and of breast screening.

The FDA in March 2023 said it would implement a national standard requiring providers to inform women of their breast density, which can obscure lesions on conventional X-ray mammography. 

  • Breast density is also a risk factor for cancer, and patient advocacy groups had been pressuring the FDA to set a standard to replace what has become a patchwork of state-by-state notification rules. 

The FDA’s rules have been incorporated into the Mammography Quality Standards Act, and require that … 

  • Mammography reports include a plain-language patient summary with “an overall assessment of breast density.” 
  • The summary must include specific language that defines breast density, explains its ramifications for detection and cancer risk, and suggests the need for additional imaging tests.

A novel aspect of the new rules is that they were mostly driven by patients – women like JoAnn Pushkin and the late Nancy Cappello who as patients discovered first-hand the shortcomings of X-ray-based mammography for women with dense breast tissue. 

What’s next? Density-awareness proponents are now turning their attention to reimbursement, which for supplemental imaging is inconsistent across the U.S.

  • A fix for the problem – the Find It Early Act – is working its way through Congress, and women’s health advocates lobbied on Capitol Hill this week to try to push the legislation through before the end of the current Congressional session. 

The new reporting landscape also creates opportunities for better software tools to detect and manage breast density and better predict risk in patients with dense breast tissue. 

  • Clinicians already realize that women with dense breasts not only need different screening modalities like MRI and ultrasound, but that they might also require more frequent screening due to their heightened cancer risk. 

The Takeaway

The FDA’s new breast density rules matter for a variety of reasons, from showing the power of patients to change their imaging experience to outlining a future in which risk plays a more prominent role in breast screening. While more work remains to be done, this is a good time to savor the triumph.

FDA Keeps Pace on AI Approvals

The FDA has updated its list of AI- and machine learning-enabled medical devices that have received regulatory authorization. The list is a closely watched barometer of the health of the AI sector, and the update shows the FDA is keeping a brisk pace of authorizations.

The FDA has maintained double-digit growth of AI authorizations for the last several years, a pace that reflects the growing number of submissions it’s getting from AI developers. 

  • Indeed, data compiled by regulatory expert Bradley Merrill Thompson show how the number of FDA authorizations has been growing rapidly since the dawn of the medical AI era in around 2016 (see also our article on AI safety below). 

The new FDA numbers show that …

  • The FDA has now authorized 950 AI/ML-enabled devices since it began keeping track
  • Device authorizations are up 15% for the first half of 2024 compared to the same period the year before (107 vs. 93)
  • The pace could grow even faster in late 2024 – in 2023, FDA in the second half authorized 126 devices, up 35% over the first half
  • At that pace, the FDA should hit just over 250 total authorizations in 2024 
  • This would represent 14% growth over 220 authorizations in 2023, and compares to growth of 14% in 2022 and 15% in 2021
  • As with past updates, radiology makes up the lion’s share of AI/ML authorizations, but had a 73% share in the first half, down from 80% for all of 2023
  • Siemens Healthineers led in all H1 2024 clearances with 11, bringing its total to 70 (66 for Siemens and four for Varian). GE HealthCare remains the leader with 80 total clearances after adding three in H1 2024 (GE’s total includes companies it has acquired, like Caption Health and MIM Software). There’s a big drop off after GE and Siemens, including Canon Medical (30), Aidoc (24), and Philips (24).

The FDA’s list includes both software-only algorithms as well as hardware devices like scanners that have built-in AI capabilities, such as a mobile X-ray unit that can alert users to emergent conditions. 

  • Indeed, many of the authorizations on the FDA’s list are for updated versions of already-cleared products rather than brand-new solutions – a trend that tends to inflate radiology’s share of approvals.

The Takeaway

The new FDA numbers on AI/ML regulatory authorizations are significant not only for revealing the growth in approvals, but also because the agency appears to be releasing the updates more frequently – perhaps a sign it is practicing what it preaches when it comes to AI openness and transparency. 

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.

      Unpacking the Biden Administration’s New AI Order

      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.

      FDA Data Show AI Approval Boom

      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.

      How Vendors Sell AI

      Better patient care is the main selling point used by AI vendors when marketing neuroimaging algorithms, followed closely by time savings. Farther down the list of benefits are lower costs and increased revenue for providers. 

      So says a new analysis in JACR that takes a close look at how FDA-cleared neuroimaging AI algorithms are marketed by vendors. It also includes several warning signs for both AI developers and clinicians.

      AI is the most exciting technology to arrive in healthcare in decades, but questions percolate on whether AI developers are overhyping the technology. In the new analysis, researchers focused on marketing claims made for 59 AI neuroimaging algorithms cleared by the FDA from 2008 to 2022. Researchers analyzed FDA summaries and vendor websites, finding:

      • For 69% of algorithms, vendors highlighted an improvement in quality of patient care, while time savings for clinicians were touted for 44%. Only 16% of algorithms were promoted as lowering costs, while just 11% were positioned as increasing revenue
      • 50% of cleared neuroimaging algorithms were related to detection or quantification of stroke; of these, 41% were for intracranial hemorrhage, 31% for stroke brain perfusion, and 24% for detection of large vessel occlusion 
      • 41% of the algorithms were intended for use with non-contrast CT scans, 36% with MRI, 15% with CT perfusion, 14% with CT angiography, and the rest with MR perfusion and PET
      • 90% of the algorithms studied were cleared in the last five years, and 42% since last year

      The researchers further noted two caveats in AI marketing: 

      • There is a lack of publicly available data to support vendor claims about the value of their algorithms. Better transparency is needed to create trust and clinician engagement.
      • The single-use-case nature of many AI algorithms raises questions about their economic viability. Many different algorithms would have to be implemented at a facility to ensure “a reasonable breadth of triage” for critical findings, and the financial burden of such integration is unclear.

      The Takeaway

      The new study offers intriguing insights into how AI algorithms are marketed by vendors, and how these efforts could be perceived by clinicians. The researchers note that financial pressure on AI developers may cause them to make “unintentional exaggerated claims” to recoup the cost of development; it is incumbent upon vendors to scrutinize their marketing activities to avoid overhyping AI technology.

      FDA Finally Moves on Breast Density

      After a long wait, the FDA issued a final rule that adds details on breast density reporting to the Mammography Quality Standards Act. The rule takes effect in September 2024 and should go a long way toward clarifying the issue of breast density for patients. 

      Breast tissue density is a risk factor for cancer, and dense breast tissue can make it more difficult for radiologists to identify tumors on conventional x-ray mammography. This shortcoming is often not communicated to women who receive “normal” mammograms, but later find out that a cancer was missed.

      Prodded by a strong patient advocacy movement, individual states have been passing laws requiring women to be notified of their density status, creating a patchwork of regulation across the U.S. 

      The FDA in 2018 agreed to set a national standard by rolling breast density reporting into an update of the MQSA. But the long wait has frustrated many in the breast density advocacy movement.

      There are several major components to the new rule, which: 

      • Requires breast imaging facilities to provide patients with a summary of the mammography report written in lay terms that identifies whether patients have dense or non-dense breast tissue.
      • Instructs facilities to include a section in the mammography report explaining the significance of breast density. 
      • Establishes four categories for reporting breast tissue density in the mammography report. 
      • Sets the specific language to be used for reporting density. 

      The new rules provide much-needed national consistency in breast density reporting, and will replace the patchwork of state regulation that has developed over the years. Developers of breast density software may also benefit from the new federal rules, as they simplify the number of regulations that need to be tracked. 

      The Takeaway

      Better late than never. While the FDA should have signed off on this years ago, now that the rules are issued the breast imaging community can move ahead with integrating them into clinical practice. The new rules should also help density reporting software developers by setting a national standard rather than a patchwork of state regulation. 

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