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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