Is AI ready for widespread use in mammography screening? That question was the focus of a point-counterpoint debate in AJR that discussed the pros and cons of broad-based clinical AI deployment for one of radiology’s most high-profile exams.
Mammography screening is perhaps the clinical use case with the most potential to help radiologists drowning under a rising tide of imaging exams.
- Several large-scale research studies have been published recently – mostly in Europe – showing that, for most normal mammograms, AI could reduce the need for a second reader, as is common in European screening programs.
Indeed, mammography AI developer Lunit last week announced a contract with a Swedish health system that would do just that, having AI act as an autonomous second reader.
- While the U.S. doesn’t typically use second readers for breast screening, AI could still play an important role in assisting radiologists in interpreting mammograms, predicting patient risk, and acting as a sort of clinical spell-check to reduce misses.
So does that mean mammography AI is ready for prime time? Taking the skeptical view were Duke University breast radiologists Eun Langman, MD, and Vilert Loving, MD, who believe caution is warranted, for the following reasons…
- Most of AI’s reported diagnostic performance gains have been with 2D digital mammography, and may not apply to DBT mammography, which has become the standard in the U.S.
- While autonomous AI interpretation of mammograms has been touted, there are practical barriers to its widespread application, such as the legal implications of AI misses.
- There is no evidence showing AI reduces breast cancer mortality, and there are many other interventions that could do so at a lower cost.
Taking the other side of the argument was MGH breast radiologist Manisha Bahl, MD, who noted that…
- Evidence supporting mammography AI’s effectiveness has come not only from randomized controlled trials like MASAI, but also from studies of routine population-based screening like the PRAIM study in Germany.
- Studies of mammography AI in the U.S. – where DBT is routinely used – have shown cancer detection gains comparable to those in Europe.
- In addition to diagnostic support, AI can speed radiologist workflow, such as through autonomous AI reporting of some mammograms.
The Takeaway
In the debate over mammography AI deployment, both sides present persuasive arguments. But as is the case with AI applications outside healthcare, the technological imperative to leverage this powerful new technology is likely to swamp any attempts to put up guardrails restricting its use.
