Headlines around the world the past several months declared that artificial
intelligence (AI) is better at detecting breast cancer than human radiologists.
Can artificial intelligence really read my own
mammogram better than me? That would be intriguing, if it were true.
In fact, there are no studies to date proving that AI technology reads
mammograms more accurately than radiologists in the real-world setting,
but what the groundbreaking study in the journal
Nature did show was that AI could detect breast cancer more accurately than radiologists
in a selected set of mammograms, particularly when those sets of mammograms
are enriched with lots of breast cancer cases.
THE PROMISE OF AI
Although there is much more research to be done, it grows clearer by the
day that AI has great promise in improving breast cancer care. But as
we venture out into the expanse of AI technology, it is critical we proceed
with caution. Recall the headlines from March 2018 of the Uber fully autonomous
car that killed a woman crossing the street in Tempe, Ariz. The car’s
AI-based software was unable to identify her as a person crossing the
street and struck her at around 40 MPH, according to the Associated Press.
Then there was the meme that went viral on social media in 2016 depicting
rows and columns of photos of Chihuahuas and blueberry muffins, which
so cleverly illustrated the limitations of AI algorithms in correctly
identifying some of those images so unmistakably identifiable by any human.
Along those same lines, the recent article in
Nature also found in its reader study that although AI was able to identify some
cancers missed by the study radiologists, at least one cancer that was
identified by all six radiologists was missed by the AI system.
So, where do we go from here? AI is good. Radiologists are good. But AI
and radiologists are better together. I am seeing that potential firsthand
as a principle investigator in an unpublished study Hoag is conducting
in collaboration with Therapixel, a company that is not related to the
Nature study, specializing in AI for medical imaging. The results of the study
fully support this concept of augmented intelligence whereby the best
results are obtained when radiologists harness the power of AI to optimize
the accuracy and performance of mammographic screening for breast cancer.
AI’S FUTURE IN MAMMOGRAPHY
Do I believe AI will become better at reading mammograms than me? I don’t
know, but I sure hope so. Do I believe AI will make me obsolete? Not in
my lifetime. Even if AI reaches its full potential, there are some cancers
(i.e. “invisible cancers”) that it will miss simply due to
the nature of mammography and other imaging techniques. Diagnosing breast
cancer isn’t easy, and it certainly isn’t as simple as interpreting
a mammogram. AI can’t lay hands on a person’s body or conduct
a meaningful clinical interview that could reveal changes in skin, palpable
lumps or discharge that turn out to be indicators of cancer. AI can’t
perform breast biopsies or aspirations, and it cannot engage in a complex
discussion about a woman’s individual values. Most importantly,
AI cannot provide women with compassion and empathy.
I have heard AI described in medicine as analogous to the autopilot function
on planes. While autopilot could potentially fly and land a plane on its
own, would anyone be willing to board a plane without a human pilot? The
same is true for patient care. AI will best be utilized in concert with
radiologists who can shape the way it is used, develop standards and identify
the technology’s limitations.
Instead of framing the story as “robot versus radiologist,”
I believe patients are better served by discussing the powerful potential
of putting AI and radiologists together. “AI has the potential to
help radiologists improve the efficiency and effectiveness of breast cancer
imaging” is not a scintillating headline. But it is a thrilling
concept, and it’s one that I am excited to explore.
January Lopez, M.D., is a fellowship trained breast imaging specialist, board-certified diagnostic
radiologist and Director of Breast Imaging at
Hoag Breast Centers.