Artificial Intelligence is getting better than humans at detecting breast cancer
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
My guest today for the Making Sense of Science podcast is Camila dos Santos, associate professor at Cold Spring Harbor Lab, who is a leading researcher of the inner lives of human mammary glands, more commonly known as breasts. These organs are unlike any other because throughout life they undergo numerous changes, first in puberty, then during pregnancies and lactation periods, and finally at the end of the cycle, when babies are weaned. A complex interplay of hormones governs these processes, in some cases increasing the risk of breast cancer and sometimes lowering it. Witnessing the molecular mechanics behind these processes in humans is not possible, so instead Dos Santos studies organoids—the clumps of breast cells donated by patients who undergo breast reduction surgeries or biopsies.
Show notes:
2:52 In response to hormones that arise during puberty, the breast cells grow and become more specialized, preparing the tissue for making milk.
7:53 How do breast cells know when to produce milk? It’s all governed by chemical messaging in the body. When the baby is born, the brain will release the hormone called oxytocin, which will make the breast cells contract and release the milk.
12:40 Breast resident immune cells are including T-cells and B-cells, but because they live inside the breast tissue their functions differ from the immune cells in other parts of the body,
17:00 With organoids—dimensional clumps of cells that are cultured in a dish—it is possible to visualize and study how these cells produce milk.
21:50 Women who are pregnant later in life are more likely to require medical intervention to breastfeed. Scientists are trying to understand the fundamental reasons why it happens.
26:10 Breast cancer has many risks factors. Generic mutations play a big role. All of us have the BRCA genes, but it is the alternation in the DNA sequence of the BRCA gene that can increase the predisposition to breast cancer. Aging and menopause are the risk factors for breast cancer, and so are pregnancies.
29:22 Women that are pregnant before the age of 20 to 25, have a decreased risk of breast cancer. And the hypothesis here is that during pregnancy breast cells more specialized, as specialized cells, they have a limited lifespan. It's more likely that they die before they turn into cancer.
33:08 Organoids are giving scientists an opportunity to practice personalized medicine. Scientists can test drugs on organoids taken from a patient to identify the most efficient treatment protocol.
Links:
Camila dos Santos’s Lab Page.
Editor's note: In addition to being a regular writer for Leaps.org, Lina Zeldovich is the guest host for today's episode of the Making Sense of Science podcast.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Podcast: The Friday Five Weekly Roundup in Health Research
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- Not a fan of breathing in micro plastics? New robot noses could help
- You don't need a near-death experience to get the benefits
- How to tell the difference between good and bad inflammation
- Brain shocks for better memory - don't try this at home (yet)!
- A new way to know if your bum back is getting better
The honorable mention for this week's Friday Five: One activity can increase your longevity even without good genes for living longer.