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.
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 is the promising research covered in this week's Friday Five:
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- How to make cities of the future less noisy
- An old diabetes drug could have a new purpose: treating an irregular heartbeat
- A new reason for mysterious stillbirths
- Making old mice younger with EVs
- No pain - or mucus - no gain
And an honorable mention this week: How treatments for depression can change the structure of the brain
Obesity is a risk factor for worse outcomes for a variety of medical conditions ranging from cancer to Covid-19. Most experts attribute it simply to underlying low-grade inflammation and added weight that make breathing more difficult.
Now researchers have found a more direct reason: SARS-CoV-2, the virus that causes Covid-19, can infect adipocytes, more commonly known as fat cells, and macrophages, immune cells that are part of the broader matrix of cells that support fat tissue. Stanford University researchers Catherine Blish and Tracey McLaughlin are senior authors of the study.
Most of us think of fat as the spare tire that can accumulate around the middle as we age, but fat also is present closer to most internal organs. McLaughlin's research has focused on epicardial fat, “which sits right on top of the heart with no physical barrier at all,” she says. So if that fat got infected and inflamed, it might directly affect the heart.” That could help explain cardiovascular problems associated with Covid-19 infections.
Looking at tissue taken from autopsy, there was evidence of SARS-CoV-2 virus inside the fat cells as well as surrounding inflammation. In fat cells and immune cells harvested from health humans, infection in the laboratory drove "an inflammatory response, particularly in the macrophages…They secreted proteins that are typically seen in a cytokine storm” where the immune response runs amok with potential life-threatening consequences. This suggests to McLaughlin “that there could be a regional and even a systemic inflammatory response following infection in fat.”
It is easy to see how the airborne SARS-CoV-2 virus infects the nose and lungs, but how does it get into fat tissue? That is a mystery and the source of ample speculation.
The macrophages studied by McLaughlin and Blish were spewing out inflammatory proteins, While the the virus within them was replicating, the new viral particles were not able to replicate within those cells. It was a different story in the fat cells. “When [the virus] gets into the fat cells, it not only replicates, it's a productive infection, which means the resulting viral particles can infect another cell,” including microphages, McLaughlin explains. It seems to be a symbiotic tango of the virus between the two cell types that keeps the cycle going.
It is easy to see how the airborne SARS-CoV-2 virus infects the nose and lungs, but how does it get into fat tissue? That is a mystery and the source of ample speculation.
Macrophages are mobile; they engulf and carry invading pathogens to lymphoid tissue in the lymph nodes, tonsils and elsewhere in the body to alert T cells of the immune system to the pathogen. Perhaps some of them also carry the virus through the bloodstream to more distant tissue.
ACE2 receptors are the means by which SARS-CoV-2 latches on to and enters most cells. They are not thought to be common on fat cells, so initially most researchers thought it unlikely they would become infected.
However, while some cell receptors always sit on the surface of the cell, other receptors are expressed on the surface only under certain conditions. Philipp Scherer, a professor of internal medicine and director of the Touchstone Diabetes Center at the University of Texas Southwestern Medical Center, suggests that, in people who have obesity, “There might be higher levels of dysfunctional [fat cells] that facilitate entry of the virus,” either through transiently expressed ACE2 or other receptors. Inflammatory proteins generated by macrophages might contribute to this process.
Another hypothesis is that viral RNA might be smuggled into fat cells as cargo in small bits of material called extracellular vesicles, or EVs, that can travel between cells. Other researchers have shown that when EVs express ACE2 receptors, they can act as decoys for SARS-CoV-2, where the virus binds to them rather than a cell. These scientists are working to create drugs that mimic this decoy effect as an approach to therapy.
Do fat cells play a role in Long Covid? “Fat cells are a great place to hide. You have all the energy you need and fat cells turn over very slowly; they have a half-life of ten years,” says Scherer. Observational studies suggest that acute Covid-19 can trigger the onset of diabetes especially in people who are overweight, and that patients taking medicines to regulate their diabetes “were actually quite protective” against acute Covid-19. Scherer has funding to study the risks and benefits of those drugs in animal models of Long Covid.
McLaughlin says there are two areas of potential concern with fat tissue and Long Covid. One is that this tissue might serve as a “big reservoir where the virus continues to replicate and is sent out” to other parts of the body. The second is that inflammation due to infected fat cells and macrophages can result in fibrosis or scar tissue forming around organs, inhibiting their function. Once scar tissue forms, the tissue damage becomes more difficult to repair.
Current Covid-19 treatments work by stopping the virus from entering cells through the ACE2 receptor, so they likely would have no effect on virus that uses a different mechanism. That means another approach will have to be developed to complement the treatments we already have. So the best advice McLaughlin can offer today is to keep current on vaccinations and boosters and lose weight to reduce the risk associated with obesity.