A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
The Lancet Oncology
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.
A football player making a tackle during a game. (© Joe/Fotolia)
(© Joe/Fotolia)
What do football superstars Tom Brady, Drew Brees, Philip Rivers, and Adrian Peterson all have in common? Last year they wore helmets that provided the poorest protection against concussions in all the NFL.
"You're only as protected as well as the worst helmet that's out there."
A Dangerous Policy
Football helmets are rated on a one-star to five-star system based on how well they do the job of protecting the player. The league has allowed players to use their favorites, regardless of the star rating.
The Oxford-trained neuroscientist Ray Colello conducted a serious analysis of just how much the protection can vary between each level of star rating. Colello and his team of graduate students sifted through two seasons of game video to identify which players were wearing what helmets. There was "a really good correlation with position, but the correlation is much more significant based on age."
"The average player in the NFL is 26.6 years old, but the average age of a player wearing a one-star helmet is 34. And for anyone who knows football, that's ancient," the brain doc says. "Then for our two-star helmet, it's 32; and for a three-star helmet it's 29." Players were sticking with the helmets they were familiar with in college, despite the fact that equipment had improved considerably in recent years.
"You're only as protected as well as the worst helmet that's out there," Colello explains. Offering an auto analogy, he says, "It's like, if you run into the back of a Pinto, even if you are in a five-star Mercedes, that gas tank may still explode and you are still going to die."
It's one thing for a player to take a risk at scrambling his own brain; it's another matter to put a teammate or opponent at needless risk. Colello published his analysis early last year and the NFL moved quickly to ban the worst performing helmets, starting next season.
Some of the 14 players using the soon-to-be-banned helmets, like Drew Brees and Philip Rivers, made the switch to a five-star helmet at the start of training camp and stayed with it. Adrian Peterson wore a one-star helmet throughout the season.
Tom Brady tried but just couldn't get comfortable with a new bonnet and, after losing a few games, switched back to his old one in the middle of the season; he says he's going to ask the league to "grandfather in" his old helmet so he can continue to use it.
As for Colello, he's only just getting started. The brain doc has a much bigger vision for the future of football safety. He wants to prevent concussions from even occurring in the first place by creating an innovative new helmet that's unlike anything the league has ever seen.
Oxford-trained neuroscientist Ray Colello is on a mission to make football safer.
(Photo credit: VCU public affairs)
"A Force Field" of Protection
His inspiration was serendipitous; he was at home watching a football game on TV when Denver Bronco's receiver Wes Welker was hit, lay flat on the field with a concussion, and was carted off. As a commercial flickered on the screen, he ambled into the kitchen for another beer. "What those guys need is a force field protecting them," he thought to himself.
Like so many households, the refrigerator door was festooned with magnets holding his kids' school work in place. And in that eureka moment the idea popped into his head: "Maybe the repulsive force of magnets can put a break on an impact before it even occurs." Colello has spent the last few years trying to turn his concept into reality.
Newton's laws of physics – mass and speed – play out graphically in a concussion. The sudden stop of a helmet-to-helmet collision can shake the brain back and forth inside the skull like beans in a maraca. Dried beans stand up to the impact, making their distinctive musical sound; living brain tissue is much softer and not nearly so percussive. The resulting damage is a concussion.
The risk of that occurring is greater than you might think. Researchers using accelerometers inside helmets have determined that a typical college football player experiences about 600 helmet-to-helmet contacts during a season of practice and games. Each hit generates a split second peak g-force of 20 to 150 within the helmet and the odds of one causing a concussion increase sharply over 100 gs of force.
By comparison, astronauts typically experience a maximum sustained 3gs during lift off and most humans will black out around 9gs, which is why fighter pilots wear special pressure suits to counter the effects.
"It stretches the time line of impact quite dramatically. In fact in most instances, it doesn't even hit."
The NFL's fastest player, Chris Johnson, can run 19.3 mph. A collision at that speed "produces 120gs worth of force," Colello explains. "But if you can extend that time of impact by just 5 milliseconds (from 12 to 17msec) you'll shift that g-force down to 84. There is a very good chance that he won't suffer a concussion."
The neuroscientist dived into learning all he could about the physics magnets. It turns out that the most powerful commercially available magnet is an alloy made of neodymium, iron, and boron. The elements can be mixed and glued together in any shape and then an electric current is run through to make it magnetic; the direction of the current establishes the north-south poles.
A 1-pound neodymium magnet can repulse 600 times its own weight, even though the magnetic field extends less than an inch. That means it can push back a magnet inside another helmet but not affect the brain.
Crash Testing the Magnets
Colello couldn't wait to see if his idea panned out. With blessing from his wife to use their credit card, he purchased some neodymium magnets and jury-rigged experiments at home.
The reinforced plastics used in football helmets don't affect the magnetic field. And the small magnets stopped weights on gym equipment that were dropped from various heights. "It stretches the time line of impact quite dramatically. In fact in most instances, it doesn't even hit," says Colello. "We are dramatically shifting the curve" of impact.
Virginia Commonwealth University stepped in with a $50,000 innovation grant to support the next research steps. The professor ordered magnets custom-designed to fit the curvature of space inside the front and sides of existing football helmets. That makes it impossible to install them the wrong way, and ensures the magnets' poles will always repel and not attract. It adds about a pound and a half to the weight of the helmet.
a) The brain in a helmet. b) Placing the magnet. c) Measuring the impact of a helmet-to-helmet collision. d) How magnets reduce the force of impact.
(Courtesy Ray Colello)
Colello rented crash test dummy heads crammed with accelerometers and found that the magnets performed equally well at slowing collisions when fixed to a pendulum in a test that approximated a helmet and head hitting a similarly equipped helmet. It impressively reduced the force of contact.
The NFL was looking for outside-the-box thinking to prevent concussions. It was intrigued by Colello's approach and two years ago invited him to submit materials for review. To be fair to all entrants, the league proposed to subject all entries to the same standard crush test to see how well each performed in lessening impact. The only trouble was, Colello's approach was designed to avoid collisions, not lessen their impact. The test wouldn't have been a valid evaluation and he withdrew from consideration.
But Colello's work caught the attention of Stefan Duma, an engineering professor at Virginia Tech who developed the five-star rating system for football helmets.
"In theory it makes sense to use [the magnets] to slow down or reduce acceleration, that's logical," says Duma. He believes current helmet technology is nearing "the end of the physics barrier; you can only absorb so much energy in so much space," so the field is ripe for new approaches to improve helmet technology.
However, one of Duma's concerns is whether magnets "are feasible from a weight standpoint." Most helmets today weigh between two and four pounds, and a sufficiently powerful magnet might add too much weight. One possibility is using an electromagnet, which potentially could be lighter and more powerful, particularly if the power supply could be carried lower in the body, say in the shoulder pads.
Colello says his lab tests are promising enough that the concept needs to be tried out on the playing field. "We need to make enough helmets for two teams to play each other in a regulation-style game and measure the impact forces that are generated on each, and see if there is a significant reduction." He is waiting to hear from the National Institutes of Health on a grant proposal to take that next step toward dramatically reducing the risk of concussions in the NFL.
Just five milliseconds could do it.