Bloomberg reporter Tanaz Meghjani writes that MIT researchers created a new system to 3D print a customized replica of the human heart, which could help improve replacement valve procedures. The new system “mimics blood flow and pressure in individual diseased hearts, suggesting a way to predict the effects of various replacements and select the best fit, avoiding potential leakage and failure,” Meghjani writes.
MIT engineers have developed a new technique for 3D printing a soft, flexible, custom-designed replica of a patient’s heart, report Gabrielle Emanuel and Amy Sokolow for WBUR. The goal of the research is to “provide realistic models so that doctors, researchers and medical device manufacturers can use them in testing therapies for different types of heart disease,” Emanuel and Sokolow explain.
Aera Therapeutics, founded by Prof. Feng Zhang, is working to “debut a type of protein nanoparticle that it believes can be used to ferry all sorts of genetic medicines around the body,” reports Lisa Jarvis for Bloomberg.
Writing for Fortune, Prof. Elazer R. Edelman and Mike Mussallem of Edwards Lifesciences write that the backlog of deferred medical treatments caused by the Covid-19 pandemic and resulting long-term health consequences could impact public health for years. Edelman and Mussallem emphasize that “it is incumbent upon us to identify timely real-world evidence to elucidate the effects of policy changes so they can be adaptive and agile enough to provide access to critical interventions and procedures.”
Researchers at MIT and elsewhere are analyzing patients’ speech patterns to see if they can detect Lou Gehrig’s disease in its early stages, reports Ben Leonard, Ruth Reader, Carmen Paun and Erin Schumaker for Politico. “Catching it early and beginning treatment can improve patients’ quality of life and delay symptom onset,” they write.
Prof. Feng Zhang founded Aera Therapeutics, a startup working to deliver curative genetic medicine to hard-to-reach parts of the body, reports Ryan Cross for The Boston Globe. “If Aera’s approach works in people, it could broaden the reach of genetic therapies, which currently have limited clinical applications – partly because there aren’t enough methods for getting those medicines to hone in on the right cells,” writes Cross.
An ingestible, pill-shaped sensor module, which can pinpoint its location as it moves through the body, has been developed by researchers at MIT and Caltech, reports Andrew Paul for Popular Science. This method “could one day offer an effective means to assess issues like constipation, gastroesophageal reflux disease, and gastroparesis,” writes Paul.
A new smart pill the size of a quarter, developed by a team of researchers from MIT, Caltech and NYU, could one day help doctors more easily identify issues in a patient’s digestive tract. “Such a device could offer an alternative to more invasive procedures in humans, such as endoscopy, that are currently used to diagnose motility disorders,” writes Nina Massey for The Independent.
Prof. Gio Traverso and his colleagues at Caltech and NYU have developed a smart ingestible sensor that may offer a less invasive way to diagnose gastrointestinal disorders. “The hope is the device will allow doctors, armed with the exact location of a GI tract disruption, to better target care — and give patients a diagnostic option they can use at home,” reports Lizzy Lawler for STAT.
Researchers from MIT and Caltech have developed a pill-shaped ingestible sensor that can be monitored as it moves through the GI tract, allowing doctors to more easily diagnose gastrointestinal disorders, reports Brian Heater for TechCrunch. “The ability to characterize motility without the need for radiation, or more invasive placement of devices, I think will lower the barrier for people to be evaluated,” says Prof. Giovanni Traverso.
Researchers at MIT and Massachusetts General Hospital have developed “Sybil” – an artificial intelligence tool that can predict the risk of a patient developing lung cancer within six years, reports Mallika Marshall for CBS Boston.
MIT researchers have developed a new AI tool called Sybil that could help predict whether a patient will get lung cancer up to six years in advance, reports Pranshu Verma for The Washington Post. “Much of the technology involves analyzing large troves of medical scans, data sets or images, then feeding them into complex artificial intelligence software,” Verma explains. “From there, computers are trained to spot images of tumors or other abnormalities.”
National Geographic reporter Maya Wei-Haas explores how the ancient art of origami is being applied to fields such a robotics, medicine and space exploration. Wei-Haas notes that Prof. Daniela Rus and her team developed a robot that can fold to fit inside a pill capsule, while Prof. Erik Demaine has designed complex, curving fold patterns. “You get these really impressive 3D forms with very simple creasing,” says Demaine.
A review led Prof. Marzyeh Ghassemi has found that a major issue in health-related machine learning models “is the relative scarcity of publicly available data sets in medicine,” reports Emily Sohn for Nature.
A study by Prof. Amy Finkelstein finds that physicians and their families are less likely to comply with medication guidelines, reports Dennis Thompson for HealthDay. The researchers found that “people tend to adhere to medication guidelines about 54% of the time, while doctors and their families lag about 4 percentage points behind that.”