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Ultrasounds give women crucial information during pregnancy \u2014 they allow expecting parents to hear a heartbeat, count fingers and toes, check how many babies there are, see how they\u2019re positioned, and so much more. But not every pregnancy gets this level of care. About two-thirds of people across the globe lack ready access to diagnostic imaging services, like ultrasounds and X-rays. And there aren\u2019t enough sonographers to perform ultrasounds for everyone who needs them. So what do you do if you can\u2019t get an ultrasound where you live?<\/p>\n
Google researchers explored an AI tool for this problem through a research study with Northwestern and Jacarand Health. The research involved training healthcare workers to perform simple \u201cblind sweep\u201d ultrasounds and used machine learning models to interpret the results. With this approach, they were able to detect important prenatal information, like gestational age and fetal presentation, as accurately as a trained sonographer, giving women in under-resourced areas better information about what to expect ahead of one of the most significant events of their lives.<\/p>\n
We sat down with Googlers Angelica Willis and Dr. Nichole Young-Lin to learn more about this research \u2014 and what it could mean for the potential future of ultrasound access worldwide.<\/p>\n
What do you do at Google?<\/b><\/p>\n
Angelica:<\/b> I\u2019m a software engineer and AI researcher. I\u2019ve always been passionate about using AI for social good and healthcare equity. When we look at maternal care, technical advancements are only as valuable as the lives they impact. My motivation is building technology that actually reaches the people who need it most. And right now, my focus is making healthcare more accessible worldwide.<\/p>\n
Nichole:<\/b> I\u2019m the in-house obstetrician-gynecologist (OB\/GYN) at Google. I actually got my start in public health researching postpartum hemorrhage to reduce maternal mortality. That inspired me to become a doctor, but I soon realized that to address global inequities in medical access, we need the scale that technology can offer. I now work on a range of women\u2019s health and consumer health projects at Google,a week while continuing to care for patients.<\/p>\n
Why are ultrasounds so important?<\/b><\/p>\n
Nichole:<\/b> As an OB\/GYN, we turn to ultrasounds for all sorts of questions. Is the baby growing appropriately? Are there anomalies? And we rely on early ultrasounds, in particular, to estimate gestational age: How far along is the pregnancy, and when is the baby due? Screenings, treatment, management, and being able to prepare for a safe delivery \u2014 that all depends on a timeline determined by gestational age.<\/p>\n
Many people have irregular periods or don\u2019t track their periods, so we can\u2019t always rely on period history to estimate gestational age. And there can be serious ramifications for getting it wrong. Let\u2019s say someone needs to deliver early because of a complication. You think you\u2019re delivering a 37-week baby, but maybe you\u2019re actually delivering a 34-week baby with less mature lungs. Those babies need very different levels of care when they\u2019re born. When we\u2019re able to accurately define the baby\u2019s gestational age, we\u2019re much better prepared to provide both the baby and the mother with the support they need after birth.<\/p>\n
What\u2019s keeping people from getting ultrasounds during pregnancy?<\/b><\/p>\n
Nichole:<\/b> Traditional ultrasound machines are bulky and expensive, creating a barrier to access. When they break in remote clinics, there\u2019s often no one to fix them, and they require stable electricity when they do work. With recent developments in handheld ultrasound devices, we\u2019ve seen greater potential for us to get ultrasounds to more women, especially in low-resource settings. The handheld machines are smaller and cheaper, and many are battery-powered, so they\u2019re portable and easily accessible<\/p>\n
Angelica:<\/b> But even with advancements in portable device technology, it still takes two years of intense hands-on training to become a sonographer, resulting in a global shortage of sonographers who can perform prenatal ultrasounds.<\/p>\n
Tell me about your research. What are you doing differently to solve those problems?<\/b><\/p>\n
Angelica:<\/b> We partnered with Jacaranda Health and Northwestern Medicine in our study of 1,000 mothers in Nairobi, Kenya, and 1,000 more in Chicago. We found our machine learning model could detect gestational age and fetal presentation as accurately as a trained sonographer.<\/p>\n
In a traditional ultrasound, the sonographer has to move the probe around precisely to get specific measurements. And it\u2019s really hard to get right. Our research involved a \u201cblind sweep\u201d ultrasound instead. Operators sweep the probe over the abdomen in a predefined pattern. And healthcare workers who\u2019ve never performed an ultrasound before can learn how to do it in eight hours.<\/p>\n
These blind sweep operators gather videos that help us get the imaging we need of the baby, and we built an AI model to analyze those videos. It can tell the operator if they need to redo the sweep. And it can estimate gestational age and indicate fetal presentation \u2014 what position the baby\u2019s in. Crucially, all of that processing happens on the device, so it doesn\u2019t require an electricity supply or even Wi-Fi to be able to provide the operator and the mother with the insights they need to prepare for birth.<\/p>\n
What could this mean for maternal healthcare worldwide?<\/b><\/p>\n
Angelica:<\/b> We saw this project as an opportunity to demonstrate what\u2019s possible in maternal healthcare. The research proves we can broaden access to expert-level care and put it directly into the hands of frontline community health workers.<\/p>\n
Nichole:<\/b> The goal of our research is to show how expanded access to life-saving ultrasound care could impact communities, and we\u2019re getting there one step at a time. Through this research, we\u2019ve made huge strides toward showing that this is a viable application of AI in maternal healthcare because we can use it across different patient populations and healthcare settings. But why stop at gestational age and fetal presentation \u2014 or even maternal healthcare? Ultrasound can be used for so many things, like seeing how much someone is bleeding after an accident or an injury. There\u2019s so much potential for AI to help improve maternal health and healthcare across the board.<\/p>\n<\/div>\n