Science Friday - How a particle accelerator illuminated 56 human organs

Episode Date: April 17, 2026

A new imaging technique using a particle accelerator is giving researchers an unprecedented level of detail of our organs, producing scans 100 billion times brighter than a CT scanner. Those 3D models... are now part of a public database called the Human Organ Atlas, available to researchers and the medically curious. Joining Host Ira Flatow to explain why they needed so much power and what kind of research advances will follow is imaging scientist Claire Walsh, director of the Human Organ Atlas hub. Check out images from the Human Organ Atlas on our website. Guest:  Dr. Claire Walsh is an associate professor at the UCL department of mechanical engineering and director of the Human Organ Atlas Hub. Transcripts for each episode are available within 1-3 days at sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

Transcript
Discussion (0)
Starting point is 00:00:03 Hey, it's Ira, and you're listening to Science Friday. When I was a kid, my dad gave me a copy of Gray's Anatomy, you know, that five-inch-thick, classic anatomy textbook. And I became fascinated with the human body. I loved going over the hyper-detailed illustrations of our muscles and our organs, and ever since then, I've been a fan of unique anatomy books. Well, my next guest is leading a project that brings Gray's Anatomy into the digital age. It's called the Human Organ Atlas. It's a new public database of organs that are scanned
Starting point is 00:00:40 with the help of an actual particle accelerator. Yeah, giving visitors an up close and personal look at 56 human organs. Here to explain why they needed so much power and what kind of research advances will follow is Dr. Claire Walsh, Associate Professor at University College London, and director of the Human Organ Atlas Hub. She researches 3D imaging techniques for human organs. Welcome to Science Friday. Hi, Ira. Thank you very much for having me here. It's a pleasure. You're welcome. I've got to say these organ images, they're just stunning.
Starting point is 00:01:16 You can see tiny individual ridges on the eyeball, all the tiny little pockmarks in the lungs. What was it like for you seeing these for the first time? Yeah, I think, I mean, you know, as an imaging scientist images is what I love. to work with and to deal with. And I think going all the way back to 2021, when we first started to get these images through, it was really a wow moment. You know, the first time we saw the images of the lung,
Starting point is 00:01:42 which was what we started with, coming off the particle accelerator that we use, because this was all during the COVID pandemic, opening them up during screen shares with all the collaborators on the projects there, and everyone just sort of taking a minute, taking it in and being like, wow, what are we even looking at? This is amazing.
Starting point is 00:02:00 Anyone can explore it. We've got explore and search functions, and you can click through the different organs. You can look at the pictures. And most importantly, you can explore the actual real data sets yourself online there. We use a viewing portal on the website, very similar to what powers Google, satellite, Google Earth. So you can basically open the data sets up in the little window there, and you can look through them and you can zoom into different places and it pulls into higher resolution. And you can explore like the 3D space of an organ. which is very cool.
Starting point is 00:02:31 So it's Google Earth for your organ. Exactly, yeah. So this started during COVID. This wasn't a project say, hey, we're all sitting around. Let's do something different. I mean, so at the very back inception of this project was during the COVID pandemic in 2021. And it was actually started because some medical collaborators of ours
Starting point is 00:02:50 from the Hanover Medical Center were looking for ways to better understand the lungs of the COVID-19 patients that they were seeing. It was in the thick of the pandemic. And they got in contact. with Professor Peter Lee, who's here at UCL, and he was like, I know the person we need to call. He called Paul Tafferow, who is at the particle accelerator in Europe. And together we kind of all push the technology together
Starting point is 00:03:14 to answer these questions of what's COVID-19 doing to the lungs of these people. But very soon after that, we realized, hey, this technique will be amazing, not just for lungs, but for all the other organs of the human body as well. Now, you're borrowing a big, basically, atom smasher that physicists used to look for subatomic particles, right? I mean, how do they feel about you taking over their machine? Well, so we're similar kind of ideas. So some of the really big particle accelerators like the CERN, the Large Hadron Collider in CERN, which a lot of people will have heard about.
Starting point is 00:03:47 It's actually kind of just up the road from the particle accelerator we use, Geneva and Grenoble. And the synchrotrons, they're slightly different to something like the Large Hadron Collider. Trotron Collider is accelerating these particles and smashing them together. With the synchrotron, you're accelerating these electrons around and you're not smashing any of them together. You're just bending them and you're using the radiation that comes off. So the synchrotron, they do a lot of different things, but imaging is a big part of what many of these synchrotons do. They're not just imaging human biomedical features, it should be said. They have a huge range of things that they do. Crystallography is a big part of what some synchrotrons do. They're also
Starting point is 00:04:27 using the similar technique, but they're imaging things like car parts and aeroplane parts and batteries and lots of incredibly exciting research. And now hearts and kidneys and things like that. Exactly, yes. Oh, you raise so many questions I need to ask. First of all, whose organs are these? Yes, I think it's really important for everyone to understand and to see these are all organs that were imaging of people who have died and donated their bodies to science.
Starting point is 00:04:55 None of this imaging is done in live human beings. The x-ray dose would be far too great. Why can't you just do, let's say, a CT skin? This sounds like hitting it with a hammer. Tell me about that. Yeah, so the imaging technique, it's called hip CT, hierarchical, phase contrast, tomography. It doesn't have anything to do with hip joints. That's just the acronym.
Starting point is 00:05:18 But essentially, you can kind of think of like a supercharged CT in a way, right? the kind of underlying principles are the same. You take an organ and you take an x-ray beam and you shine that x-ray beam through the organs and you rotate them around slowly and you're taking images at all these different rotation angles, which is the same way that a hospital CT scanner works, but there's a few really critical differences. One is the types of x-rays that we're using. So we go all the way to a particle accelerator in Grenoble, France,
Starting point is 00:05:50 called the European Synchrotron Radiation Facility. And what this particle accelerator does is accelerates electrons around a ring that's about 800 meters in circumference, and it accelerates them up to near the speed of light. Now, when you accelerate electrons that fast and you bend them around like a ring, around a circle, they emit radiation as they bend. It's called synchrotron radiation, it's wavelengths of x-rays, and it's that that we're using to image the samples. And this x-ray is different to the x-ray that.
Starting point is 00:06:20 you kind of get in hospitals because it's much, much more, it's called brilliant. It's a more brilliant source, which basically means it's much more intensely focused and much brighter than the x-rays that you would get in a hospital CT scanner. So when you have these way, way more brilliant and higher energy and higher power kind of x-rays, you can do some interesting things that you couldn't do with a hospital. The first thing is that if you go into a normal hospital CC scan or an x-ray scan, you're shining x-rays through the tissue and the image that they get on the other side is because some of the tissues in your body absorb x-rays more than other. So like bone absorbs a lot of x-rays.
Starting point is 00:06:58 So if you're in an x-ray and there's bone in there, the x-rays will be absorbed by the bone, but they'll pass through the softer tissue more. And so that's why the bones appear kind of bright and the softer tissue appears. And it's the same thing with a normal CT. The difference that we have here is that as will the x-rays pass through the tissue, we're not as interested in how much the signal is absorbed, that that is a factor, but we're actually interested in something else that happens to x-rays. So as x-rays pass through tissue, x-rays are waves, if you imagine, and these waves are shifted as they pass through tissues with different densities. The waves are like shifted relative to one another.
Starting point is 00:07:35 And when these waves get shifted relative to one another, you get like a, what's called an interference pattern. And it's this interference pattern that we can measure. and it basically gives us the ability to look at really small differences in density between the tissue. So those are the primary differences that you get. You couldn't do this in a hospital CT scanner. Yeah, you're getting a lot more detail, right? Exactly.
Starting point is 00:07:59 And we're at much, much higher resolution. So a normal hospital CT scanner, you're kind of one millimeter size for each of the little cubes that make up the image. So the resolution, you can say it's like one millimeter. With the hip CT technique, we go down to one micrometer. Wow. So you're like a hundredth the hair, a hundredth the diameter of a human hair. That's got to be a big file size for that data. Really, really big data sets.
Starting point is 00:08:24 So our data sets are kind of terabytes in size for a lot of the data. And that's a big part of the human organ atlas that we've created is how do you make data that size available to anybody around the world and not just like available, but how can you allow them to like interact with it in a way that's interesting and meaningful like scientifically and educationally. And tell me why this is so useful for researchers to have super detailed scans of organs. Yeah, so there's a whole bunch of ways
Starting point is 00:08:55 that kind of these scans are really useful for researchers. And some of it is in terms of kind of just medical education and understanding anatomy. So that's one idea, anatomy researchers who are trying to understand, okay, where does this anatomical detail fit? We're seeing for the first time here in like undistorted three-dimensional,
Starting point is 00:09:13 dimensions what anatomical features look like. If you, to do physical anatomy dissection, some structures you won't be able to see because they're too small. And also you have to cut an organ up to get to the internal structure. And sometimes if you've made a cut in one direction, like you can't see a structure. Maybe you've cut through it or you've cut at an angle that doesn't allow you to see that structure. Right.
Starting point is 00:09:36 With this kind of virtual digital version of the organ, you can cut in any direction you want and you can see very small structures. So that's one thing. Another big area that we look at and we work at is we do AI-assisted segmentation of structures. So one that we've worked on a lot is the blood vessels. So looking at the blood vessel network in the human kidney, for example. And with these data sets, you know, we have a load of human kidneys within the human organ atlas and you can extract the blood vessel network across all these kidneys.
Starting point is 00:10:08 And you can say, hey, how does the blood vessel network change between you. male and female kidneys, or how does it change in the younger versus the older kidneys, or how is it changed by donors where they have conditions like diabetes in them, we can look at these kind of differences and understand how does that change structure? Say more in this, because I want to know perhaps what are some other ways that AI, machine learning, could come into this. Yeah, so I think there's tons of errors that are really interesting that we're looking at with the AI and the machine learning.
Starting point is 00:10:43 A lot of it is around looking at different structures of interest. So the blood vessels is one that I've mentioned, but we also have projects in the human brain, and we're looking at the connectivity of the white matter within the human brain. So the white matter in the human brain is kind of the wiring portions of the brain that you can imagine. And with HIPCT, we can look, those wires are actually individual axon cells with very, very long tails that join parts of the brain to other parts of the brain. With the HIPC-T, you can look at the orientations and the directions that these connections are going,
Starting point is 00:11:18 and you can start to unpick, okay, what's the wiring diagram of the human brain? So that's one, another project that we work on with this data. We also have really exciting work going on in the heart, looking at when you have congenital heart disease, how do structures within the heart change when you have these kind of congenital diseases, structures that we expect to be in one location are actually maybe in a different location. And if you're a surgeon performing, you know, if you're a surgeon doing a surgery on a condition to repair congenital heart disease, it's really useful to know, okay, where might these structures
Starting point is 00:11:54 actually be in this kind of different heart. We have to take a quick break, but don't go away. More on this when we come back. So that's how this can filter down to actual patients. Yeah, that's one of the ways in which it can filter down to actual patients. training, surgical training for surgeons to understand better the anatomy and then to improve their kind of surgical skills. But there's also kind of some other interesting ways that are a bit more long term that we're looking at where we look at these very high-resolution hip CT scans and we compare them to scans, clinical scans, so like a clinical MRI or a clinical CT scan that this donor
Starting point is 00:12:43 may have had when they were still alive. And by comparing those scans to each other, it's another area that AI can come in where you say, okay, can we learn anything from this very, very high resolution image that we have from HIPCT? Can we compare it to the scans the donor had when they were in life? And are there any things that we can see in that clinical scan that we didn't really know we're there, but actually once you, once you have the HIPCT data and you align those two, can you suddenly see other features that you maybe weren't able to extract from the original clinical data. Now, I know that since you can only scan cadavers, I'm sure there are certain medical conditions you couldn't use this approach with, right? I mean, tell us about maybe how you might get
Starting point is 00:13:28 around that or how you could use that. Yeah, so, I mean, the other thing about HIPCT is that it's a static technique, you know, kind of the organs are fixed in place, and at the moment we can only scan them like that still. So, you know, there's a lot of conditions, human bodies are not static statues, right? They're dynamic systems. And a lot of times, you know, some of the conditions of interest and the problems that we have are to do with that more dynamic part. So any conditions where something that's kind of, something that's dynamic or is changing that doesn't result in like a structural change to the organ is going to be kind of invisible to hip CT. You can imagine, for example, you know,
Starting point is 00:14:15 very simply kind of like a leukemia, like a blood cancer, like hipsy T. We're not imaging like the flow of the blood and things. And where that's the primary issue, you don't really have access to to that with the hip C.T as much. Do you think you could ever eventually scan a whole body? Yeah, I think that's definitely a goal more like kind of long term in the next sort of five years is to be able to scan an intact whole human cadaver. And I think that would just be a really scientifically interesting thing to do because at the moment we're scanning individual organs. But again, human bodies, organs don't work individually on their own in a body.
Starting point is 00:15:01 They work as part of a system, you know, like the heart and lung. They function together as a system. And so when you image one separate from the other, you lose a load of that connectivity between the two that's incredibly important in terms of how they actually function. So by scanning a whole intact human body, you preserve those connections between the different organs and you get a much better and holistic understanding of how does the body function and how does that go wrong in disease. I know you said you were really surprised when you first saw the, what was it, the lungs, right?
Starting point is 00:15:39 Do you have a favorite organ or is that your favorite? So I think my, my personally, I work, I work a lot with the kidneys and the brain. And one of my favorites is actually the kidney. I think it's a bit of the, it's a bit of an unsung hero. It's a beautiful organ to look at. It's kind of under, under, under, under recognized, I think, maybe. But it's really interesting, fascinating. You have these different compartments within the kidney that serve these very different roles.
Starting point is 00:16:08 And I think also in terms of understanding human disease, kidney, kidney disease. kidney kidney disease is a huge, a huge burden on healthcare systems worldwide. Yeah. And I think this technology offers such a powerful tool for understanding that and maybe being able to mitigate some of the problems people have with transplant rejection and chronic kidney disease and a whole range of other things. Well, this has certainly been fascinating stuff. I want to thank you for taking time to be with us today.
Starting point is 00:16:36 And good luck to you in the future. Thank you very much, Ira. Dr. Claire Walsh, director of the Human Organ Atlas Hub, and you can check out more of these stunning images that are on our website at Science Friday.com slash organs. Speaking of body parts, we got this call from a listener, I think you'll enjoy. We did a segment about the uses of spider silk a few weeks back, including some of its healing properties, and got this call. Hi, it's Linda calling from New Jersey. was listening to the program about spiders and wanted to let you know that my grandmother, who was born in 1889, Kamyanka Stronglova, Poland, told me that when she was a girl and she
Starting point is 00:17:21 cut her hand very badly, she put it in a spider web and it stopped the bleeding and it helped the cut to close up and she always believed in using spider webs to heal things. So just wanted to let you know that. Thanks for all the information. Bye. Thanks for calling, Linda. This episode was produced by D. Peter Schmidt. I'm Ira Flato. Thanks for listening.

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