Optical coherence tomography (OCT) produces cross-sectional images of tissue, most commonly the retina, using light interference rather than physical cutting. Because depth differences occur at the micron scale, OCT cannot rely on timing light bounce-back directly, so it splits light into a reference beam and a tissue-probing beam and reads the phase interference between them to reconstruct depth. The hosts predict the 2026 Medicine Nobel could go to James Fujimoto, David Huang, and Eric Swanson for their foundational 1991 paper, noting OCT's wide clinical use in tracking glaucoma and retinal disease.
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Fujimoto is identified as a professor of electrical engineering and computer science at MIT, Huang at Oregon Health and Science University, and Swanson also at MIT's research lab of electronics.
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The hosts note the 35-year gap since the 1991 foundational paper as fitting a typical Nobel timing pattern they call a sweet spot.
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13:16>> So that one's going to be interesting if that goes. And the last prediction I have for medicine, medicine is the only one where I have three because I think it could be either one of these three, but again, honestly, it's a crapshoot, so probably not, right? But the the last one that I have is optical coherence tomography or OCT. This produces a cross-sectional image of tissue using light. It's a major major medical application. Usually we use this on the retina where there's thin layers that can become distorted. They can lose cells. They can accumulate fluid. OCT reveals that internal structure without actually cutting into the eye. So this non-invasive imaging is really really
13:58nice. The challenge always is like determining depth. Like here over here we're seeing a cross-section, right? And and we're using this optical coherence tomography to to look at what the depth is in a tissue. >> You would think that the depth you can just find by shining light and then seeing when the light bounces back, but this is at the micron level. >> Okay. So getting that timing is going to be insane >> with Google Maps at the micron level for tissue. >> Yeah. Yeah. And you can't really look at delays in light. So what they do here instead is they use interference. They have a reference light and then they have light that comes in and out and then depending on you know >> the timing >> there's going to be phase
14:40>> accumulation and then that is going to interfere with the reference light and that's going to give you a kind of timing signal at the end of the day. Right. It's quite clever. >> That's clever. >> Um this one's actually >> kind of clean. There's three that are involved. Okay. >> They published their paper in 1991. So it's also, you know, 30 years now, 35 years since >> Sweet Spot. So it's a sweet spot of like okay and it's been used for so much because um like OCT now helps clinicians track glaucoma and retinal disease. So it's been used in treatment which kind of goes back to Nobel's original will where he said you know for the benefit of mankind. Well this is pretty clearly for the benefit of mankind. So the three
15:20that I think are going to get it are James Pujimoto, David Hang and Eric Swanson. They had their foundational paper in 1991. Their early retinal images led to imaging living eyes and the practical clinical instruments. Um, Fujioto is the professor of electrical engineering and computer science at MIT. Guang is at the Oregon Health and Science University in Portland. And Swanson is also at MIT's research lab of electronics. >> As you can tell, this year we're toning down the MIT hate a little bit. Uh, >> look, if they win though, it's it's going to happen. >> We got very lucky last year that we had two alma modders win between both
16:01Princeton and UCLA >> and all three were University of California. >> Yeah. All Yeah. >> Right. All like the physics prize. Physics prize was all University of California. >> The um the medicine prize had one UCLA graduate and the Omar Yagi obviously was a professor at Berkeley at the time. At the time, California forever goodbye. Um, it's not looking good. based on these predictions this year. >> It's not looking good. >> No, but physics is coming up.