The Peter Attia Drive - July 08, 2019


#61 - Rajpaul Attariwala, M.D., Ph.D.: Cancer screening with full-body MRI scans and a seminar on the field of radiology


Episode Stats

Length

2 hours and 13 minutes

Words per Minute

205.52306

Word Count

27,373

Sentence Count

1,562

Misogynist Sentences

35

Hate Speech Sentences

15


Summary

In this episode, Dr. Raj Atayde talks about why we don't run ads on this podcast and why instead we rely entirely on listener support to sustain the show. He also discusses the benefits of subscribing to The Peter Atiyah Drive and why you should do so.


Transcript

00:00:00.000 Hey everyone, welcome to the Peter Atiyah drive. I'm your host, Peter Atiyah. The drive
00:00:10.880 is a result of my hunger for optimizing performance, health, longevity, critical thinking, along
00:00:15.940 with a few other obsessions along the way. I've spent the last several years working
00:00:19.660 with some of the most successful top performing individuals in the world. And this podcast
00:00:23.620 is my attempt to synthesize what I've learned along the way to help you live a higher quality,
00:00:28.360 more fulfilling life. If you enjoy this podcast, you can find more information on today's episode
00:00:33.000 and other topics at peteratiyahmd.com. Hey everybody, welcome to this week's episode
00:00:43.360 of the drive. I'd like to take a couple of minutes to talk about why we don't run ads on this podcast
00:00:48.580 and why instead we've chosen to rely entirely on listener support. If you're listening to this,
00:00:53.820 you probably already know, but the two things I care most about professionally are how to live
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00:01:31.600 league of their own. In fact, we now have a full-time person that is dedicated to producing those and
00:01:36.460 the feedback has mirrored this. So all of this raises a natural question. How will we continue to
00:01:42.700 fund the work necessary to support this? As you probably know, the tried and true way to do this is to
00:01:48.320 sell ads. But after a lot of contemplation, that model just doesn't feel right to me for a few
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00:02:00.400 telling you about something when you know I'm being paid by the company that makes it to tell you about
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00:02:22.060 to do what a handful of others have proved can work over time. And that is to create a subscriber
00:02:28.240 support model for my audience. This keeps my relationship with you both simple and honest. If you value
00:02:35.300 what I'm doing, you can become a member and support us at whatever level works for you. In exchange, you'll get
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00:02:52.880 So for example, members will receive full access to the exclusive show notes, including other things
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00:03:19.860 asking questions directly into the AMA portal and also getting to hear these podcasts when they come
00:03:25.800 out. Lastly, and this is something I'm really excited about. I want my supporters to get the best
00:03:30.780 deals possible on the products that I love. And as I said, we're not taking ad dollars from anyone,
00:03:35.620 but instead what I'd like to do is work with companies who make the products that I already
00:03:39.900 love and would already talk about for free and have them pass savings on to you. Again,
00:03:46.420 the podcast will remain free to all, but my hope is that many of you will find enough value in one,
00:03:53.640 the podcast itself, and two, the additional content exclusive for members to support us at a level that
00:04:00.380 makes sense for you. I want to thank you for taking a moment to listen to this. If you learn from and
00:04:05.320 find value in the content I produce, please consider supporting us directly by signing up for a
00:04:11.020 monthly subscription. My guest this week is Dr. Raj Atariwala. Raj is an amazing guy. I've known him
00:04:16.280 for several years. He's incredibly well-trained. He first actually went down the engineering pathway
00:04:21.740 doing his PhD in biomedical engineering at Northwestern, then decided he wanted to go into
00:04:27.560 medicine and sort of apply his engineering approach to that. So he went back to medical school,
00:04:31.780 did his residency in radiology, and then went on to specialize in nuclear medicine and spent a great
00:04:38.380 deal of time at some of the top institutions in North America, Memorial Sloan Kettering, UCLA, USC,
00:04:44.100 et cetera. He's now back in Vancouver. And what he's been up to for about the past decade has been
00:04:48.800 effectively creating a new way of doing MRI. So he's sort of what I think can only be described as an
00:04:56.160 MRI ninja. And that is to say, he's been able to tinker with the hardware and the software to create
00:05:02.240 a completely revolutionary product and process by which to look at the body using this technology of
00:05:10.040 magnetic resonance. Now, I think this is a bit of a technical episode, but I also think it's one that
00:05:15.160 anybody who's ever had an X-ray, a CT scan, an ultrasound, an MRI in their life needs to listen to.
00:05:20.460 Why? Because truthfully, most doctors don't actually understand this stuff in great detail.
00:05:25.700 You have to really go out of your way in medical school and residency to understand radiology.
00:05:31.220 I was obsessed with it. I went out of my way to learn about it. I learned a little bit about it,
00:05:35.240 but obviously nothing to the level of what someone like Raj knows. And so what we did in this episode,
00:05:40.240 which you can sort of divide into two halves, is as follows. The first half is sort of a history of
00:05:44.600 radiology. So we start with talking about what an X-ray is, how it works, what the radiation
00:05:49.960 does and doesn't mean, CT scans, ultrasounds, PET scans, nuclear medicine scans, all of these things.
00:05:56.800 And I promise we've done this in a way that is really geared towards the patient. I think we do
00:06:01.060 a pretty good job of always bringing it back to language that makes sense and we don't get terribly
00:06:06.060 lost in the physics. And of all areas in medicine where you can get lost in the physics,
00:06:10.000 this is head and shoulders above the rest. Second half of this episode, we really do this deep dive
00:06:16.120 into cancer screening and this particular type of MRI technology that Raj has almost single-handedly
00:06:23.640 developed, although he would probably bristle at the sound of me saying that because he's just such
00:06:27.620 a modest fellow. What I enjoy about this episode is it gives me a little bit of a chance to talk
00:06:32.400 about cancer screening. This is something I'm incredibly passionate about and it's something
00:06:35.440 I love talking about with my patients. The show notes for this are going to be important because one,
00:06:40.380 radiology is obviously a very visual field. You see things and much more than you sort of hear
00:06:46.440 things. So we're going to do a great job to pair a lot of what we discuss with images, especially once
00:06:54.240 we get into the confusing MRI stuff and we try to explain the difference between a T1 weighted image
00:06:59.900 and a T2 weighted image and a diffusion weighted image and things like that. The second thing is we're
00:07:05.680 going to link to some of the material that we use with our patients on cancer screening because I know
00:07:12.140 this is a very controversial topic and I suspect that this episode is going to generate just a lot
00:07:16.640 of controversy, but I want to be clear that cancer screening is a very personal decision and it comes
00:07:22.120 with risks. And the biggest risk, of course, is a false positive, which then leads to subsequent
00:07:26.780 screening, emotional distress, potential harm. We talk about all of this stuff and as I said, we'll link to
00:07:34.240 some of the materials that we've prepared specifically for our patients that I think just create a nice
00:07:39.520 primer for how to go through that. So without further delay, please enjoy my conversation with Dr. Raj
00:07:45.280 Atariwala. Hey Raj, thanks for carving some time out today in the middle of your busy day. I've
00:07:53.220 probably done what no one else has done before, which is shut down this clinic, huh?
00:07:57.160 That's fantastic to see you again and to be here. It's a pleasure as always.
00:08:00.760 What's the deal with Vancouver and Uber? I got off the plane this morning and tried to
00:08:06.160 get an Uber to come here and apparently there's no Uber in Vancouver.
00:08:10.920 It's stunning. Everybody complains. We all complain, but I don't know, somebody somewhere
00:08:15.740 is not allowing it. It was amazing. I was in India and you can get Uber in India.
00:08:21.620 Yeah. And it's not a Canadian thing because I Ubered in Toronto.
00:08:25.080 Toronto, Calgary, almost all the country, just Vancouver.
00:08:27.740 Yeah. Very well. I'll reserve my editorial comments for myself. Well, I've been looking
00:08:32.340 forward to this for a long time, Raj. We've known each other for about four years. I think we were
00:08:35.700 introduced through a mutual acquaintance who's a good friend of mine and has become very interested
00:08:41.020 in your technology. And I'm not even sure if you remember the context, but the context was
00:08:46.280 basically this person reaching out to me to say, Hey, there's this really fancy MRI scanner up in
00:08:53.980 Vancouver. Can you go check it out for me? And at the time I was focusing a lot on different
00:09:03.720 technologies that might be able to aid in the detection of atherosclerosis. And he may have
00:09:09.660 misunderstood what I was interested in, but it was sort of pitched to me through that lens.
00:09:14.060 You and I hopped on a call. I still remember where I was sitting actually in my office at the time.
00:09:19.080 It was probably, yeah, it was in January. By the end of that call, I was really interested. And you
00:09:24.440 said, look, I mean, I think you should just come up to Vancouver, get scanned and let's spend a day
00:09:28.260 discussing it. And the rest is history. So, you know, what I wanted to do today was obviously talk
00:09:33.060 a lot about AIM, which is the, well, I guess it's the name, is that the name of the company or is that?
00:09:39.160 Yeah. So actually what I did is I actually set up AIM as a private MRI company and we basically put
00:09:44.280 in the MRI machine so I could play with it. That's one of the problems of being an engineer.
00:09:49.080 And so AIM is the name of the scanning company, the clinic, but we've actually now kind of moved
00:09:53.620 it into PreNuvo. And what PreNuvo is about is actually to basically sort of put the power of
00:09:58.500 preventative medicine into patients' hands. Yeah. Well, we'll talk a heck of a lot about this,
00:10:02.980 but let's talk a little bit about your background because that was one of the things that right off
00:10:06.580 the bat made me realize that this was going to be an interesting discussion. I, even in medical
00:10:11.920 school, just took a huge interest in radiology. I never thought for a moment I would become a
00:10:15.980 radiologist, but I knew that whatever type of medicine you practice, you have a choice,
00:10:21.180 which is basically you can just be confused and intimidated by all of these scans that your
00:10:26.360 patients get, or you can at least try to understand them and have some hope of appreciating the risks of
00:10:32.840 them, the benefits of them, the subtleties, et cetera. So when I did my radiology rotation,
00:10:36.580 I was probably the most eager student who wasn't going into radiology. And I remember,
00:10:43.580 and I still have my notes, but I took, I mean, maybe 50 pages of notes, drawing coils and all
00:10:50.340 sorts of things. So let's start at the beginning. You have a background in engineering, which a lot
00:10:56.240 of radiologists seem to have, right? It's actually common in radiology. It's like,
00:11:00.520 basically there's a lot of technology in radiology. And so as a result, it attracts those of us who
00:11:04.960 actually are technophiles. And so my background, actually, I started out in chemical engineering.
00:11:09.600 And then during that period of time, kind of realized that I actually kind of liked the body
00:11:14.500 and physiology and how that works. And as a result, I then went into biomedical engineering,
00:11:19.020 where I did my master's and PhD in biomedical engineering in Northwestern. During that period
00:11:24.160 of time, I was actually working on fluid mechanics. We're actually looking at blood flow and hemodynamics
00:11:28.940 and all sorts of complicated things. And we also actually did what engineers do. We actually had all
00:11:34.660 these manual systems that we're using to measure blood flow and blood pressure. And we decided,
00:11:39.680 okay, let's build a robot to do it instead. So we did. And this robot that we actually built allowed
00:11:44.580 us to do keyhole surgery in the eye that wound up attracting a lot of attention from physicians,
00:11:50.720 from top tier universities all over the United States, from mass general everywhere. And as engineers,
00:11:57.300 the attitude was, we can build anything you want. What do you want? A lot of times physicians can
00:12:02.160 never answer that. I was working with a lot of these top tier guys, like editor in chief of
00:12:06.360 the different medical journals and ophthalmology. And it was like, they were speaking a different
00:12:11.480 language and I just didn't understand what they were talking about. And so I actually kind of decided,
00:12:16.820 okay, well, let me apply to medical school and see what happens. So I can actually kind of learn
00:12:21.260 this language and kind of learn more about medicine. And so I applied and then I actually kind of
00:12:27.720 got accepted and I was like, hmm, do I want to do this? It's like, I'm really an engineer
00:12:31.960 and was born an engineer. So my PhD advisor's famous last words were that the engineering world
00:12:37.660 will always take you back. So I went off to medical school and actually hated every minute of it. It
00:12:43.600 was kind of like, I need to know more. I'm one of those kids who's kind of like, why, why, why,
00:12:48.040 why, why? How does this work? Explain this to me. I don't get it. And realize that there's a lot of
00:12:53.040 things in the body and physiology and pathophysiology that we just don't understand.
00:12:58.760 Despite the massive amount of literature that's out there in the medical world, you really couldn't
00:13:03.200 find a lot of the answers of why things go wrong and how they go wrong. So then I'd wind up sort of
00:13:08.400 exploring, okay, how do we advance understanding of what's going on in the body? Like the simple aging
00:13:13.200 process, what happens? Why does everything change? Why? People can answer it. Instead, it was like,
00:13:18.960 okay, memorize this list of changes. I'm like, okay, great. Let me try and remember all that.
00:13:25.540 And what I would actually start to boil down to is that I would actually go back to my engineering
00:13:30.180 pathophysiology texts and I actually read them and talk to the PhD guys. And they would actually
00:13:35.780 sort of give me the theories on what they thought was happening. And when you actually got that theory,
00:13:40.580 it was almost like planting a seed. Then you actually kind of understood how the entire tree would
00:13:44.400 look. And that's when I said, okay, maybe this is good, but I still need my technology.
00:13:49.540 Where is technology going? We worked on some of the very first surgical robotic machines ever built.
00:13:54.740 My colleagues presented the first telerobotics telepresence conference ever held in the United
00:13:59.960 States. At the same time, the group that made the Da Vinci was there. I kind of looked and said,
00:14:04.660 there's not a lot of space for robotics because people don't want machines operating on them. As a
00:14:10.340 former surgeon, I'm sure you probably feel the same way. You don't want a machine operating on you
00:14:13.620 unless it's going to be better. So that's when I decided, okay, the technology that people understand,
00:14:18.900 doctors understand is a picture. And that picture is radiology. And that's really where all the
00:14:23.180 technology is. And so I actually started in an area called nuclear medicine, which is a sort of a
00:14:28.120 small specialty within radiology, which is where you're actually looking at functional imaging,
00:14:32.760 how things work, how do things change, what happens over time, and really enjoyed that area because
00:14:39.460 it was sort of showing you what's happening when things are normal. And then when things
00:14:43.380 become abnormal, and it was actually one of these other amazing fields that in medicine,
00:14:47.580 there's a lot of shades of gray. Whereas in nuclear medicine, it's almost black and white.
00:14:51.300 It's there or it's not. It's one of these very few areas where you actually get a binary choice of
00:14:55.960 what's happening. Is there a problem? Yes or no? As opposed to, well, there might be.
00:15:01.660 So that's actually what I liked about it. But then I also kind of realized that radiology is basically
00:15:06.020 very much like anatomy. You actually see what's going on. You actually see the changes and you see the
00:15:10.160 shapes of things. And you use that very much as a blueprint for a building to actually kind of see
00:15:14.220 what it does. Whereas nuclear medicine is kind of, instead of the blueprint, you actually kind of
00:15:18.840 know there's all these people carrying letters moving in and out of this building. We don't really
00:15:22.500 know the detail of where the building walls are, but we know that there must be something happening
00:15:27.060 there. And hey, when you put the radiology with the architecture together of the blueprint of the
00:15:31.980 building, then you combine that with the people going in and out of it, you realize it's the post office.
00:15:36.520 And you realize that these are postal workers carrying things. And here's the geometry of the
00:15:41.260 building. So that power really is actually quite useful in the fact that it's really that there's
00:15:46.500 this famous equation when people actually realize to put functional imaging or nuclear medicine
00:15:51.140 imaging together. The first device that did that was positron emission tomography and CT or PET-CT.
00:15:57.640 And the famous equation is that one plus one equals three. These two separate modalities of
00:16:02.060 functional imaging and anatomic imaging come together to actually make something better than
00:16:06.420 each part individually. And so that's what really attracted me to the whole field, just because you
00:16:11.380 could see what's going on and you can actually see the power of what's happening.
00:16:14.840 That was certainly one of the more powerful lessons I remember as a medical student when I
00:16:20.220 went sort of headlong into radiology, which was what I really liked about this rotation. I remember,
00:16:24.840 I wish I could remember the names of the residents, but they took me under their wing,
00:16:27.820 even though they knew I wasn't going to be a radiologist. And as you know, from being in medical
00:16:31.020 school, that's a little unusual. Typically the residents tend to gravitate to the students
00:16:34.980 that are going to follow in their footsteps. But I think they saw in me genuine curiosity and they
00:16:39.900 thought, well, look, the smarter we can make this surgeon, the better down the line for us
00:16:44.700 radiologists. And so I remember them taking me aside and saying, look, Peter, anytime you order a test
00:16:49.980 in the back of your mind, you have to be asking yourself, do you want anatomical information or
00:16:53.980 functional information or both? And the example you gave is a great one. And in the show notes for this
00:17:00.000 podcast, we'll link to tons of pictures so that people understand what is meant by
00:17:04.940 anatomic imaging. And the way I would explain this to a person is an anatomic image has nice sharp
00:17:11.040 edges. It looks like what it is you're trying to take a picture of. So the anatomic image of the
00:17:17.680 brain shows all of the substructures. And when the radiologist looks at it, he or she can make out
00:17:23.320 every little blip and bend and crevice inside of the brain. And they can comment on different
00:17:29.700 structures while there's a tumor here, or there's a blood vessel that's slightly dilated there.
00:17:34.360 If you contrast that with the PET scan, as you pointed out, that's looking at a function of the
00:17:38.600 brain, which is how much glucose does it uptake? And instead it lights up darker, the more glucose
00:17:44.280 that's being taken there. And that's so you're near analogy. The CT scan is showing the architecture
00:17:49.740 of the post office, but the PET scan is showing you the distribution of people moving into different
00:17:56.840 areas of it. And by putting it together, that gives you a really powerful picture.
00:18:01.040 Exactly. And that's actually exactly how it works. And one of the things that might be useful as well
00:18:04.720 is if we kind of look at the different sort of techniques that are used between nuclear medicine
00:18:08.500 and radiology, we all know that imaging started with the simple x-ray, but that was actually
00:18:13.940 groundbreaking for the field of medicine.
00:18:15.780 Let's start with that. So everybody has seen an x-ray and I think most people, if they can close
00:18:22.160 their eyes and picture it now, or look at an image kind of know directionally that an x-ray is nothing
00:18:29.100 more than a series of contrasts going from black to white and everything in between. So at the highest
00:18:37.680 level, how do we take an x-ray? What are we doing with those little electrons going through someone?
00:18:42.480 How does it produce that image?
00:18:43.520 For sure. And it's quite amazing actually how it was discovered by Runt. And effectively what it is,
00:18:47.680 is we're taking these high energy wavelength and it actually penetrates right through the body.
00:18:52.840 And anywhere where there's something dense, very hard, like bone, the x-ray beam can't make it
00:18:58.240 through. We've all sort of taken like a flashlight and sort of shown it through our finger and we can
00:19:02.520 actually see the red light coming through. Well, effectively that's what an x-ray is. We're just taking
00:19:06.920 higher energy wavelength that we can't see with our eyes. And it's actually allowing the areas where
00:19:12.100 there's things like air or soft tissues, the x-ray penetrates right through it and goes right through,
00:19:16.440 shines through. Whereas in places where there's bones, the x-rays can't make it through. So they
00:19:20.560 actually get left behind. And that's what gives us like the white pictures of the bone because
00:19:24.720 the film that's exposed on the other side, soft tissues, the x-rays have gone through,
00:19:30.100 they turn it from white to black. Whereas in bones, the x-ray doesn't make it through because it gets
00:19:34.700 left behind in the person. And therefore on the film on the other side, it stays white.
00:19:38.420 And back in the days of Rankin, did they appreciate the damage of ionizing radiation or were there
00:19:44.340 a number of casualties along the way from people being far too exposed to this type of energy?
00:19:49.940 Unfortunately, there were lots of casualties. And actually our understanding of radiation
00:19:53.660 has actually been moved by really traumatic events such as Hiroshima and Nagasaki and things like that,
00:20:00.160 where there's been real radiation damage. And we've actually been able to watch people over time.
00:20:03.980 And recently in the past 10 to 15 years in imaging, we've actually realized the danger of
00:20:10.100 this high powered ionizing radiation and how it can damage cells. And when the DNA of the cells get
00:20:15.760 damaged, there's a risk of inducing cancers with that. And so we're actually starting to understand
00:20:20.400 that more and more. And we're actually starting to see that a lot of patients, individuals are like,
00:20:24.600 look, I know about the potential damaging effects of x-ray radiation. Therefore, I don't want a lot of
00:20:29.640 x-rays, CT type scans. Now, the way I generally talk about this with my patients, I have a graph
00:20:35.340 that I show them that on the x-axis lists a number of different technologies. So a chest x-ray,
00:20:42.040 an abdominal x-ray, a mammogram, and they're generally in increasing amounts of radiation.
00:20:47.020 So at the top end of that spectrum, you'd have a whole body PET-CT just for, if you want it to go
00:20:51.560 as ionizing as possible. And then the y-axis, I use these units called millisieverts. Can you explain
00:20:57.480 what a millisievert is? Exactly. So a millisievert is actually the unit of measurement of radiation.
00:21:02.280 And it's actually set by the standards group, System Internationale in France, that actually
00:21:07.440 sets what a standard dose of radiation is. And now it's actually important that a lot of people
00:21:12.380 really don't understand radiation. There's good radiation, there's bad radiation, but radiation
00:21:16.820 is anytime you actually have any ion that's actually releasing a component of its energy,
00:21:22.660 that energy has to get deposited somewhere. It actually comes off as a photon
00:21:26.540 of energy that has to, by, I guess, energy effects, go from, it's never created, it's never
00:21:34.500 destroyed, but it's actually transferred. And so that energy, if it doesn't go through you,
00:21:38.940 it's actually going to deposit in you. And if it actually deposits in you, that's where it can
00:21:42.660 actually cause the damage. And now when we look at all the different types of imaging, as you talked
00:21:47.600 about, on one end, you have the mammogram, which actually has a very low amount of radiation in
00:21:52.460 millisieverts, it's usually about 0.05, which is quite negligible. Whereas on the other end of the
00:21:58.580 scale, you'll have the PET-CT. And now the PET-CT basically couples the radiation from the CT.
00:22:04.620 And the CT scanner is basically a powerful x-ray that's spinning around the body and creating a
00:22:08.900 three-dimensional view of you. Combined with the PET, which is the positron emission tomography,
00:22:13.740 where you're taking radioactive glucose, and you're actually labeling with fluorine.
00:22:18.480 And that fluorine is a radioactive fluorine-18, which actually now gives off a positron.
00:22:23.840 And that positron has tremendous amount of energy. It's the highest energy that you can actually have
00:22:28.020 in imaging for radiation. And that's 511 kilo electron volts. So very, very high.
00:22:33.720 And so when you combine those two together, you wind up getting, typically, when we actually give
00:22:38.500 somebody radioactive glucose for a whole body scan for, let's say they have cancer, it's roughly
00:22:43.640 one millisievert per megabequereld. But I guess I'm trying to convert the Canadian.
00:22:49.600 Oh, that's okay. Yeah, we've got an international audience here. You don't have to make it
00:22:53.180 Americanized.
00:22:54.840 Right. So we do it in megabequerels up here in Canada. And so it's typically about 35 megabequerels
00:23:00.840 per millisievert. So typically, somebody will actually get the US dose would be about 12 millimoles.
00:23:06.320 And so that's about the 12 millisieverts of radiation, in addition to what they get on the CT scan.
00:23:11.280 So they could easily get 30, 40 millisieverts in total in that scan, if they were doing chest,
00:23:17.540 abdomen, pelvis, for example.
00:23:18.980 It's possible. Yeah. And a lot of that radiation would come from the CT. Whereas with nuclear
00:23:22.840 medicine, what we typically do, since we're actually going to inject somebody with the
00:23:25.900 radioactive material, as a result, we've exposed them to that radiation. So all parts of the body.
00:23:30.360 So as a result, as it circulates through their entire body, we want to take pictures of everything
00:23:34.660 from head to foot. Because if we're going to give somebody radiation, we want to maximize the
00:23:39.440 amount of data we're going to extract from that exposure.
00:23:42.720 Now, I don't know in Canada what the number is, but in the United States, the NRC recommends that
00:23:47.880 no one receive more than 50 millisieverts in a year. But of course, not all of that can be assigned to
00:23:54.500 radiography because living at sea level exposes you to what, two millisieverts a year, maybe three.
00:24:01.520 I mean, I think even if you live at elevation, people in Denver are getting probably six or seven
00:24:06.200 millisieverts a year at background. I'm probably a bit off on that. It might be a bit less.
00:24:09.540 That's right. Yep. So the higher you go, actually get more cosmic radiation.
00:24:13.060 And then as well, certain geographies will actually have radon, which is another exposure to the
00:24:18.720 millisieverts. And as well, when you actually travel, when you actually go up in altitude in
00:24:23.080 planes, we actually get a lot more radiation exposure. So that's why pilots, for example,
00:24:28.580 when they wear glasses, they actually have to block the UV radiation, the UVA, UVB,
00:24:34.820 and also the x-ray radiation, which is much more prevalent at higher altitude.
00:24:38.880 The route matters. I know I've calculated this for myself doing a lot of East West Coast travel.
00:24:45.120 Fortunately, not very much exposure. I believe it's less than 0.1 millisievert per round trip.
00:24:51.240 But if you do LA over the pole, right, all of a sudden it goes up by, again, I don't want to
00:24:57.100 misquote it because we have the data so I could just post it, but it goes up by a nonlinear amount.
00:25:02.460 It's much more radiation when you cross the North Pole than just the extra distance you travel.
00:25:09.000 Exactly. And that's because of the ozone. The less ozone you have at the poles, the more
00:25:12.620 exposure you're going to get because the ozone actually absorbs the radiation.
00:25:16.560 So there's actually a calculator available online for people to actually determine how much
00:25:20.400 radiation they're getting from exposure. And it's actually required that pilots and flight
00:25:23.900 attendants calculate their dose.
00:25:26.040 We'll make sure we find that and link to that. I just, because the NRC says 50 is the limit,
00:25:30.800 I've never really thought of that as we should go up to 50. I've thought of that as they probably
00:25:36.320 have some reason to believe that successive years with exposure to 50 millisieverts is not a good
00:25:41.320 idea. Do we have a sense of what the implication of that is in terms of normal physiology?
00:25:46.360 We do and we don't. And actually a lot of the time, our understanding of that really comes from,
00:25:50.440 like I said, the tragedies of Hiroshima and Nagasaki, as well as other people like in the Fuji reactor
00:25:55.540 who actually got exposed. And that's where understanding of the damage comes from. Now
00:26:00.240 there's actually a landmark paper out of Columbia that actually looked at the amount of radiation
00:26:03.900 that people actually receive from CT scanners. And it actually forced radiology as a field to
00:26:08.440 actually look at the potential damaging effect of x-ray radiation. And what they actually kind of
00:26:13.360 found is that the younger you are, the greater the risk of cancer induction from CT scanners, which is
00:26:19.380 why in the pediatric world, we actually try and really minimize the amount of dose that children in
00:26:23.560 particular are getting. And the sex as well matters. So females are actually more sensitive to radiation
00:26:28.580 than men. Meaning if you took a 20 year old male and a 20 year old female, so both in their reproductive
00:26:35.140 prime, are you saying that the ovaries of the woman are more sensitive to DNA damage in the egg
00:26:43.100 than the sperm are in the testes of the male? Exactly. I didn't know that. Why is that? And that
00:26:48.700 actually has to do with the fact that the egg was actually produced during embryonic stage.
00:26:53.720 And as a result, that DNA is effectively frozen in time. And so as women are getting older and older,
00:26:59.620 they're releasing these DNA in the eggs. So therefore the younger you are, the fresher, the DNA,
00:27:06.240 whereas, you know, when they're prime sort of around 12, which is when this DNA comes out of the,
00:27:10.340 I guess, frozen state during the beginning of menstruation, that's when these eggs start to
00:27:15.320 be released. So actually 12 is sort of the worst time for females. Which is really sad because of
00:27:20.160 course anybody who spent time in a hospital knows that there are invariably kids that need to undergo
00:27:25.300 radiographic studies. You only need to spend a few days in a cancer ward to realize all these poor
00:27:29.860 children that are right at that age and they're being exposed to it. And unfortunately there's not
00:27:34.380 much of a choice. And trauma is another area where the child comes in having sustained a bad injury in
00:27:39.400 a car accident. You go out of your way to use ultrasound whenever possible, but invariably sometimes
00:27:44.040 patients do require x-ray and CT radiographic studies. So let's go back to the x-ray because
00:27:50.580 I like, I like where you started there historically. And then you alluded to the fact that basically if
00:27:56.200 you understand how an x-ray works, if you truly understand what's happening, then you understand
00:27:59.800 what a CT scan is doing because it's just doing it in three dimensions spirally. So the other thing
00:28:05.160 about x-ray that I think is very interesting for anyone who spends time looking at it just to
00:28:09.480 appreciate it, even though it seems so simple is nothing in the body is two dimensional. So you
00:28:15.360 talked about how this photon is going through the body and if it hits a rib, well, that's going to
00:28:19.920 show up as white. Whereas if it's passing through the lung between the ribs, it's going to show up as
00:28:24.820 black. But of course you could hit a rib on the front, but not on the back. You can hit a rib on the
00:28:29.440 back and not on the front. You can hit the sternum. So when you look at an x-ray, even to this day,
00:28:35.580 I'm still constantly amazed at what the collage looks like of overlapping layers of tissue.
00:28:44.340 And I mean, I just don't think I ever got good at reading x-rays. It was actually easier for me to,
00:28:49.960 I think, because we just spent more time reading CT scans and there's so much more anatomic detail.
00:28:53.800 But when I look at these old time radiologists, look at x-rays and the stuff that they could pull
00:28:58.260 out of it, I was blown away. Exactly. It's true. It's an amazing skill to actually be able to pull that
00:29:03.800 3D information out of a 2D picture. And if we actually kind of think about it, our brain is
00:29:08.160 designed to always imagine in 3D, always think in 3D. You know, even if you actually, somebody lost an
00:29:14.000 eye, they can still see in 3D. And that actually has to do with the fact that that's how our brain
00:29:18.520 was wired or I was wired. And so the amount of information in x-ray is phenomenal. But the
00:29:24.500 biggest problem is that sometimes you're actually overlapping different things and you just can't see.
00:29:28.060 So quite often, the reason we do two x-rays, when you do a chest x-ray, you do a frontal,
00:29:33.400 a PA, as well as a lateral, is so you can actually try and mimic those two together to become a
00:29:39.020 three-dimensional object. And so when CT came around, that's when it actually really allowed
00:29:43.320 us to look at things in 3D. And that's where surgeons and everybody else who actually operates
00:29:48.440 and deals with people in 3D, they can actually start to look at these and actually start to imagine
00:29:52.720 what they're going to be operating on. They actually kind of get the power of where the 3D image
00:29:57.120 comes in. And so a simple way to think about an x-ray, as I try to tell people, it's almost like
00:30:01.700 an x-ray is basically like a flash. Take a single flash and you get a picture. Whereas a CT scan is
00:30:07.220 really like a searchlight in a boat kind of going around an island. You actually get all the images
00:30:11.580 the whole way around. And then the equipment, what it does, it actually sort of sees how the intensity
00:30:16.160 passes through, let's say, two panes of glass and comes out the other side. And then you can actually
00:30:21.100 start to evaluate what's going on inside that entire building. The police officers use this all the
00:30:26.780 time when they actually need to stake out a building or a site. They actually use it to determine where
00:30:31.100 the occupants are. And that's exactly what an x-ray does. It's triangulation effectively by spinning
00:30:36.900 around in multiple different cycles by going around 360 degrees. So we should clarify our semantics for
00:30:42.220 people. We use the term CT very loosely, but it stands for commuted tomography. And sometimes people
00:30:47.140 back in the old days used to refer to it as CAT scan or CAT. And the A was for axial, of course,
00:30:52.140 because it's going up and down the axial dimension of the person.
00:30:55.820 Right.
00:30:56.360 When was the first CT scan put into clinical practice? I mean, would it have been in the
00:31:01.100 early 80s or something like that or earlier?
00:31:03.400 Earlier than that, it was actually EMI, the phonographic company that actually built the
00:31:07.300 very first CT or CAT scanner. And I believe it was in the 70s or even earlier. It's actually been
00:31:12.780 around for quite a while. Realistically, that three-dimensional image really revolutionized
00:31:17.280 medicine, as did all imaging.
00:31:19.140 And the other thing that people will often hear about, and I guess maybe patients don't
00:31:23.540 hear about it as often, but it certainly gets touted to them as a feature, is they talk about
00:31:28.400 the speed of these things. They say this is this many bits or that many bits. And presumably the
00:31:33.700 first one was a four-bit?
00:31:34.960 I think it was actually even less than that. It might have been two-bit. And it actually just took
00:31:38.160 a long time to go around. And it was actually first used in the brain.
00:31:41.800 So let's explain what that means. So two-bit means you really only have two flashlights.
00:31:46.220 Exactly. Or one flashlight, one detector.
00:31:48.500 Exactly. Yeah.
00:31:49.260 On and off.
00:31:49.660 It'll be easier, I think, when people look at pictures and we'll make this clear. But
00:31:52.600 you have this cylinder that goes around the patient who's laying down. And there's one place where you
00:31:58.120 shine the ionizing radiation. And on the backside of the cylinder is where you read it. And then that
00:32:05.160 thing has to rotate. So it's moving in its rotational plane, but also moving up and down the Z plane
00:32:11.820 in time. Correct?
00:32:13.200 Right.
00:32:13.420 This makes so much more sense when I can use my hands, by the way.
00:32:16.220 And so it's exactly like that. Basically 180 degrees apart, you have the x-ray and the
00:32:20.900 detector. And then it actually starts to spin around in rapid revolutions. So when you actually
00:32:25.120 look at a machine, there's the donut hole in the middle, but around it, there's actually the casing
00:32:30.840 and these two parts, the detector and the machine that are actually spinning around the body very,
00:32:34.600 very quickly. It's actually quite fascinating. Maybe we can find a picture of one of these actually
00:32:39.000 with the cover off.
00:32:39.860 Yeah, we'll find one. And I feel like even when I got to residency, which is, so let's just say
00:32:46.780 directionally 20 years ago. I mean, I still think people were using 16 and 32 bit scanners, right?
00:32:53.220 Yeah, they were.
00:32:53.780 So 16 bit means you've got eight, you're spaced out equally eight units, and then you've got your
00:32:59.120 eight detecting surfaces.
00:33:00.900 Right. And so what it winds up doing is, so if you start at the, let's say the top of your head
00:33:04.880 and go to the bottom, we'll call that the axial dimension. What the eight bit would mean is that,
00:33:09.740 or eight slice, I guess is probably the more correct term, is that you basically have like
00:33:13.660 one slice and then you're actually measuring immediately below it and immediately below that.
00:33:17.260 And so as a result, as you're circulating around the person or the patient, you're actually doing
00:33:22.160 eight slices at a time, or 16 slices at a time, or 32 slices at a time. So what that means is as
00:33:28.160 you're rotating around, the amount of coverage you get is more, the higher the number of slices,
00:33:34.060 or you can actually also have thinner and thinner slices. And the more thin you get, the more detail
00:33:39.960 you can get from an imaging perspective, but the more radiation you require to overcome the signal
00:33:45.280 and the noise background. Yeah. So what you're trading off is an optimization problem,
00:33:50.080 which is speed, resolution, radiation. Now, where are we today? I assume 256 is pretty common.
00:33:58.220 256 is one of the common ones that's actually used for things that are rapidly moving.
00:34:02.140 Typically the heart. The heart. Do we have a 512 yet?
00:34:04.620 In research. Really? Yeah. You can actually make them as high as you want. The problem is you
00:34:08.140 eventually sort of get to these diminishing returns of how thin the slices are and how many images you need.
00:34:13.220 So if someone needed to scan a part of the body with a CT scan that wasn't moving functionally,
00:34:19.160 so something that's anatomically complicated, like the pancreas, but it's not moving like the heart,
00:34:24.960 are you good enough at 128 or 64? Like does 256 offer an advantage?
00:34:29.420 It doesn't really offer any advantage. No. You can actually, eight slices work quite well. As long as
00:34:34.380 the person can hold their breath and there's not a lot of movement, eight slices work well.
00:34:37.320 One of the things I remember at Hopkins, there was a radiologist there. I don't know if he's still
00:34:40.980 there. I think his name was Elliot Fishman. And he was sort of the god of pancreatic reconstruction.
00:34:45.760 And of course this was important at Hopkins because at the time Hopkins was the epicenter
00:34:49.520 of pancreatic cancer surgery. And as important as it was to have a great surgeon, John Cameron,
00:34:56.120 Charlie O, et cetera, that could do this operation, it was as important to have an exceptional radiologist
00:35:02.340 because as you know, and maybe some of the listeners know, many patients with pancreatic
00:35:07.520 cancer technically shouldn't be operated on. And you'd really like to know that before you enter
00:35:12.620 the patient's abdomen, which is not always possible. But I remember that Elliot Fishman's
00:35:17.340 images, he would have these 3D reconstructions of the pancreas at a time. I mean, today that's pretty
00:35:22.220 common, but at the time, like nobody was contemplating this kind of resolution. And we would sit there
00:35:27.320 on rounds and look at these images when they were still printed out on that sort of vellum,
00:35:32.460 whatever the hell that plastic paper is. And you just couldn't believe it. So to think that he was
00:35:36.460 doing that with relatively few slices, right? Exactly. And like the whole power of that is,
00:35:41.720 again, as I mentioned at the very beginning, is that our brain thinks in 3D, right? And so the
00:35:46.180 power of that, as opposed to looking slice by slice at a 2D image, became very useful because now it
00:35:51.240 became real. It became what our eyes could see, what our brains could see. And it actually really
00:35:56.000 helped everybody plan their surgery. And so it really was revolutionary to actually start to
00:36:00.340 look at things in three dimensions. Now there's another element that we're going to introduce
00:36:03.480 to this, which is contrast. So what is contrast? Why do we use it? What contrast is, and for the CT
00:36:10.940 world, it's actually an iodinated material. And so what iodine does, it actually absorbs the photons
00:36:17.000 and so therefore makes things look white on a CT scan. So it's like having liquid bone in your
00:36:22.360 bloodstream. Pretty much a liquid photon absorber. And so what it does is, so we actually inject it
00:36:27.880 into the vein and then we actually, the heart pumps it around. And so that means we're actually
00:36:32.000 able to time when we actually take the CT image in order to be able to see what type of organ we're
00:36:37.040 looking for. So you can think of it, if you actually get the arterial phase, you'll actually
00:36:41.440 see where the arteries are connecting to an organ or else you can wait for the venous phase or when
00:36:46.240 the veins are returning blood flow from that organ. And you actually see the entire detail of the
00:36:50.720 organ. And what contrast really is, is basically a way to light up the blood vessels and light up
00:36:56.260 the capillary net and everything in between, between the artery and the vein to allow us to
00:37:00.980 see the anatomic detail from the perspective of adding blood to it. And the name of course
00:37:05.540 explains exactly why it's to create contrast. Exactly. In the absence of contrast, blood looks
00:37:12.920 functionally like water. I feel like I just want to go into this in so much detail, but I'm also
00:37:17.840 trying to be mindful of not going deeper than we need to. But I guess we can talk about a Hounsfield
00:37:22.280 unit because that will allow us to explain this contrast thing and tissue differences, right?
00:37:26.880 Exactly. So what actually happened in CT is that Hounsfield came along and kind of said, okay,
00:37:31.080 how do we calibrate this? And so there's a range of Hounsfield units from minus a thousand, zero to
00:37:36.480 2000. And what that actually has to do with is density. And so zero is defined as water. A thousand is
00:37:43.760 basically air. And so as a result, we can actually see the difference between the density of bone and
00:37:49.920 air with water effectively in the middle. So you have at plus 1000, it is black, right? At minus 1000,
00:37:57.800 it is pure white. Pretty much. Yeah. And the biggest problem is that the eye actually can't see that
00:38:02.520 range. So on our computers, we actually will narrow down and look at, we'll actually look at the higher
00:38:07.940 Hounsfield units and we'll actually see lung. Then we go down and we look at the denser material
00:38:12.060 and that becomes bone, but we can't see the whole thing. Right. So you could technically specify
00:38:18.040 multiple parameters. You could specify the width of your window and where it is centered,
00:38:22.580 for example. So if you wanted to look at lung, you would center it much closer to positive numbers
00:38:29.620 and you don't need a very wide range, do you? No, not at all. So what's a typical lung window,
00:38:34.920 like 800 plus or minus a hundred or something to that? I mean, I have no idea. I don't even
00:38:38.780 remember anymore, but it's, that's the gist of it, right? Exactly. Yeah. And actually I don't
00:38:42.820 even remember because you push a preset. Once you set it, you never really change it much.
00:38:47.980 So I had committed all of these to memory in medical school. I was so obsessed with knowing
00:38:51.400 the window for optimizing the viewing of every tissue. As did I. And then when you actually start
00:38:56.040 to practically use it, you kind of, you wing it because what happens is that every person is
00:39:00.280 actually slightly different appreciation for contrast. Yeah. And also it's like the amount of
00:39:04.660 photons lost based on the patient's body size, the amount of absorption changes things. So the
00:39:10.360 numbers actually kind of move around and you wind up building a database in your mind of actually
00:39:14.280 what you're looking at. And so when you first start, you actually push the buttons and it's
00:39:17.860 like 60, 40 for the abdomen. And you actually know all these numbers. And then as you kind of go
00:39:22.240 through, you're like, nah, I just need to see what I need to see. What you said a moment ago,
00:39:25.980 it really brought back those memories of how horrible it looked if you tried to set the window to be
00:39:32.360 the entire plus minus 1000, you could appreciate nothing. And that sort of struck me as a metaphor
00:39:37.720 for life at times, which is like at a thousand feet, sometimes you can tell I'm looking at a
00:39:42.520 human, but that was about, that was about the limits of detection, but you could appreciate
00:39:46.900 so many different things by zeroing in on the capillaries of the lung, but you had to be in the
00:39:52.280 right resolution versus if you wanted to look and see if they actually had a fracture. People forget
00:39:56.600 CTs are great for bones, right? And we're going to talk about how MRI, for example, is less great
00:40:01.840 for bones. So now we've got the CT thing. So what we've established is that x-ray is a purely
00:40:08.340 anatomic study. There's nothing functional about it. As you go into CT by itself, it's also a very
00:40:13.920 anatomic study. You can add contrast to get even better information about the vasculature.
00:40:19.020 And you now have so much information that you can basically titrate or calibrate the window in which
00:40:27.380 you look into that collection of radiation and specify your tissues. CT scans are generally pretty
00:40:34.000 quick, right? People who are claustrophobic don't tend to struggle that much in a CT scanner, correct?
00:40:39.260 Exactly. And that's actually the real power of CT is the speed. So for example, in trauma settings,
00:40:43.880 that's what you want. Basically, if a patient's not doing well in a trauma, you want to put them
00:40:48.020 through the CT scanner as fast as possible to get the information out as fast as possible. And they're
00:40:52.260 very fast. So something that's even faster than CT and comes without at least one of its most
00:40:58.620 significant drawbacks, which is radiation, is ultrasound. So how does ultrasound work? Where does
00:41:05.560 it fit into this? And what are its limitations? The way ultrasound works is basically it's a high
00:41:11.640 frequency, so higher than what our ears can hear. And effectively, it's penetrating solid tissue.
00:41:17.460 So it's a high frequency sound wave versus an ionizing wave of energy.
00:41:23.140 Exactly. And so then it's actually going and every tissue interface, it actually reflects back.
00:41:28.060 So it's very much like an echo. So if you're standing in a mountain range and you yell out,
00:41:32.420 you actually hear the echo coming back. And you can actually, from that time, you can determine how
00:41:36.300 deep that tissue is. And so with ultrasound, we're just doing that very, very fast. And so at every
00:41:41.280 tissue interface or every mountain range, if we could, you actually hear that reflection coming back.
00:41:46.260 You actually are able to then composite that as a representative of how deep things are away from
00:41:51.840 you.
00:41:52.280 Now, there are animals that do this, right? Including some of our closest relatives, right?
00:41:58.000 They do. And as bats also do them, that's actually how they see.
00:42:01.480 And the bat's resolution on this is what compared to, say, a dolphin. I've read, and I feel like I read
00:42:07.540 this in the journal Science many years ago, so I'm almost assuredly not remembering this correctly,
00:42:11.780 that the resolution with which a whale or a dolphin could undergo sonography rivaled that of our finest
00:42:20.320 medical equipment. I mean, their ability to discern was remarkable. I found that amazing. And of course,
00:42:26.800 in part, that's because the medium through which they travel is water, as opposed to what the bat has
00:42:32.080 to do, which is go through this poorly, poorly dense air, right?
00:42:35.680 Exactly. So traveling through a different material actually makes a very good way to explain it,
00:42:40.700 because in the air, actually, ultrasound doesn't penetrate very far because it's this high frequency
00:42:45.420 and it just, you lose it because there's no reflection coming back. Whereas in more solid
00:42:49.900 material like water or even dense material like organs in the body, it actually reflects back
00:42:54.940 easier. And so it's actually that reflection that actually allows you to discern the different
00:42:58.980 tissue types based on how quickly it reflects back.
00:43:01.320 Now, ultrasound can't harm you, right? You don't have ionized. You could ultrasound yourself all day,
00:43:06.580 every day for the rest of your life, and you're not increasing your risk of cancer. Whereas if you
00:43:10.320 did a CT scan of yourself every month, you're going to be in trouble after several months.
00:43:15.720 Exactly.
00:43:16.420 The drawback of ultrasound is the resolution doesn't seem to be as high.
00:43:20.380 Right. With ultrasound, you're only looking at one slice, right? So you're only looking at one slice
00:43:24.440 in time, and you're basically kind of sweeping through an organ, trying to composite those slices
00:43:28.840 together in your brain to try and build that 3D model. Because like I said, our brain always wants
00:43:33.420 to build a 3D model. So with ultrasound, as you sweep through, you get one layer, then you get
00:43:37.400 another layer, then you get another layer, and then eventually that's composited together to see
00:43:41.280 what's going on.
00:43:41.880 An ultrasound also seems to really struggle when it encounters air inside the body. So if you're
00:43:48.660 trying to do an ultrasound of someone's aorta, but their bowel is in front of it, it becomes difficult
00:43:54.060 to see. For the same reason the bat can't really use high-frequency ultrasound to fly.
00:43:59.120 Exactly. And so that's why when, for example, you look at a female pelvis, you want their bladder
00:44:03.220 to be full. Because in their bladder being full of fluid, it actually acts as a nice window to allow
00:44:08.180 the ultrasound beam to pass right through to be able to see the uterus behind it.
00:44:11.640 I think any woman listening to this who's been pregnant, that's got to be one of their
00:44:15.580 most vexing parts of prenatal ultrasound, is they always had to sit there in a waiting room with a
00:44:21.040 full bladder waiting to have that ultrasound. And of course, that's why we like to do ultrasound
00:44:26.060 on a fetus, right? Is you're not causing any harm. I mean, certainly one thing I came to appreciate
00:44:31.300 in the hospital was the skill that was required on the part of the person doing it. So if you gave me
00:44:38.260 the best ultrasound device money could buy today, like you literally went and bought whatever
00:44:43.720 ultrasound was at the absolute limit of technology, and then you walked down to the local hospital here,
00:44:48.960 Vancouver general, and you grabbed just a middle of the road radiology ultrasound tech, someone who's
00:44:55.400 maybe been out of school for a year, and you gave him or her the worst ultrasound machine on the
00:45:02.080 market, there's no comparison who would be able to see more.
00:45:05.680 This is where skill and experience is invaluable. Basically also dealing with the difficult patient
00:45:11.400 body type is really critical and you can't replace that experience.
00:45:14.820 Now there's a special subset of ultrasound that we do on the heart. Where did that idea come about?
00:45:20.980 Who figured that idea out?
00:45:22.200 Again, the value was like once you could actually find like a nice window that would actually allow
00:45:25.660 you to miss the air in the lungs and actually kind of look at the heart, you realize that boy,
00:45:31.480 you can actually start to see this two-dimensional plane of the heart quite well. And as a result,
00:45:35.540 you can actually see where things were moving, such as the valves in the heart or the walls of the
00:45:39.660 heart. And then as well, you actually add something called Doppler, which is basically the frequency
00:45:44.720 bouncing off of blood vessel. If it's going or coming, the frequency is going to be different.
00:45:49.580 And so as a result, you can actually now start to see how blood is moving. And so that's what
00:45:54.680 echo does. And so it actually allows you to look at the heart in detail with a very, very thin window,
00:45:59.580 usually underneath the chest and around the lung.
00:46:02.540 Yeah. So anybody listening to this, who's had an echocardiogram, they know
00:46:05.940 that the person doing it is really pressing quite hard. It's somewhat uncomfortable for you,
00:46:11.860 the person getting the echo done. And the reason is they've got that jelly on you, which again is
00:46:17.180 doing everything to eliminate even a drop of air between the interface. And secondly, they're pushing
00:46:22.620 and they're grinding it in between the ribs and they want to get that view versus, so that's a
00:46:27.160 transthoracic echo where you're doing it over the chest. In surgery, often if we needed to look at
00:46:33.240 the heart, you would have, the anesthesiologist would actually put the echocardiogram in the
00:46:36.940 esophagus and you get an even better view of the heart. The esophagus sits right underneath it and
00:46:42.920 there's nothing in between. And it's a beautiful view. And the patient, obviously, because they're
00:46:47.080 asleep, they don't have to worry about having this huge probe stuck in their esophagus.
00:46:51.760 Right. And because you're closer to the organ you want to see being the heart,
00:46:54.520 the detail is going to be fantastic. Because one of the other things with ultrasound is that
00:46:58.500 the deeper you go, the beam effectively fans out and gets thinner and thinner. So you actually get
00:47:03.480 less sort of detail on the edges. Whereas right in the center, right underneath the probe is where
00:47:07.680 your maximum amount of detail is going to be. So by having it right in the esophagus, which is right
00:47:12.120 beside the heart, you're going to get fantastic detail. As important as the CT scanner was in trauma,
00:47:17.360 the ultrasound was actually the most important radiographic tool we had in trauma. And that was
00:47:24.380 the one thing that even the surgical residents needed to know how to do. And it was called a
00:47:29.520 fast ultrasound. There was an algorithm for this because in a busy trauma center like Hopkins,
00:47:35.220 you're going to see trauma so often, penetrating trauma in particular, where you have to know,
00:47:40.760 does this person need to go up to surgery? Is there fluid in the abdominal cavity? That's generally
00:47:46.240 one of the things you care about. You certainly also care if there's fluid around the pericardium,
00:47:50.740 this non-stretchy sac that surrounds the heart. These are surgical emergencies, especially
00:47:55.880 fluid around the pericardium. So I think sometime in our second year of residency, we would go off
00:48:01.380 and do this course where on pigs, we would have to practice this over and over again until you learn
00:48:06.500 the four places that you were looking for fluid inside the abdomen. I guess we got pretty good at it.
00:48:12.340 I think I got okay at it, but I, I still always felt like a little nervous when push came to shove
00:48:19.320 because I always felt like I wish I could go and spend a year just being an ultrasound tech
00:48:23.980 to really, really dial this in because the stakes are so high, especially if you miss
00:48:29.500 the slight amount of fluid in the pericardium, that's a lethal injury.
00:48:33.200 And one of the real tricks as well is that depending on the composition of the fluid,
00:48:37.260 there's like frank blood or coagulating blood. It can be really tricky to actually pick it out.
00:48:41.280 And so a lot of times you'd actually see that fast ultrasound would be done.
00:48:44.380 And if people weren't a hundred percent confident that there's a problem or not a problem,
00:48:49.100 they'd go straight to CT scan because you just couldn't make that error.
00:48:52.140 And that happens time and time again.
00:48:54.120 Yeah. And it's funny. One of the last traumas I was ever involved in as a resident was just one
00:48:59.560 of those cases where the patient came in and he was responsive. He had the tiniest,
00:49:05.520 tiniest stab wound. So less than a centimeter wide under the xiphoid.
00:49:10.760 That's it. So this is a guy who walks in who has a sub centimeter sub xiphoid incision. I mean,
00:49:17.060 it could have been a shaving cut, but he's been stabbed and he's more or less seems pretty normal.
00:49:24.560 Vital signs are more or less what you would expect. When I lay him down and do this ultrasound
00:49:30.160 of his heart, it really looks like there's something there, but I can't quite figure it out.
00:49:35.560 And now the question is, well, he's obviously too responsive to warrant cutting his chest open,
00:49:40.720 which was what you would do in the emergency situation. So you have to do the CT scan. But
00:49:45.940 of course the risk in the CT scanner is as fast as the CT scanner is, he is still laying down on a
00:49:53.200 scanner, potentially ready to have a cardiac arrest for at least a minute and a half. And usually what
00:50:00.460 would happen is I don't recall in this case, but a lot of times, if you're going to go through the
00:50:03.600 trouble of doing that, you're going to do a contrast CT scan as well. You're not just going to do what
00:50:08.200 we would call a dry scan with no contrast. So now you've got the fumbling around of getting the iodine
00:50:13.680 machine hooked up to him, et cetera, et cetera. And Eddie Cornwell, who was the chairman of surgery at
00:50:18.540 Hopkins, he's now the chairman of surgery at Howard and just an incredible human being. I remember one of
00:50:23.840 the things that he told us when we were junior residents is beware of the patient who gets wildly
00:50:30.200 anxious when you lay them down. And sure enough, when we go and lay this guy down in the scanner,
00:50:35.800 he just starts freaking out. And when you sat him up, he sort of calmed down a little bit.
00:50:42.720 It was do not pass go, do not collect $200 and took him to the OR, opened him up immediately. And sure
00:50:47.700 enough, that knife had actually hit his pulmonary vein. And so that pulmonary vein was bleeding into his
00:50:54.320 pericardium. And so he would have had a cardiac tamponade if we'd left him on that table.
00:50:58.060 And amazingly, that patient went home three days later.
00:51:01.360 Yeah, no, exactly. And you can see like the power of the clinical skill as well as like just the
00:51:05.700 basic imaging, right? The power of imaging plus clinical is pretty much where medicine is right
00:51:11.940 now and how we actually are able to diagnose things quickly and efficiently.
00:51:15.140 So we've talked about two technologies that most women are very familiar with when it comes to
00:51:19.700 breast cancer, which is of the cancers where screening is done vis-a-vis imaging technology,
00:51:26.340 breast cancer is head and shoulders above the others in terms of the frequency and ubiquity of
00:51:30.520 the scan. So let's talk a little bit about, because you've already explained what an ultrasound and an
00:51:35.000 x-ray is. So now explain what mammography is and why we would sometimes say mammography is
00:51:41.080 sufficient versus insufficient. And why do some women get told, well, you also need an ultrasound?
00:51:45.640 Right. So basically mammography is a lower attenuation x-ray. We're actually taking x-ray,
00:51:51.320 but a weaker strength of it because we never have to penetrate bone. And actually now it shines to
00:51:55.980 the breast tissue, which is all soft tissue. And so one of the things that actually is maybe
00:52:00.280 stepping back is to actually kind of look at breast tissue in particular. So breast tissue is composed
00:52:05.720 of normal subcutaneous tissue, which is mainly fat and as well as glandular tissue. And so when women
00:52:11.320 are in their childbearing age, it's almost all glandular tissue to produce milk for eventually feeding
00:52:16.160 a baby. And as women then go through menopause, that glandular tissue can invariably involute. So
00:52:22.000 it's one of these things, you don't use it, it gets replaced with fat. But in some women,
00:52:25.620 it actually doesn't get replaced with fat. And that is what we call the dense breast tissue.
00:52:30.900 So mammograms are very, very good at shining through fat. And it actually allows you to see
00:52:34.920 very, very simple things like calcification in fat, because they are just so dense and it actually
00:52:39.540 just stands out. Whereas in glandular tissue, sometimes that photon of low energy x-ray doesn't
00:52:45.960 make it through. And as a result, the tissue is very, very hard to see through. And that's what
00:52:50.300 we call the dense breast tissue. And the reason it's hard to see through is because of all that
00:52:54.440 glandular tissue that in some women over menopause or even older, they just retain. Nobody really
00:52:59.960 knows why they retain that extra glandular tissue, why in some women it gets replaced with fat,
00:53:04.640 in other women it doesn't. We don't know why. And so many states, and I think they're actually over 38
00:53:09.520 and possibly soon to become federal law in the United States, is going to require that the very first line
00:53:14.480 on a mammogram report is going to be that the women's breast tissue is dense, limiting mammographic
00:53:20.780 sensitivity, or the breast tissue is almost entirely fat, in which case mammograms are helpful.
00:53:26.460 Because that actually will really allow women to determine, was this test good enough? And so for
00:53:31.900 women who actually have dense breast tissue, so they, for some reason, if they're postmenopausal or if
00:53:36.620 they're premenopausal in their childbearing age, they still have a lot of glandular tissue. That means a
00:53:41.140 mammogram might not be enough, and therefore they need another second imaging modality to look through
00:53:45.840 the tissue. And that's where ultrasound comes in. And as well as MRI would come in as well, to be able
00:53:50.660 to see through that dense glandular tissue that the mammogram can't see through. Now, the last time I
00:53:55.740 looked, and these data could be, they could just be simply dated, but I think directionally this is
00:53:59.920 right. A mammogram had a sensitivity of about 80, call it 84, 85%, and a specificity of about 90,
00:54:10.520 91%. Does that still sound about right to you? It depends, actually. Yeah, that was like all comers
00:54:15.340 was the point I was going to make, which is it becomes almost impossible to interpret what that
00:54:20.540 means, because what you need to know is, what if I had a thousand women that looked exactly like the
00:54:27.360 women I'm scanning right now? Exactly. And so that's where it actually becomes really critical
00:54:31.120 in the fact that depending on the breast density, and that's why it's important for women to know
00:54:35.600 what that is, you're going to know how helpful the mammogram is or may not be. But one of the other
00:54:40.800 things that becomes actually very, very powerful in the mammogram is to actually use comparison over
00:54:45.200 time. So that's why they recommend screening intervals of either one or two years. It's a matter of
00:54:50.940 academic debate. And because if you actually have like a mammogram taken, and then let's say two years
00:54:56.680 later, you do another one, it's actually far more sensitive to see that subtle change over time
00:55:01.640 than it is to actually look at an individual mammogram all on its own. So a single mammogram
00:55:05.880 on a dense woman, its sensitivity is about 55%. It's actually quite poor. Whereas on a woman who
00:55:11.480 actually has fatty tissue, it's very high. How high? It can actually be over 95%. So let me explain what
00:55:17.540 sensitivity and specificity means so that a person understands what this is about. Let's just use the
00:55:22.320 numbers 80 and 90 because those are generally accepted as an aggregate. So when we say a mammogram
00:55:28.500 has an 80% sensitivity, here's what we mean. If there are a hundred women who have breast cancer,
00:55:35.680 so there's a hundred women and we absolutely know that they have breast cancer and we subject them to
00:55:39.780 a mammogram, 80 of them will test positive. 80 of them will have a true positive and 20 of them
00:55:47.720 will test falsely negative. So the sensitivity is the true positive rate over the true positives plus
00:55:55.960 the false negatives. Correct? Exactly. So the higher the sensitivity, the less likely you are to take
00:56:05.840 someone who has the cancer and miss them. That's the juice on sensitivity. Let's now talk about
00:56:11.880 specificity. So mammography, a moment ago you gave a staggeringly sad example, so we'll come back to that.
00:56:17.580 But let's use the better one, right? Let's say 90%. So now what does it mean to have 90%
00:56:22.780 specificity? So that means you take a hundred women who we absolutely know do not have breast cancer
00:56:30.320 and you scan them. 90 of them will correctly identify as not having breast cancer. 10 of them
00:56:38.520 will incorrectly identify as having breast cancer. So 10 will be false positives. 90 will be true
00:56:46.440 negatives. So the sensitivity is the number of true negatives over the true negatives plus the
00:56:53.660 false positives. And so the example you gave a moment ago is if you have a woman whose breasts are
00:56:59.580 very fatty, not glandular, therefore she's the poster child for mammography, you're driving that
00:57:06.780 specificity up, which means you are reducing the number of false positives. But in the example you gave
00:57:14.840 earlier, which is a woman who might have very, very dense breast tissue, imagine what it means to
00:57:20.340 take a hundred women who have very, very dense breast tissue and drive your specificity down to 50%.
00:57:27.360 That means on a given day, half the women that walk into your clinic are going to be told they have
00:57:34.660 cancer if they don't. Exactly. So it's like flipping a coin. And by the way, one of the greatest examples
00:57:39.980 of this, I mean, I attribute it to Bob Kaplan, but maybe he heard it somewhere else, but I love it is
00:57:45.220 you can make a test that is a hundred percent sensitive. If you're willing to have zero percent
00:57:50.640 specificity and vice versa. For example, you could send a letter. You could have a little card that
00:57:56.620 says you have cancer and you show it to every single person you meet. You have a hundred percent
00:58:01.940 sensitivity. Right? Right. You will never have a false negative. The problem is that's so clinically
00:58:09.420 useless because you have no specificity. And similarly, you could have a little magic card
00:58:14.500 that you show everyone you ever meet for the rest of your life that says you do not have cancer.
00:58:18.180 Guess what? You have a 100% specific test. It just has zero sensitivity. So it's as useful as a warm
00:58:24.800 bucket of hamster vomit. And so it's this trade-off between sensitivity and specificity, which I'm teeing
00:58:29.960 this up because I know we're going to come and talk about this when we get into the more advanced MRI
00:58:33.440 stuff. But the example of mammography is amazing to me because it makes you realize you can't just
00:58:40.140 rely on one test, especially when that test has such low sensitivity and specificity depending on the
00:58:45.840 individual. Exactly. And I think that that's the real important lesson is that it's actually very
00:58:49.780 individually tailored, right? And so if you have one test and you don't know what your fingerprint or
00:58:55.700 what the tissue that your breast is made of, you really have no idea what you're looking for.
00:59:00.380 So you always need the one to kind of find out, is this good enough? People always talk about
00:59:04.440 machine learning and AI and how it invariably it has to infiltrate medicine. And it seems to me that
00:59:09.240 one of the best places for it to do so is in at least comparative radiology. So given the ubiquity
00:59:17.100 of mammograms, hopefully every woman above a certain age in the United States, Canada is getting
00:59:22.840 regular mammography. There's no shortage of data. Are there companies out there that are working on
00:59:28.880 basically doing that once you have a baseline, which would be almost impossible for a machine to
00:59:34.040 read, but once you have that baseline longitudinally comparing it? There are actually a lot of
00:59:38.800 companies that are actually doing that. And, and even in some States that are actually using machine
00:59:44.280 learning techniques to actually help the radiologist and they actually can be used as even a second
00:59:48.420 reader. There are a fair number of companies working on that, but it's not perfect.
00:59:52.060 What do you think that could improve the sensitivities and specificities of mammography
00:59:56.820 to? I mean, can we get to the point where, I don't know. I mean, most people would say you've
01:00:01.420 got to be North of 97, 98% on both to really feel confident.
01:00:07.320 I think that's a pretty high target to achieve. And the reason that would be is just because of the
01:00:11.300 way the tests are done and the individual variability of people. It's going to be tough. Can machine
01:00:15.720 learning get that good? It'll take a while. It's going to need volumes and volumes of data that's
01:00:19.580 actually reproduced the exact same way. And I think that's the biggest problem is because we're
01:00:23.200 unique. The way the breast is compressed, the way everything is done when a mammogram is taken is
01:00:28.320 somewhat different each time. So the amount of coverage is a little bit different each time.
01:00:33.220 It's possible. Are we there yet? No, we're nowhere near close, but we're getting better.
01:00:37.940 And that's also one of the challenges that we have when we look at the data on mammography is it's so
01:00:44.240 backwards looking. And so if you want to look at the most comprehensive study of mammography and breast
01:00:51.780 cancer screening, by definition, you are looking at a trial that was enrolling patients 15 to 20 years
01:00:57.720 ago. And therefore you have to be able to say, well, how relevant is the technology that was being used
01:01:04.940 then relative to today? And in the case of mammography, it shouldn't be changing that much,
01:01:09.580 but I mean, things do get better. I mean, we're reading pure digital now. We have much better
01:01:15.100 capacity to read even an x-ray than we did 20 years ago, don't we? We do. And basically now what's
01:01:19.820 actually happening is we're actually doing a fluoroscopic version of a mammogram where we're
01:01:23.580 basically sort of trying to slice through this three-dimensional object and actually get the
01:01:27.920 detail of it a three-dimensional layer. Whereas before the mammogram were typically just like the
01:01:33.000 chest x-ray was done, two different views compositing that three-dimensional picture together. So that
01:01:39.460 three-dimensional view of the mammogram is actually better than it was. Now there's something else that
01:01:44.000 I've never actually seen done clinically, but I've read about it called MBI, molecular breast imaging.
01:01:50.020 Is that used any longer? And what is it? The reason it came across my radar was many years ago when I was
01:01:56.740 just trying to get the landscape on ionizing radiation, this came up as a test that was done as a
01:02:02.640 follow-up to a mammogram. But I thought there must be a typo based on how much, it had like something
01:02:07.500 like 20 millisieverts of radiation. I mean, it was 40% of your annual radiation limit.
01:02:13.200 What that is now, that's a functional test. So in the realm of nuclear medicine. And so what that is
01:02:18.700 doing is we're actually taking radioactive material and then we're actually injecting it into the body.
01:02:22.780 And so tissues that actually have increased mitochondria actually concentrate this
01:02:28.080 radio tracer. And so that typically happens in breast cancer. So it's actually used with a
01:02:33.740 radio tracer called Sestamibi. You've heard of this Mibi scan, which is where we actually inject this
01:02:38.340 into the heart. And we actually look at whether or not the heart is being properly perfused.
01:02:43.000 And so areas that aren't being perfused, so therefore the muscle is not alive, basically don't take up the
01:02:49.120 radio tracer. Whereas muscle that is alive does take up the radio tracer. And that muscle that's alive,
01:02:54.240 that's moving has a very high mitochondrial rate. So therefore it actually concentrates
01:02:58.080 this material. So breast cancer was actually doing a very similar thing. They'd actually have a high
01:03:03.440 metabolism. And so this tissue would actually concentrate or this radio tracer would concentrate
01:03:07.980 in that tissue. So that was the MPI exam for breast. Is that test still done? Rarely, but it can be done
01:03:13.420 in women who actually have very, very dense breast tissue and you actually need to see what's going on.
01:03:16.820 It can be done, but a lot of it's actually been replaced with positron emission tomography scans.
01:03:21.720 So right now, how many women, young women, if we just say, because the young women are going to
01:03:26.900 be more likely to have dense breast tissue, do we have a sense of what percentage of them
01:03:30.140 really are being uncovered? Meaning they're not getting adequate sort of surveillance with
01:03:35.420 just mammography and would require at least ultrasound. Is that a third of women? I mean,
01:03:39.100 do we have a sense of what that number is?
01:03:40.440 Depending on the jurisdiction. So the guideline for when you actually start screening for mammography
01:03:44.760 can either be for the age of 40 and higher or 50 and higher. Each jurisdiction is a little bit
01:03:49.260 different. So what that means is that basically anybody under the age of 40, unless you have a
01:03:53.700 family history of somebody having breast cancer at an early age, they're not getting screened at all.
01:03:58.280 So everything we've talked about from a technology standpoint, in some ways,
01:04:02.640 pales in comparison to what we're about to talk about, which is about as complicated a set of
01:04:08.360 physics as you're going to find within the walls of a hospital, right? I mean, it doesn't get a lot
01:04:12.240 more complicated than an MRI, does it?
01:04:14.040 No, it doesn't. It's really an engineer's delight.
01:04:16.920 Yeah. And I certainly, again, thinking back to my brief six weeks of doing radiology,
01:04:22.060 I feel like more of my notes were scribbling down an explanation of how this thing worked
01:04:28.460 than anything else. So let's go back to the beginning. Who the heck thought of this?
01:04:33.320 There were actually three people actually thought about it, but the Mansfield is actually one of the
01:04:37.620 main creators of it in UK. And so the MRI machine really, it's actually quite an amazing tool. And
01:04:44.120 it actually wasn't initially developed for imaging. It was actually just sort of developed on a bench
01:04:48.100 top where they're actually just kind of looking to see what the effect of electromagnetic waves does
01:04:53.220 to anything. And somebody wind up sticking tissue in it saying, hey, look, it's like we can actually,
01:04:58.320 what goes in one side comes out a little bit differently on the other side. And as a result,
01:05:02.220 we can actually determine what that composition of material was.
01:05:05.180 So does that mean like the NMR that we were looking at when we did organic chemistry was
01:05:10.740 really the precursor to the MRI that we're sitting outside of right now, listening to it hum?
01:05:15.880 It's the exact same device. The NMR basically is just a two-dimensional version of an MRI,
01:05:21.700 which is three dimensions because our brain likes three dimensions.
01:05:24.240 So let's go back to organic chemistry. So again, we'll link to a picture of an NMR spec so that people
01:05:31.820 can see what we're talking about. But I, I guess there's also no easy way around this, right? I
01:05:36.000 think you have to sort of roll your sleeves up a little bit on physics to understand how an MRI works.
01:05:40.900 There is no, I'm sure there's a kid's book out there waiting to be written on the topic,
01:05:45.460 which would be amazing, but it's pretty tough. So you take a molecule like alcohol. Okay. So it's got
01:05:54.140 these two carbons that are joined. The first carbon has three hydrogens around it. The next carbon
01:06:00.460 has a hydrogen and a hydrogen, but then instead of the third hydrogen, it gets an oxygen, which is
01:06:06.240 bound to a hydrogen. That is the stuff that people drink and get drunk on. Now put that into a nuclear
01:06:13.320 magnetic resonance machine and you're going to see different peaks, right? It's going to show you that
01:06:19.300 there is a methyl group somewhere. It's going to say, it can't tell you what it sees, but it tells you
01:06:24.560 that there's a carbon bound to three hydrogens, right? Right. How does it do that?
01:06:30.840 Perhaps I might actually take up the challenge of a children's book. My problem is I dislike writing,
01:06:35.380 but maybe for children, I'll be okay. The way it actually does it is actually quite fascinating.
01:06:39.580 And it's actually relatively simple. So what it actually does is the hydrogen in particular. So
01:06:46.860 we're going to sort of fixate on hydrogen because that's the atom that we're really interested in.
01:06:50.800 And I'm just going to say one thing because you're going to do this anyway, and I just want to preface
01:06:54.620 it. You're going to use hydrogen and proton interchangeably, aren't you? I will. Can you
01:06:59.140 just tell someone why you're going to use hydrogen and proton interchangeably? Sure. So the atom basically
01:07:04.460 of the hydrogen is you have one proton and one electron. And in the hydrogen proton, we don't really
01:07:10.800 care about the electron. It just sort of disappears. So the hydrogen, I guess, nucleus is a proton.
01:07:16.460 And it has no neutron. Its mass is one. Its mass is determined by the one and only proton it carries,
01:07:23.020 correct? Exactly. Yeah. Okay. So now hydrogen and proton, they're the same thing for the purpose of
01:07:27.260 this discussion. Exactly. So when we look at the NMR, so you actually have hydrogen bound to an oxygen
01:07:32.640 or hydrogen bound to a carbon. And so the behavior of that nucleus is going to be a little different.
01:07:38.000 So there's basically a magnet that's creating a field. And somehow through that, we can see
01:07:44.740 how the hydrogen is bonded to either the oxygen or the carbon in the ethanol molecule.
01:07:51.300 Right. So we were talking about the NMR. And so what the NMR does is that it really is a hydrogen
01:07:56.140 or proton imager or actually just detector. And so the way the magnetic field of hydrogen behaves,
01:08:03.260 if it's attached to either the oxygen and OH of alcohol or the CH3 of carbon is completely different.
01:08:10.500 And it actually gives off a different wavelength. And so as a result, that's how we're actually able
01:08:15.000 to get this, what we call NMR spectra. And so what happened is that from there, there's a person named
01:08:21.120 Damadian, who many consider to be the father of MRI. He actually said, well, you know, look,
01:08:27.180 if we can actually take what Mansfield and Lauterberg did on a benchtop, can we actually put a human in it
01:08:31.880 and actually start to see the soft tissue? Because we know that our body's composed of roughly 70% water.
01:08:36.780 There's a lot of hydrogen on fats. So can we see that frequency difference? We can see it on a
01:08:41.420 benchtop, but what about in people? So we have more hydrogen in us. If we were just going to count
01:08:45.580 up the atoms in us, hydrogen wins all day long. Because as you said, if we're 70% water, that's
01:08:50.500 two to one hydrogen over oxygen there. And then all the fat that's in us is all the hydrogen to the
01:08:56.560 carbon there. And there's basically hydrogen in protein as well. I mean, so if you have a hydrogen
01:09:02.920 detector, that's basically the way you would describe an MRI.
01:09:07.080 An MRI is exactly that. It's a hydrogen imager. So basically we're looking at hydrogen nuclei,
01:09:12.700 which is a proton. And so a lot of times as well, people actually talk about proton spectroscopy,
01:09:18.220 which is NMR. An MRI is just basically a simple hydrogen imager.
01:09:22.880 So I think anyone who's had an MRI knows that there's a magnet involved and it's generally a
01:09:28.760 non-trivial magnet. Some people have probably heard of some of these real horror stories where
01:09:32.860 accidentally in the hospital, a patient's wheeled in and there's a loose oxygen tank under the gurney
01:09:38.300 that's wheeling them in and it goes flying across the room and hits somebody and can kill someone.
01:09:42.700 So how strong is the magnet and why does it need to be so strong?
01:09:46.740 Right. So the magnets, they come in different flavors. So typically it's regarded as a Tesla.
01:09:51.060 Tesla. And so Tesla is roughly 10,000 Gauss. And so a Gauss is effectively what the North Pole can
01:09:58.580 produce. And it's actually the typical measurement for most magnets. But when we actually get into the
01:10:03.580 MRI field, it becomes so much stronger. And the reason we actually kind of need that high Tesla
01:10:08.540 field strength is because we're actually taking hydrogen, which is typically not that magnetic
01:10:14.360 compared to like a magnet that we think about like a bar magnet. And what we're trying to do is
01:10:18.740 we're actually trying to orient that little dipole of the water molecule or fat molecule a certain
01:10:25.160 direction. And that's what the static field does. And that's why it has to be so strong. So they come
01:10:29.700 in flavors 1.5 Tesla, 3 Tesla, which is double the strength, 7 Tesla. And so the higher the Tesla they
01:10:37.520 go, the more it's actually able to pull all of the hydrogens and orient them in one direction.
01:10:42.400 Because as we're sitting here or anywhere, normally our hydrogen molecules are on water.
01:10:46.920 We're just kind of bouncing around randomly, kind of pointing at any which direction. And then
01:10:50.940 there is no kind of magnetic component to us. The hydrogens are spinning around just based on
01:10:56.980 Brownian motion. And so when you actually go into a magnet, that strong magnetic field,
01:11:01.640 these hydrogens basically kind of turn and orient themselves in that direction.
01:11:06.000 And so that's what actually provides the initial basis for an MRI. And that's why, contrary to what
01:11:10.740 we see on TV, that magnet is always on. You can never turn it off. Because that magnetic field
01:11:16.160 always has to be there in order to provide that orientation. And as well, the way it works is you
01:11:22.420 actually have a superconducting wire that's actually running just above absolute zero degrees
01:11:26.740 Kelvin. So it's roughly two Kelvin. And so you can't turn that off. This is superconducting wire.
01:11:33.940 It has like pumps that are pumping all the time to keep it that cold. So that when you actually put
01:11:38.180 an electric field in like a loop of wire, that electric field is what actually generates the
01:11:43.160 magnetic field in a perpendicular direction. So you have a generator that backs up if you lose power,
01:11:48.760 which invariably you're going to lose at some point. Exactly. You have to have that backup power
01:11:52.580 to always keep this pump moving this liquid helium that's surrounding the wires to always keep that
01:11:57.600 liquid helium floating around, circulating around that wire to keep that wire near absolute zero Kelvin.
01:12:02.480 Now, if we were to walk in the scanner today, and everyone can sort of picture this,
01:12:05.960 there's a bed running through a donut. What is the direction right now that that magnet is being
01:12:11.900 oriented? The donut. So that's where that loop of superconducting wire is sitting in. And so
01:12:16.800 depending on how it's put in, most of the time, the north will actually face away from the control
01:12:21.380 center. And that's the direction of north. Got it. And if I recall, there's like a right hand rule
01:12:26.200 on this, isn't there? There is. Very nice. So it can tell you which way the power in the coil is going.
01:12:31.460 And it's actually going, I guess, if you're looking from the foot of the bed, it's actually going in a
01:12:35.780 clockwise circle. And that's the right hand rule. The right hand rule. It's pointing in the axis. Okay.
01:12:40.220 Now, aside from the fact, let's pretend we weren't wearing anything metal. If you walked into a room
01:12:46.460 where there was a 10 or a 20 Tesla magnet, would you feel anything? And would it do anything to you
01:12:53.480 that is harmful? The actual magnetic field won't do that much. Now, when you get very, very strong to
01:12:59.400 a moving magnetic field, you can actually start to feel it because it can actually trigger your nerve
01:13:04.740 impulses to start moving. So sometimes people actually, if the magnetic field is too strong,
01:13:09.560 they'll actually get twitching. And sometimes people who are actually around magnets all the
01:13:13.940 time, they actually become more and more attuned to this type of a thing. And so if you have MRI
01:13:18.300 technologists or people who are working with the high fields all the time, they can say, you know,
01:13:21.760 when I go to the head of the magnet or like the north side, I actually kind of feel something
01:13:27.320 pulling. And then sometimes people describe getting temporary headaches. And as soon as they step away
01:13:32.620 from the field, it all goes away. Usually when patients ask me if there are any side effects
01:13:36.860 or harm of an MRI, I mean, our lib answer is to say, no, no, no, no, no, especially with a
01:13:41.640 non-contrast. Like if there's, I mean, not that the risk of gadolinium is high, but if you're just
01:13:45.980 having a dry MRI, you say nothing, nothing, nothing. But I actually had a patient who had very, very,
01:13:50.860 very severe migraine headaches. And she actually had a migraine triggered by an MRI. And I truly believe
01:13:56.580 that wasn't just a coincidence. I mean, I think her headaches were so severe. So, so I now sort of
01:14:00.780 always couched my response as there's virtually no short-term or long-term consequence that can
01:14:06.080 come from an MRI, but at least in the case of that person, you could trigger a headache.
01:14:10.420 You can, because what it does is it can actually stimulate the nervous response. And depending on
01:14:14.540 how strong the field is. So for example, if you were to do a seven Tesla magnet, you're definitely
01:14:19.380 going to notice it. And as a result, I'll tell people, look, you can't be in this too long because
01:14:23.740 of the fact that you're actually going to stimulate. So I remember going back to learning about this.
01:14:28.180 One of the other things that sort of strikes anybody who's had an MRI is they take a long time. So why
01:14:34.060 is it that if you wanted to get an MRI, let's nevermind whole body, which we'll come to, but
01:14:38.600 you just want to get an MRI of the abdomen that could easily take 40 minutes. Whereas a CT scan of
01:14:44.520 the abdomen can take two minutes. Yeah. And it's basically the way the images are acquired to
01:14:49.220 completely different mechanism. So if we go back and talk about the x-ray, it's basically like a single
01:14:53.620 flash. We're actually looking through everything. The CT is basically this x-ray that's
01:14:58.140 constantly on spinning around and basically sort of circulating around you. Whereas the MRI behaves
01:15:04.040 completely differently. And during the period of time of that acquisition, what it's doing is
01:15:08.760 everything that's inside the center of that donut is being pulled in a certain direction, all the
01:15:12.780 hydrogens on your water and fat. And then the loud part of the MRI is actually a temporary magnetic
01:15:18.540 field, which is countering that static field. And so it's actually now pulling all the hydrogens
01:15:24.280 in the opposite direction. And then in that opposite direction, it actually turns off.
01:15:28.580 And then the hydrogens reorient to where they were in that static field. And as they reorient,
01:15:33.420 they actually give off a different frequency. And that different frequency takes a while to gather.
01:15:37.960 And that's what we call the TR or repetition time or the TE of the echo time. And that you can't speed
01:15:44.100 up. So let's talk about TR and TE because it's the TR and the TE that determine what sequence you're
01:15:50.280 looking at. So again, I think the average person probably won't recognize these terms, but certainly
01:15:55.380 anyone in the medical profession will know the difference between a T1 weighted versus a T2
01:16:01.620 weighted image versus a spin versus an echo versus all of these things. So let's just talk about the
01:16:07.540 difference between TR, that repetition pulse time, and then TE. Is TE the time it takes to relax back to
01:16:14.880 its original position. So just discussing TR and TE, how do they differ in acquiring a T1 weighted image,
01:16:23.120 which is the one that's really anatomically beautiful. It's the closest thing you see to,
01:16:28.280 wow, I know what I'm looking at and I'm not a radiologist versus the T2 weighted image, which
01:16:32.980 seems to highlight water more. So things that are water look more white, but it doesn't have the
01:16:39.620 anatomic resolution. How would you differentiate those?
01:16:42.300 Right. So the simplest thing to do, and it's actually quite fascinating, is I went through
01:16:45.540 residency. People are always sort of stunned with, is this a T1 image or a T2 image? And went
01:16:51.340 through all that and it was kind of like, sort of a bit obscure. And then when they started to do MRI
01:16:56.260 much more, it's like it became actually pretty simple. On the T1 image, we actually see nothing but
01:17:02.040 fat. So fat gives a lot of signal, which is what makes it nice and bright. So we see a single element,
01:17:07.400 or I guess a single element that the hydrogen would be bonded to that we're looking at.
01:17:11.540 Whereas a T2, we're actually now seeing two elements. We're seeing fat and water. And so
01:17:17.300 those two elements are actually coming off at different frequencies from the MRI machine.
01:17:21.860 And you have to wait a longer echo time to be able to pick up the water because it
01:17:26.500 returns back to normal much more slowly than the fat does. So that's our T2.
01:17:31.400 The T2 weighted images take longer to acquire because the TE is long because you have to wait
01:17:38.580 to get both fat and water. What's the difference in the TR between the T1 and T2?
01:17:43.760 It's all going to be entirely dependent on the machine. So you actually have to customize those
01:17:47.220 parameters for every single machine. And so that actually kind of takes a while to actually kind
01:17:51.520 of go and calibrate and kind of get used to what your eyes are used to seeing. And it's also going to
01:17:55.960 be dependent on the signal, the overall magnetic field as was overall signal to noise for that
01:18:01.420 coil set that you're using. So each one has to be effectively tuned.
01:18:05.580 And then what does it mean when you have these other things that come out and God,
01:18:09.480 it's been so long since I've done it that I don't even remember when we would look at spin,
01:18:13.660 spin, echo, flare, all of these. I vaguely remember all of these other sequences we would order.
01:18:19.280 I don't actually recall what they were. Give us a brief rundown of that.
01:18:22.420 One of the things that MRI absolutely loves is just the different acronyms for everything.
01:18:25.960 It's almost like whoever can come up with the coolest acronym wins like lava and all these
01:18:32.720 other things. But effectively, there's three main categories of MRI sequencing. One is what we'll
01:18:39.340 call conventional. So conventional spin echo. And so that's basically just waiting as long as you can
01:18:44.040 for the hydrogen to completely relax and give off both its water and fat signal. And then we have
01:18:50.100 what's called gradient imaging. And so that's actually, you're not waiting for it to completely
01:18:53.840 return back to normal, but somewhere in the middle, you're actually kind of repulsing again. So you're
01:18:58.780 basically hearing that noise of the machine turning back on and saying, you know, we're not going to
01:19:02.900 wait to completely relax. We're going to fire up again.
01:19:05.500 And just give us a sense of the actual time. How many milliseconds, if you're trying to get a T2
01:19:10.520 signal and you're waiting for that full relaxation, how many milliseconds is that directionally?
01:19:15.600 It's actually going to be, it can be up as high as like 60 milliseconds or even longer for some of
01:19:20.640 them. Okay. And when you do these gradient-based tests where you're going to repulse, how quickly
01:19:26.420 are you repulsing? You can actually repulse in like two milliseconds or even faster. And then
01:19:31.980 there's actually the third category, which is actually called EPI or echo planar imaging.
01:19:36.640 And this is actually amazing. So this part actually allows you not just to be looking at
01:19:41.140 a single slice of a person, but you're actually going and you're actually now running
01:19:46.320 multiple slices simultaneously where you're actually putting two different fields on the
01:19:53.040 person at the same time. And so as a result, and it kind of gets complicated because we use the word
01:19:58.400 gradient all the time. And so what a gradient basically means, it's effective like a ramp from
01:20:03.440 a low number to a high number. And so if I was kind of looking at you and I sort of said, we're going to
01:20:07.880 start the image from your top down. First, we're going to put a gradient on from top to bottom.
01:20:12.380 So it's going to be a little bit of a higher frequency at the top, a little bit of a lower
01:20:15.640 frequency, lower down. And then we're actually also going to look at phase from right to left.
01:20:20.560 And depending on how your body's oriented and where the blood flow is going to be, we're going
01:20:23.880 to look at phase and frequency, which now bring us into the realm of a Fourier transform. So these are
01:20:29.480 now with the pulses, we're effectively looking at all these repetitive sine waves.
01:20:34.040 And we're actually plotting that in frequency and phase domain.
01:20:39.120 Right. And for the listener, we always talk that Laplace was only half the man Fourier was.
01:20:44.580 That's like the nerdiest math joke I'm going to tell today. All kidding aside,
01:20:48.960 how does one get into MRI radiology without a background in mathematics and physics? It seems
01:20:54.520 it would be impossible.
01:20:56.140 It's a struggle. I can actually remember with the group of residents that I was with training and
01:21:00.740 great people that we actually had a physicist come in and was talking about MRI physics for
01:21:05.680 a couple of days and trying to teach us all. And I thought, boy, this guy's really watering it down.
01:21:10.060 I can barely hang on to what this guy's saying. Then I kind of looked and talked to all my colleagues
01:21:14.500 and they were just bewildered. They had no idea what he was talking about. Because as far as an
01:21:19.320 engineer is concerned, it's like Fourier domain. It's kind of like, that's sort of like the alphabet.
01:21:24.080 Yeah. That's our bread and butter back in the day.
01:21:25.640 Yeah. The difference with the MRI is that you start in this Fourier domain. And because we're
01:21:30.180 a three-dimensional object, when you're looking at a two-dimensional plane, that's the Fourier
01:21:33.740 transform. When you now add that third dimension, it becomes what we call K-space. So it's effectively
01:21:38.280 a two-dimensional Fourier transform, which is what the MRI world operates on. It's called K-space.
01:21:43.680 So what we're going to do in the show notes here is we're going to link to some very common
01:21:48.980 types of MRIs that people have, right? The most common ones that people have is you've tweaked your
01:21:54.080 knee. You're going to get the knee MRI. You've hurt your back. You're going to get the MRI of your
01:21:58.200 back. You're having headaches. They're going to do the MRI of the head, those sorts of things.
01:22:02.160 So when you think about the bread and butter clinical practice of medicine, what types of
01:22:06.760 MRIs, describe what those three would be. What sequences would be run to it? If you wanted to
01:22:10.860 evaluate someone's ACL, the ligament in the knee, what are you going to look at?
01:22:14.720 The first thing you're going to do, and this sort of relates back to the plane X-ray,
01:22:18.420 you're always going to look at things in two dimensions. So you're going to look at two planes in this case.
01:22:22.420 And so you'll be slicing from right to left, top to bottom, side to side. And the beauty of the MRI
01:22:28.040 is that based on how you orient your gradients, you can easily slice those three directions or
01:22:33.140 actually in any direction you want, which is why we call it multi-planar. And so if we were to look
01:22:38.860 at a simple thing, like a simple image, like a knee, so we always like our anatomy image. So that's
01:22:43.560 our plane T1 because fat is beautiful and it actually allows us to see everything really well. And it
01:22:48.680 looks like what we're actually accustomed to seeing. And so we do a T1 sequence. Then we'd also look at
01:22:54.260 a T2 sequence or a T2 fat sat sequence. And what that actually allows us to do is on a T2 fat sat,
01:23:01.120 we actually go in. That's fat saturation. Yeah. So T2 fat saturation, what we're doing is we're taking
01:23:05.960 T2. So now T2 looks at two things, so fat and water, and then we actually suppress the fat. So really
01:23:12.040 all we're seeing is water. And why that's most interesting is because edema. So when there's something
01:23:17.240 going wrong in the body, almost anywhere, edema happens. It's like if you bang your hand and it
01:23:21.520 swells up, that swelling is edema. You injure your knee, it swells up, that's edema. And so if you
01:23:26.880 actually bang the bones on your knees, so you've actually injured the cartilage, you're going to get
01:23:30.880 edema happening in the ends of the bone as well as in the cartilage. So that's why the T2 with fat
01:23:36.440 saturation or removing the fat signal becomes so powerful because it effectively now turns into a
01:23:41.960 edema imager. And when we know when there's edema, there's a problem. And that's kind of a simple
01:23:46.520 concept in MRI that is quite often lost, but it's very, very important.
01:23:51.060 And then when you look at somebody's brain, for example, we just reviewed my MRI recently. So one
01:23:56.760 thing that stands out, I think, is the exquisite anatomic detail you're getting that seems to look
01:24:02.680 far better than it does in CT scan. And secondly, it's the fact that without any contrast, you're
01:24:10.600 able to see as though you did an angiogram on all the vessels in my brain. Now, is that something that
01:24:18.860 any MRI can do? Or is that just something that the MRI here can do? Most MRIs should be able to do that.
01:24:25.080 And so when we can sort of think back to what an MRI is, so again, hydron imager, but it's also a big,
01:24:30.760 powerful magnet. And so what makes our blood red is actually the iron that's contained within it.
01:24:36.120 So what you can actually do is you can take all the blood that's, let's say, flowing to a particular
01:24:40.860 organ like the head. So anything that's flowing up and you say, okay, I'm going to actually excite
01:24:46.160 anything going up North to the brain. And so therefore that's arteries. And so then you'll
01:24:50.320 actually get to see all the exquisite arteries in your brain just by exciting that blood.
01:24:54.620 I had never realized something so obvious as you just said it, but that's one part of the body where
01:25:01.780 it's really easy. I mean, the limbs would be the same where directionally it's so clear. You know,
01:25:08.400 which way your magnet is oriented, you know, which way is blood flow away from the heart.
01:25:13.860 And you've got this beautiful iron floating around in water.
01:25:18.160 Right. That's one of the beauties of MRI is that there's all these different things that you can
01:25:21.740 actually add to it. And so not only that, you can actually excite anything flowing in one direction,
01:25:26.200 but you can actually also pick off the frequency that's different between oxygenated arterial blood
01:25:31.460 and deoxygenated venous blood. And so that comes into a different sequence called SWI or susceptibility
01:25:37.500 weighted imaging, where you can actually look at the deoxygenation status of venous blood and you can
01:25:43.020 get spectacular contrast of the small blood vessels in the brain using that sequence.
01:25:47.960 I remember the first time you did an MRI of my head. I don't know why I was more nervous about
01:25:53.340 seeing that than anything else, because we sort of remember the most extreme, horrible stories. But
01:25:59.300 I mean, I know people who have died of aneurysms. You and I were even speaking about a patient a few
01:26:04.480 hours ago about this. I used to ride a bike with a guy who was maybe six years, seven years older than
01:26:10.580 me and was at Disneyland one day with his kids and had a horrible headache and dropped dead. And he had
01:26:15.320 an aneurysm, which is congenital. And so, yeah, I was sort of like really nervous, even though I realized
01:26:21.340 on this straight probability basis, the odds were quite low. They weren't zero. And I figured, well, it's better
01:26:28.680 to find this now because you can treat these things electively quite easily. But once they rupture, the
01:26:34.280 mortality is incredibly high.
01:26:35.820 The mortality of a ruptured aneurysm is over 93 to 95%. So most people don't make it. Whereas when you do find
01:26:42.040 them earlier, there's all sorts of options, such as coiling, where you can actually treat it or clipping.
01:26:45.960 And so that's actually one of the real powers of being able to kind of see what's going on without
01:26:50.880 any injection or anything like that. You can see the exquisite detail of the arteries.
01:26:55.300 And if there is a problem, and we've found a fair number of people with them,
01:26:58.560 you can actually save their lives.
01:27:00.240 What is the frequency? Admittedly, you have a, you could argue a somewhat biased population
01:27:05.400 because they're more health conscious. Obviously, anyone who can afford to just pay for an MRI out
01:27:11.080 of pocket is going to have a socioeconomic advantage. But, but if you argue that that's
01:27:15.140 still a reasonable cross-section of the population from a genetic standpoint, which is what we're
01:27:18.860 basically asking, what is the prevalence you find of aneurysm in the brain?
01:27:23.760 So when we actually scanned a thousand people, we actually found eight intracranial brain aneurysms.
01:27:28.600 So 0.8%.
01:27:29.740 That's higher than I would have guessed. Does the literature support that?
01:27:33.580 The literature is actually a little bit less. And the question is, is that because you don't find
01:27:37.800 them? Because basically people have passed away and we don't know what happens to the elderly because
01:27:43.220 if they pass away, it's natural causes.
01:27:45.560 Yeah. We're not doing the autopsies. Now there are other aneurysms that are not quite as lethal,
01:27:50.040 but are really bad. And the two that I remember from residency were splenic artery aneurysms and
01:27:55.800 popliteal artery aneurysms. Do you see those? And if so, at what frequency?
01:28:00.140 We found only think two splenic artery aneurysms, but they are particularly deadly. And now the
01:28:06.060 popliteal arteries, haven't seen many of those. No, haven't seen those. And then those should be
01:28:10.420 actually easier.
01:28:11.200 You can palpate those on a thin enough individual.
01:28:13.620 I was going to say, those are actually easier to feel and to see and to look at,
01:28:17.300 but we actually haven't found any of those.
01:28:18.640 I'm kind of still shocked. That's a frightening statistic, Raj, to think that almost 1% of the
01:28:23.860 population has an aneurysm in their brain.
01:28:26.620 And one of the things that we actually find though, and this may be showing the genetic component to it,
01:28:31.060 is that when you find it in one person in the family, next thing you know, all their extended
01:28:35.100 families coming in, right? They want to know what's going on.
01:28:38.100 We looked into this three years ago. I have a patient, a young woman, probably in her late 30s.
01:28:43.360 Her mother died very young when she was very young. The patient was very young and the mother
01:28:48.160 herself was quite young from an aneurysm. It was not in the brain, but I'll, for the sake of trying
01:28:53.340 to protect her confidentiality, I'll refrain from saying what part of the body it was. And then when
01:28:57.960 we dug into her family history further, we found another person who had died of an aneurysm in yet a
01:29:03.280 different part of the body. So not aortic where you normally see that linked to atherosclerosis,
01:29:07.580 but a different major vessel. And our team did a bit of work on this and actually found evidence
01:29:13.700 that there really was potentially a genetic component here. And so we petitioned her insurance
01:29:20.180 company to pay for an MRA, a magnetic resonance angiography, which is basically what we're talking
01:29:24.800 about here. And they declined it, which really irked me. And we fought with her insurance company for
01:29:29.820 six months to get this paid. And they denied it and they denied it and they denied it. And finally,
01:29:35.000 the woman just paid out of pocket for it. And I was blown away at how much it cost. Do you want
01:29:40.280 to take a guess at how much it costs to get an MRA in the United States? I've seen some interesting
01:29:45.520 pricing. It was $9,000. Wow. Wow. That's a, that's unbelievable. Yeah. And it was negative. So we were
01:29:53.820 happy and she was obviously fortunate enough to be able to afford that. But it upset me that we couldn't
01:29:58.300 make a case to the insurance company that two people, one first degree, one second degree
01:30:03.680 related to this woman have died from an aneurysm young. And they were like, yeah, that's cool.
01:30:10.480 Wow. That's a tragedy. That's so let's come back to now what you do here, Raj, because I've been
01:30:16.040 around a lot of MRI. And if we bring this story back full circle four years ago, or whenever we were
01:30:21.100 introduced, the question that was asked of me was, Hey, is this thing kind of cool or what? And I came up
01:30:27.040 here and I spent the full day with you and I thought, yeah, boy, this is really cool. But so
01:30:32.060 many things that you were doing just seemed counter to what we were seeing in the big shot hospitals.
01:30:37.940 And for starters, you were using a puny magnet, right? So one of the things hospitals love to brag
01:30:44.860 about is the size of their magnet, right? I'm going to just try to not to name any hospitals and offend
01:30:50.180 everybody, but you know, pick your favorite institution. We've got the newest four Tesla magnet.
01:30:55.740 I probably was in the top five questions I asked you, Oh, so what size magnet are you using? And
01:31:01.280 you said, we're using a 1.5 Tesla magnet. And I said, Oh, that's interesting. That seems a little
01:31:06.860 bit JV. So explain why you use a magnet that is not at the peak of what you're capable of just from
01:31:14.780 a technology standpoint. Well, it really sort of depends on like basically how you tune a magnet.
01:31:19.580 So I actually kind of view a magnet. It's very much like a smartphone. If you actually build the right
01:31:23.880 hardware, you can actually really get it to sing and do an amazing job. And so with a 3T magnet,
01:31:29.420 one of the things is you can get some pretty exquisite imaging as you see quite commonly.
01:31:33.220 And really there's a lot of bragging rights associated with it. We're not much of braggers
01:31:37.400 up here. We just actually want to do the best imaging we can and actually tune the machine as
01:31:42.220 optimally as possible. So with a 3 Tesla magnet, one of the things that actually commonly happens is
01:31:47.380 that when you look at the wavelength of a 3 Tesla, because remember it's electromagnetic fields
01:31:51.360 actually go hand in hand. And those are actually wavelengths. And so the 3 Tesla wavelength is
01:31:57.620 roughly 15 centimeters. So it's the width of your head. 1.5 is roughly 30 centimeters. So it's the
01:32:03.380 width of most people's shoulders. So as a result, you actually start to get a lot more penetration
01:32:08.260 with a lower field magnet. And so that way you're actually able to see things quite well when you're
01:32:13.760 particularly having everything tuned to that particular wavelength. And quite commonly when people
01:32:19.460 are purchasing machines, they just don't know the physics of how the static magnetic field, the gradient
01:32:25.420 magnetic fields, the coils, and there's roughly about 150 parameters per T1, T2 fat saturation sequence that
01:32:33.640 you can actually adjust to make it work the way you need it. And most of the time, what commonly happens
01:32:39.340 almost everywhere is that you'll have the vendor will actually come in and set the standard parameters.
01:32:44.460 And from there on, it's kind of like, let's make it as simple as possible, push a button. And that's
01:32:49.660 kind of not what I do. We don't want to just push buttons. We actually want to understand how it all
01:32:54.060 works, how it can be optimized to the person that's coming in, and how the entire system from front to
01:32:59.760 back is optimized. So we're maximizing our signal to noise. And when you maximize your signal to noise,
01:33:05.100 that's when you actually really get a lot of speed and detail. And that's where one of the real values
01:33:10.900 of being able to talk engineering or physics with the MRI physicists, and also then put on your
01:33:15.740 clinical hat and kind of saying, well, this is what I want to see. This is a level of detail I need
01:33:19.700 and the level of resolution that you can really tune the machine to where you want it to be.
01:33:24.740 To me, of course, that was the analogy you came up with. The first one that jumps to my mind is
01:33:28.140 looking at sort of the heyday of F1 in the late eighties and early nineties, when the cars had become
01:33:35.180 monsters. So if you look at the McLaren MP44, which is regarded as either the greatest or second
01:33:42.900 greatest Formula One car in history, the only other car that could probably rival it would be the 1993
01:33:47.480 Williams. It had a 1.5 liter engine. So for any gearhead listening, that's a really tiny engine.
01:33:53.900 Like your Prius probably has a bigger engine than a 1.5 liter engine. And yet it produced 1200 horsepower
01:34:00.460 redlining at something like 15,000 RPM. And I just remember being a boy, being so obsessed with that.
01:34:09.480 Like, how could that possibly happen? And I remember looking at my dad's station wagon, which had like
01:34:15.440 a five liter Chevy block in it and thinking, how is this thing so inferior? But in the end, like you
01:34:22.860 can engineer, I mean, I think the technical term is you can engineer the shit out of anything, right?
01:34:27.840 That would be exactly. And that's exactly what it is. And it's very analogous to the Formula One.
01:34:32.820 And a lot of people kind of, they're more into the bragging rights of like the bigger, the bigger,
01:34:36.760 the bigger. It's not always bigger. It's kind of like, if you really understand what you're doing
01:34:40.880 and want to get underneath the hood, you can take that 1.5 liter engine, you can put the turbochargers
01:34:46.520 on it. You can put, you know, like the multiple valves and the everything to actually get the torque
01:34:51.820 and horsepower you want out of it. But most people don't think that way. They think bigger is better.
01:34:56.600 How did you do all this tinkering? Because you basically have here in Vancouver, a piece of
01:35:04.580 hardware that doesn't exist anywhere else in the world. And you've layered on top of that software
01:35:09.600 that is now also in a league of its own. And that's even more complicated. I just am interested
01:35:15.000 in this hardware. I mean, one of the things that I send a number of patients here, and usually the
01:35:19.840 first question I ask is, why are you sending me to Vancouver? Like I live in fill in the blank,
01:35:24.720 some city in the United States, we do everything the best. There's no way, Peter, you're telling me
01:35:30.620 there's an MRI in Vancouver. In fact, I told my parents the other day, I was coming to Vancouver
01:35:35.260 to get the MRI and they live, you could almost hear them look at me through the phone. Like,
01:35:39.700 why are you coming to Canada? So, I mean, not to toot your horn too much, but you're doing something
01:35:46.340 very different, Raj. So, how did you go through this process of tinkering with the 150 variables
01:35:54.040 at your disposal to come up with this super custom pimped out hardware that doesn't resemble
01:36:01.540 anything else on the planet? So, part of it is, it's like the biggest problem with me is that I'm
01:36:06.980 an engineer in medicine. And so, when I kind of go through, it's like I say, well, what do I want to
01:36:12.620 know? What do I want to see? And how do I make it work? And so, I kind of start at sort of the back
01:36:16.840 end and say, okay, what I want to know is exactly what's going on everywhere in the body. And what
01:36:21.840 are the different sequences that are going to get me there? And then I kind of work backwards. And
01:36:26.240 then this is where you put your engineering or physics hat on. And you actually wind up starting
01:36:31.240 to talk to like the MRI physicists who are, there's a plethora of them. They're almost everywhere.
01:36:36.560 And they love to talk to doctors, but just most of the time, doctors can't talk to them or vice versa.
01:36:42.060 And that's when you start to really kind of get under the hood and really kind of understand how
01:36:46.120 to make this work. And then you travel around to different academic centers or different places,
01:36:50.560 and you wind up spending time with the people who actually really understand the hardware. And those
01:36:56.500 are mainly the physicists, very similar to a mechanic. It's like, if you want to figure out how to make
01:37:01.500 your five liter behave like a thousand horsepower, you talk to the mechanics who know how to do it.
01:37:06.920 Don't try it yourself, right? They've already been there. They've seen it. They worked on things
01:37:10.540 forever. And that's actually how a lot of it happens. And so we would actually be having some
01:37:15.300 of the top MRI physicists sort of saying, Hey Raj, can you test this? We wrote this sequence.
01:37:20.160 And the sequence is basically like a filter, like a T1 or a T2 or a fat saturation.
01:37:24.840 Can you try it out and kind of see how it works? So we'd go and try it out, usually on me as a
01:37:29.260 subject, because I also know what I'm looking for. And then we'd have a feedback loop, one or two of my
01:37:33.960 MRI technologists here who would actually sort of push the buttons and run the machine.
01:37:37.480 And we'd see what it would give me. And I knew from all the other imaging training that I would
01:37:41.980 have, what I would be looking for. So I put my nuclear medicine hat on and say, okay, from a
01:37:46.480 functional point of view, this is what I want to see. Then I put my radiology hat and say, this is
01:37:51.160 what I want to see from an imaging perspective. And let's define that a little bit. I mean,
01:37:54.780 objective is important. So when you went about this process, what were you optimizing for? Were you
01:37:59.700 interested primarily in detection of cancer or what was the problem you wanted to solve clinically?
01:38:04.440 The first thing I wanted to do is, so when we talk about the nuclear medicine, so when we're
01:38:08.560 injecting somebody with radioactivity, we want to basically optimize that dose that we're giving
01:38:13.120 to somebody. So that means we want to cover everything from head to foot. We don't want
01:38:16.620 to just look at an individual body part and we want to see how it all works. Then we go to radiology,
01:38:21.560 typically we're just doing a snapshot of an individual part, like a head or a neck or a torso.
01:38:26.520 And so I kind of thought, well, of all these MRI machines that are out there, all they're doing
01:38:30.040 is looking at individual body parts. And I thought, if I customize this hardware with a
01:38:35.340 few things that might allow me to move people around while they're on the table, while they're
01:38:40.240 laying there, will I maybe be able to connect the head with the neck, with the chest, with
01:38:44.740 the abdomen? And so I actually, when I bought the hardware myself, I kind of put together
01:38:49.600 probably about 50 options that the vendors kind of said, you're crazy. We've never seen any
01:38:55.260 of this stuff just with the thought that, you know, I think this might work. This is
01:38:59.300 where I was kind of looking at all the different options and kind of knew what they could possibly
01:39:02.420 do. And I thought, if I build this hardware, this, this way, will it work? And it was a
01:39:09.680 complete guess, but an educated guess. And then once I put that hardware together, then
01:39:14.280 we started to test and test and did more and more. Then we would start talking to more
01:39:19.460 physicists. The vendors themselves actually have a lot of good resources with very technologically
01:39:24.660 capable people. And when I started to put this together, then I kind of thought, okay,
01:39:29.900 what would I want? If I'm a patient, what would I want to know? Well, number one, I'd want
01:39:34.400 to know that my brain's okay. I'd want to know that the arteries in my brain are okay. They're
01:39:38.120 not going to rupture. And then I basically want to say, whenever I go into any test or anybody
01:39:42.960 goes into the doctor and gets any kind of imaging test of any kind, the first question
01:39:47.420 out of their mind is, do I have cancer? Yes or no. And in nuclear medicine, most of the
01:39:51.980 tests are binary. We can actually answer that with a yes or no.
01:39:54.660 In radiology, it's not so clear. It's kind of like, maybe. And you're actually kind of
01:39:59.520 playing more statistics, like probably not. And I thought, how do I marry these two together?
01:40:04.460 And this is where an MRI becomes a beautiful machine. And the fact that it actually allows
01:40:07.860 you to take that yes or no binary answer of functional nuclear medicine and combine it
01:40:13.200 with the anatomic localization and understanding of tissue types that radiology has. And so I
01:40:18.540 merged those two together on the one machine.
01:40:21.320 And what is the functional arm that you've brought into it?
01:40:25.180 Yeah. So the functional arm is actually an area that's actually growing a lot in academia. It's
01:40:29.080 actually called DWI or DWIBS, which stands for diffusion weighted imaging with background
01:40:33.680 subtraction. And so what we're doing with DWIBS is that we're actually looking at water at two
01:40:39.180 points in time. And so we're actually looking at it within about 60 microseconds of water motion.
01:40:44.240 And so by doing that, what happens is that you first look at water at one point in time,
01:40:49.140 and then you look at it at the second point in time. And if it hasn't moved,
01:40:52.840 it's because it's not allowed to move. It's effectively trapped between walls. And so that
01:40:57.560 could be because of the fact there's a tight cell membrane, or it could be because components of a
01:41:02.440 cell are preventing that water from moving.
01:41:04.960 What's the time gap between those two samples?
01:41:07.340 Six microseconds.
01:41:08.200 Wow. And so when you see that something isn't moving, when you see that water is
01:41:13.480 being forced to be stationary, as opposed to moving, according to the stochastic prediction
01:41:19.100 you have, what do you infer clinically about that tissue?
01:41:23.100 So as soon as you start to see that water is being prevented from moving, that means that there's
01:41:27.040 basically going to be a high density of cells there. So a big cluster of cells. And so it's very
01:41:32.800 much like, I actually call it the lump detector. So it's basically like they tell women for breast
01:41:36.960 cancer, feel for a lump. And basically when you're feeling for a lump, that's hard spot. And so the
01:41:41.680 reason it's hard is because you have this increased cellular density. And so with that increased cellular
01:41:46.260 density, that's where water is restricted from moving. And that's what DWI or diffusion-weighted
01:41:51.460 imaging does. And why it's called DWI is because the fixed law of diffusion basically means that the
01:41:57.320 normal diffusion of water, allowing it to move a lot, is being completely restricted. And it just
01:42:01.580 doesn't have the ability to move.
01:42:03.040 You know, I usually tell patients about this part of the MRI, telling them something that I think many
01:42:08.160 people outside of medicine would find surprising. When you do what's called a laparotomy, when you
01:42:13.140 open up a person's abdomen and let's say they have colon cancer. So the colonoscopy has confirmed that,
01:42:18.760 of course, you have a biopsy. So now you're going in to do an operation to remove their colon,
01:42:22.760 but you still have another step along the way, which is you have to complete what's called staging.
01:42:26.760 You have to ask the question, has this cancer spread?
01:42:29.780 So usually the first thing you're doing is you're running your hand along parts of the abdomen.
01:42:35.340 You can't even visualize the entire surface of the liver, even behind the liver, something you
01:42:39.160 won't see. It's actually unmistakable what cancer feels like because it is so in contrast to what
01:42:46.240 normal tissue feels like. And even the colon, before you cut it out, if you just reach in and
01:42:51.520 pick up a piece of the ascending colon, it's not remotely subtle where the cancer is. It's entirely
01:42:58.600 obvious just based on the firmness of the tissue. And even when I talk to surgeons who operate on
01:43:04.640 parts of the body that I didn't operate on, such as the prostate or things like that, it's the same
01:43:08.780 thing. And the example you give with breast is perfect. And so it really is this amazing ability
01:43:14.260 to pair exquisite anatomic detail at resolutions that we'll discuss, but basically now approaching
01:43:21.840 one by one by one millimeter resolution anatomically with now this functional property of firmness.
01:43:29.300 Is that an accurate statement?
01:43:30.800 It definitely is. So we're actually combining the anatomic and functional. And that's where just like
01:43:35.460 the PET CT, where that famous one plus one equals three is exactly what we're doing. And the beauty of
01:43:41.160 it is there's absolutely no radiation. So there's no risk.
01:43:43.360 So the risk, it seems, because one of the things I do explain to patients is who should consider doing
01:43:50.620 this, right? And my view with cancer screening is it's just a very personalized decision. I don't
01:43:55.840 think it is for everybody to do the kind of stuff that I do or that a number of my patients who you've
01:44:00.760 now scanned have done over the past three or four years. And when people say, is there a harm of doing
01:44:06.560 this outside of the probably rare, rare event of getting a migraine headache triggered by the magnet,
01:44:11.900 I say there is a harm, the harm of a false positive. The harm is that we see something
01:44:16.620 that turns out in the long run to not be cancer, but in the process of going down the advanced
01:44:23.840 diagnostic pathway to get there, you are either physically harmed by something we do subsequently,
01:44:30.360 for example, another biopsy or a biopsy or a subsequent biopsy. And of course, the emotional toll
01:44:37.040 it takes on you to see a shadow in this part of your body and have to sit there and have a
01:44:42.880 discussion about what it could be, what it's probably a cyst, but it might be a tumor. We
01:44:47.900 probably need to do a follow. I mean, to me, this gets back to where we were a while ago on the
01:44:53.260 discussion of sensitivity and specificity, right? So if somebody came along and said, I have a test that
01:44:58.280 is a hundred percent sensitive, but only 50% specific, I'd throw it in the wastebasket. I
01:45:06.060 mean, it would serve virtually no purpose for reasons I could walk the listener through in
01:45:10.520 terms of positive and predictive value, negative predictive value. So when you think about the
01:45:15.960 sensitivity and specificity of the technology that you've developed here, which again, we haven't
01:45:21.060 even really done justice to getting into, we've talked a little bit about the hardware. We haven't
01:45:24.600 even got to the software. I'd love to talk about that a little bit. Do you think about
01:45:28.120 sensitivity and specificity by tissue type, by cancer type? How do you, in your mind, wrap your
01:45:34.780 head around that? So typically the way I kind of look at it is really almost organ by organ. When
01:45:39.680 we're actually kind of going through, for example, in the liver, basically the simple thing we want to
01:45:43.960 kind of know, is there a problem? Yes or no. Like really, that's the simplicity that the average
01:45:48.660 person, and I put myself in that category, wants to know, do I have a problem to worry about?
01:45:53.380 Well, and that's where I kind of say, by combining this functional as well as an anatomic imaging
01:45:57.320 together, we're actually really able to nail that down. So in our thousand people that we did,
01:46:03.140 the fascinating thing about this is all these people, we actually followed them up and actually
01:46:06.780 talked to them and kind of found out what happened. And so we actually had two false positives. So these
01:46:11.320 were two people where we kind of thought, okay, there's a problem here that you need to get
01:46:14.940 addressed further by their further imaging and see what's going on. And of those two false positives,
01:46:20.600 one was a male with asymmetric breast tissue. So he actually just had one-sided breast tissue.
01:46:26.700 We didn't know what it was. It's like... So meaning you, he came out of the MRI and you
01:46:30.640 believed he had breast cancer, which most listeners might think is odd, but it turns out men can get
01:46:35.220 breast cancer. It's just virtually and exceedingly rare. Exactly. But that's basically the DWI showed a
01:46:40.820 difference in density between... One breast and the other. Yeah. And so we're like, why is that?
01:46:45.020 Most of the time when men actually have gynecomastia or they have breast tissue, it's usually bilateral
01:46:50.240 because it's hormonal. But to have unilateral is somewhat odd. And so as a result, we sent this
01:46:56.140 person to an ultrasound, which is a commonly done, and they too had no idea. And so they actually also
01:47:01.880 made the call to biopsy and it came back as normal breast glandular tissue in a male.
01:47:05.940 So let's talk just about the harm there. So emotionally, that man probably spent a series of,
01:47:11.600 well, if it was in Canada, a year. If it was in the United States, a week. Being stressed out about
01:47:16.240 this. Sorry, I just can't help but take digs at your healthcare system as you take digs at ours.
01:47:20.820 No, I'm totally teasing. So there's a legitimate emotional strain here, which I don't think anybody
01:47:25.820 who's known someone who's gone through that or who's gone through that themselves, you just can't
01:47:29.280 deny this. And I've not lived it personally, but I've seen it and it's very difficult. And then secondly,
01:47:34.200 he had to get a procedure. He had to get a needle stuck into his breast tissue. And look, that's
01:47:38.700 on the scale of procedures, that's still pretty minor, but it's not trivial. So what was the
01:47:44.480 second case? And so the second case was actually a woman who basically had a seatbelt injury to her
01:47:49.920 breast and actually wound up having unusual scar that had actually trapped fluid in it.
01:47:54.280 And so this person actually should have, but never did actually have any mammograms because that would
01:47:58.860 have led to the same conclusion that we don't know what this is. So that was the second case where it's
01:48:03.600 kind of like, there's something unusual going on in this breast. We don't know what it is,
01:48:07.020 but we didn't actually have any proper history from her. And so we-
01:48:11.080 How old was she?
01:48:11.740 She would have been late 50s.
01:48:13.740 A woman in her late 50s had never had a mammogram?
01:48:16.180 Surprise. It's out there.
01:48:17.580 Even in Canada?
01:48:18.520 Even in Canada. Yeah.
01:48:20.000 That in and of itself is very hard to believe in a country where-
01:48:22.900 It's free. Yeah.
01:48:23.920 Yeah. And then what would bring that patient in to get a whole body MRI?
01:48:27.760 MRI. The person actually kind of felt that I just want to know where I'm at. And it's like,
01:48:32.240 I don't believe in the radiation from mammography. And I keep trying to tell them, look, it's so
01:48:36.560 minimal that the benefit outweighs the risks. But they're like, I want the MRI instead because
01:48:41.380 number one, patients kind of know that it's the most detailed exam you can get. And as well,
01:48:45.940 there's no radiation. So we actually had the patient and it's kind of like, yes, there's this,
01:48:50.040 I don't really know what this is going on here. So we sent them off to a facility that does
01:48:55.200 nothing but women's imaging. And they too didn't know what it was. And so they stuck a needle in
01:49:00.680 it and it actually came back as a trap.
01:49:02.480 Something fibrous.
01:49:03.620 Exactly. It was actually trapped scar tissue. And at that point when we'd spoken to a woman
01:49:07.400 afterwards, we're like, did you ever have trauma? Like, why would you have scar to that area? And
01:49:12.040 it's like, oh yeah, I was in a bad car accident. And that was it. It was a seatbelt scar.
01:49:15.440 Those are two pretty interesting false negatives, right? Both breast, men, women. I would have always
01:49:21.440 maybe guessed or been most concerned about the false positives that occur deeper in the body.
01:49:27.740 I always tell patients, the call I'm always most afraid of getting is the little shadow in the
01:49:32.760 pancreas where you just don't know, is this an adenocarcinoma of the pancreas? Which of course is
01:49:38.020 something that if you're lucky, you can resect it. And if you're even luckier, you can survive it.
01:49:43.080 And I guess that's the only shot you're going to have at surviving pancreatic cancer is an
01:49:47.220 incidental finding. I really don't think anybody that presents with pancreatic cancer is going to
01:49:51.100 survive it, at least not as an adenocarcinoma. But then you worry about, well, what if it's
01:49:56.340 something that turns out not to be cancer? And you hear these horror stories. There's a very famous
01:50:00.140 one, I believe at Stanford several years ago, where a woman went to a sort of drive-by CT clinic,
01:50:05.300 got a CT scan, showed something in the pancreas. She ended up going to get a biopsy. And I believe
01:50:11.260 it was an ERCP. I did biopsy. One complication led to another, led to another. She died of sepsis.
01:50:17.680 And by the way, it turned out she didn't have pancreatic cancer. I don't know that
01:50:20.860 firsthand. So that might be a bit of a wives' tale stretch, but certainly that's a very popular
01:50:25.580 story in the Bay Area. But it's the cautionary tale, right?
01:50:28.720 Definitely it is. And that's kind of where the real value of actually having MRI as opposed to
01:50:32.540 CT comes in. And the fact that when we're looking at organs, particularly like the pancreas or any
01:50:37.080 of the visceral solid organs, we're looking at about seven different filters, looking at it different
01:50:41.940 ways, top to bottom, front to back, to really be able to see what's going on. And that's where what we
01:50:46.860 call contrast density becomes really important in the fact that when we're actually looking at the
01:50:51.800 pancreas in particular, we can actually pick out the pancreatic duct as well as a bile duct and be
01:50:56.840 able to see that just standing out against the rest of the organ. And one of the first, most common
01:51:01.440 things that pancreatic cancer likes to do is to actually start to block that duct. And so that's
01:51:05.840 why when ERCPs are done, they're actually looking for cells of pancreatic cancer. And an ERCP is basically
01:51:11.660 when they go down into the mouth and the esophagus and they actually go and take a trace of fluid from
01:51:17.420 the pancreatic bile duct. So one of the other things that kind of amazes me when we go through
01:51:23.320 these images here is when we've talked a little bit about the hardware though, actually, I kind of
01:51:27.720 want to come back and ask more hardware questions, but it's almost like you've created your own software
01:51:31.420 now as well. I had never seen this. Is it commercially available to have that rotating diffusion
01:51:37.960 weighted image map? Is that a commercially available piece of software or did you guys make that?
01:51:44.400 We actually built that as a display tool and that's actually effectively taking a page out of
01:51:49.580 the nuclear medicine positron emission tomography or PET CT handbook. And the reason why we actually
01:51:54.920 put it together is because it actually allows you an effectively a pretty efficient viewing to be able
01:52:00.400 to see what's going on through the entire body. It's almost like making a transparent person
01:52:03.980 and where basically any of the black spots that stand out would be the hard spots or the firm areas.
01:52:10.640 And the one that we've just looked at earlier, I remember you saying that, if I understood you
01:52:16.640 correctly, one of the advantages of using a quote unquote low power magnet like you're using is you
01:52:22.260 don't have any of the gaps in the spine. You've got this, everything that you showed on that rotating
01:52:27.220 diffusion weighted image, you had the dark brain, obviously full of firm fluid. And then you have this
01:52:33.480 dark, beautiful tail coming out of it, which is the spinal fluid, but it was perfectly smooth.
01:52:39.540 Right. And that's actually one of the important things because magnets actually have a lot of
01:52:43.320 homogeneity problems, we call them. And the fact that you want it to be perfect so that the field
01:52:48.360 in between the top and the bottom and the left and the right are identical. And as soon as you put a
01:52:53.360 person in there that comes in various sizes and shapes, they actually distort that magnetic field.
01:52:57.480 And the sweet spot for the magnetic field is perfectly in the center. And so when we put all
01:53:02.700 these protocols and built all these things, we actually built it for different body shapes and
01:53:06.980 we can actually go and tune it for all these body shapes so that the goal is that no matter what,
01:53:11.720 when we're doing these rotating images, that it looks like a normal person, not a segmented piece
01:53:16.040 of a person.
01:53:17.100 Yeah. It's funny you say that you took a playbook out of the PET CT. That's exactly what it looks like.
01:53:21.140 It looks just like you're looking at the FDG PET juxtaposed with the CT.
01:53:25.460 Right. And that's the entire purpose. And so that's where I talk about the MRI being this tool
01:53:30.480 that can actually combine functional imaging of, in this case, DWI or DWI diffusion weighted imaging
01:53:35.560 and the MRI being the equivalent to the CT, which is far more tissue weightings in detail.
01:53:42.140 It's where the one plus one equals three.
01:53:44.200 Now, if the radiation didn't bother you of a whole body PET CT, and of course it should bother you
01:53:50.320 because a whole body PET CT would be more than 50% of your, it'd be probably close to 80% of your
01:53:56.980 annual allotment of radiation, right? If not more.
01:53:59.840 It'd be quite high. Yeah. And depending on if you live at altitude or where you live, right? So if
01:54:04.420 you're at sea level, you'd probably be allowed one a year maximum, if not one every two years.
01:54:10.380 Yeah. So putting aside that issue, which is not trivial, what advantage do you think that
01:54:16.960 the MRI with DWI has over the PET CT? And where does the PET CT have an advantage? So if you go
01:54:25.080 either by histology, by tissue, by tumor type?
01:54:28.180 With the PET CT with radioactive glucose, one of the areas that actually doesn't work very well at all
01:54:33.180 is the brain. And the MRI is always known as like the best image of the brain. The PET CT,
01:54:38.540 you can actually miss things in the brain because what you're looking for with the radioactive glucose
01:54:42.880 is areas of increased glucose utilization. And the brain in particular is a glucose,
01:54:49.000 that's all it can use unless you're in ketosis. And then the other problem is that the glucose is
01:54:54.720 then excreted by the kidneys. And so the kidneys now become difficult to see because they're actually
01:54:59.800 full of glucose. And as is the bladder, you can't see a thing in the bladder because it's full of the
01:55:05.240 accumulated glucose. As well in the prostate, prostate is very, very poorly perfused. And as
01:55:10.900 a result, it doesn't get a lot of glucose coming to it. And so PET is actually almost entirely useless
01:55:16.480 with FDG at looking at the prostate. Diffusion weighted image of the prostate, coupled with
01:55:22.940 the more advanced molecular tests, the 4K as an example of a blood test, in my mind have totally
01:55:29.720 revolutionized the way we think about prostate cancer. So we now have a blood test that produces
01:55:35.720 much better resolution than just a PSA. But more importantly, we have this MRI. And even in a
01:55:42.700 practice as small as mine, I have had two patients for whom PSA is high, 4K comes back high. So these are
01:55:54.220 patients who now have a 20% chance, maybe 16, 18, 20% chance of having cancer in their prostate or
01:56:02.580 having metastatic cancer over the next two decades. That's basically what the high 4K tells you.
01:56:07.160 In the olden days, we would have just biopsied them. And now we run them through this MRI. And the
01:56:13.300 answer is, nope, that's totally fine. Right. And then that's actually where MRI becomes very,
01:56:17.520 very powerful, particularly with the DWI. And I think in many countries, it's now coming to US and
01:56:22.620 becoming more popular. But in Australia, in Europe, particularly UK, Scandinavia, it's actually
01:56:28.720 the de facto standard. Basically, almost all men are actually getting screened with MRI.
01:56:33.740 Wait, wait, wait. Did you say in Europe and Australia?
01:56:35.980 Yeah. They're actually doing it with a DWI. And so-
01:56:39.340 How is that even possible that countries with single payer socialized medicine could use an MRI for
01:56:45.140 a screening tool? I mean, that would be unheard of in Canada, wouldn't it?
01:56:48.520 Well, you know, we just don't have the access to the number of machines here. But I think one of the
01:56:52.200 things that people are actually finding with screening for the prostate is that all men are
01:56:56.220 either going to die with or from prostate cancer. And so you really want to be able to separate those
01:57:00.120 out. And up until MRI with DWI came into effect, there was no real way to do that. So you'd be
01:57:05.840 doing PSA or 4K. And all that would do was say, yeah, there's an increased risk of something going
01:57:11.500 on. But is it going on? So PSA in particular, it can actually be elevated for three reasons. One,
01:57:16.980 prostate cancer, the other one, inflammation or prostatitis. And then the third being enlarged
01:57:21.920 prostate. And so if it was up for any of those causes, then you would actually go and take a
01:57:25.860 biopsy, which actually comes with risks. But the whole idea is that all the staging was based on
01:57:31.200 that tissue sample. Whereas what's happening very similar to the breast is kind of like a lot of
01:57:36.420 people are saying, well, treating this is like a big deal. I don't want the biopsy. And people get a
01:57:41.300 choice of what they want to do. And a lot of men are saying, look, I want to see what's going on.
01:57:45.720 I want to see if there's going to be a change. And if it actually starts to grow or something's
01:57:49.960 growing in the prostate at an accelerated rate, that's when I want to deal with it. Whereas if
01:57:53.900 it's actually just there and holding still and not changing much, I'm not going to worry about it
01:57:58.020 because something else may take me first. Is DWI going to have the same effect on breast
01:58:02.720 cancer? In other words, if you could put resources aside for a moment, if a woman could have a mammogram
01:58:08.720 and a DWI MRI, then it's important to point out that you can't eliminate mammography because
01:58:15.320 we're going to come to this, but MRI has its own blind spots and small calcifications would be a
01:58:20.420 blind spot. But with those two tests, mammogram and DWI MRI done the way you guys are doing it,
01:58:28.360 not just off the shelf, are you going to miss breast cancer in those situations?
01:58:32.820 Pretty unlikely. And actually there's been a couple of really nice big studies that have
01:58:36.100 finally started to come out from groups at UCSF and as well at Sloan Kettering,
01:58:40.440 Memorial Sloan Kettering in New York that have actually shown that.
01:58:42.900 You did your fellowship at Memorial, didn't you?
01:58:45.120 No, I was actually there for quite a while actually doing PET-CT.
01:58:48.200 Okay, yeah, yeah.
01:58:48.980 Amazing institution, absolutely amazing. But what's actually come out of the MRI group is that
01:58:53.880 basically if you actually use DWI with MRI, you actually are as sensitive as giving a contrast
01:59:00.360 injection breast MRI.
01:59:02.080 Wow.
01:59:02.560 But that's diffusion done right. And the problem is out of the box, it's not always done right.
01:59:06.900 Yeah, that's the challenge I think for the patient, right? Is the patients,
01:59:10.200 look, you kind of need a PhD in physics, let's be honest, to really understand the nuances of MRI.
01:59:17.140 I consider myself pretty technically smart when it comes to the physics of this stuff. And I would
01:59:23.020 not feel competent to try to differentiate or even parse out the differences between scanners. In fact,
01:59:31.120 anytime I'm sending my patients to a scanner, I sort of have to rely on other people to help me.
01:59:35.600 I have to reach out to experts and say, hey, my patient has to get this scan done in New York or
01:59:40.680 in San Francisco or LA. Is this the best we got? If they're not going to get on a plane and go to
01:59:44.940 someplace where I know exactly what they're going to get. So that's a significant challenge, right?
01:59:49.580 Because there's, people are going to listen to this and think, okay, well, as long as it's
01:59:53.080 diffusion-weighted imaging MRI, it's perfect.
01:59:55.540 Yeah. And that's actually the biggest problem with MRI. Like earlier on, we talked about CT having
01:59:59.460 units of Hounsfield, like Hounsfield units to actually sort of calibrate and standardize them.
02:00:03.300 Unfortunately, MRI has no standardization whatsoever. And there's actually a movement
02:00:08.680 called Kiba or Quantitative Imaging Biomarkers Alliance. It's a component of the Radiology
02:00:13.800 Society of North America that's actually really trying to push to standardize the amount of signal
02:00:18.700 to noise coming off of MRI machines with the goal that if you actually get a scan at one site or
02:00:23.560 another site, the image quality is the same. Right now, it's really not that at all. And it really
02:00:30.540 is sort of caveat emptor lookout. So right now, if somebody goes to Shreveport and gets a 256 slice
02:00:39.340 CT scanner on a Siemens, pick your favorite model, and they do the same thing in Seattle,
02:00:46.140 you can share those data across radiologists and it can be made to look identical. Your acquisition is
02:00:52.840 the same. Relatively. So what I mean by that is that the actual amount of signal on your film or on your
02:00:57.900 screen, water is going to be zero. And so the Houndfield unit is always going to be exactly
02:01:02.820 calibrated. So what's the opposition? I mean, that seems like a no-brainer. What is the opposition
02:01:06.880 to doing this with MR? It actually relies on the vendors coming together. And a few years ago,
02:01:11.940 we actually spoke with a bunch of the vendors and saying, you know, look, why don't you guys do
02:01:14.960 this, particularly for a diffusion where it's actually so important because this is such a new
02:01:19.000 and powerful sequence. And they all kind of came back and said, well, you guys write a white paper and
02:01:24.580 then we'll implement what you said. And this is fortunately starting to move forward with this
02:01:29.260 organization, Kiba, out of RSNA. And they're doing it organ by organ. So there is a bit of a
02:01:33.920 standardization for prostate, for liver, and as well, breast is now coming out. And that was actually,
02:01:40.720 the breast was led by a group out of University of Washington. And the overall leader for this is a
02:01:45.840 person named Michael Boss out of, now he's the American College of Radiology. And this needs to
02:01:50.560 move forward because otherwise people have no idea what they're getting.
02:01:53.760 And it's really sad because even if you walk down the streets, for example, in a place like New York,
02:01:58.240 I used to live literally 20 feet from a MRI shop. And they had all these sort of images and what I
02:02:06.400 consider just sort of bogus propaganda all over their window. Like, why go down to Memorial and get
02:02:11.280 your MRI there when you can come here and do a standing MRI? It's comfortable, it's fast, and blah,
02:02:16.440 blah, blah, blah. And I'm thinking to myself, and it sucks. So, and again, I don't know that that
02:02:21.040 exists in Canada, but it's certainly in the United States, there's a bit of a cottage industry around
02:02:25.020 one-stop shop scanners that I think patients just don't know what they're getting into, right?
02:02:30.540 Right. And I don't know how well it works in the United States, but it really is. It's like,
02:02:34.260 because of this lack of standardization in the field of MRI, and it's really unfortunate because this
02:02:38.980 is, of all the imaging tools, it's the most powerful, but it really does need this ability for
02:02:44.280 standardization. And it may also sort of be the fact that in order to make it standardized,
02:02:48.460 you need to get the physicists together with the radiologists who are basically the eye of the
02:02:53.540 final image. And quite often that doesn't happen because of the language barrier.
02:02:58.600 Right. And of course it's not, it's the language of physics is the language, you know.
02:03:02.280 Going back to the hardware for a second, where do you see things evolving? In other words,
02:03:06.320 if you had to project where you think you, with the right technology, would like to see this in
02:03:12.340 five or 10 years, what could make this better? What I'd actually like to do, and when you see
02:03:15.940 sort of what we're doing, the speed with which we do and that the detail and resolution that we're
02:03:20.540 able to acquire in about 55 minutes is really unprecedented anywhere. But I know from a physics
02:03:25.120 point of view that I could speed this up further. Right now, everything we're doing is perfectly
02:03:28.980 within FDA specifications. There's nothing outside of the box, but I really would like to push this and
02:03:34.740 go outside of the box. And what that really requires is a lot more computational horsepower.
02:03:39.080 It's really difficult to do all that computation within a single CPU machine on site. Whereas I
02:03:45.420 expect that in the future, as more as long computers get faster and faster, you can actually
02:03:50.100 do a lot of this stuff computationally and make it much faster. And the goal would really be to
02:03:54.880 actually have these scans that we're doing, you know, under half an hour, even faster. And it can be
02:03:59.880 done from a physics point of view. It's not a technological barrier.
02:04:02.760 Even with the magnet that you have, even at 1.5.
02:04:05.700 Yeah. Now, I had my scan today. A friend had a scan today. And one of the things that people
02:04:10.440 always talk about when they're done these scans is, my God, it gets hot in there. What is it about
02:04:14.800 a whole body MRI, even one that's done in as short a period of time as 55 minutes, that makes it so
02:04:20.620 uncomfortable by the end in terms of body temperature?
02:04:23.140 It really has to do with the amount of energy that's being absorbed. So what we're doing with
02:04:26.580 the electromagnetic field is you're actually putting in radiofrequency, right? And that radiofrequency
02:04:31.860 is always also coming out. And that radiofrequency is the same thing as a cell phone would get.
02:04:37.360 That's called SAR or specific absorption ratio. And the hydrogen ions are basically moving around and
02:04:44.700 that's basically effectively heating you up. So it's not quite like a microwave, but you can actually
02:04:49.160 think about it as a microwave. The wavelength is exactly very similar to an AM radio. And so
02:04:55.660 your cell phone is typically far more powerful. So as an example, I went and did the calculation a
02:05:00.820 while ago on how much SAR we're actually putting into a whole body per nuvo scan. And it's equivalent
02:05:06.720 to talking on a cell phone for about four hours. Interesting. But it concentrates it across your
02:05:11.780 whole body. Right. Yeah. It's funny. Every time I get an MRI or a whole body, the first 30 minutes,
02:05:18.200 I'm like, yeah, it's not so bad. And then the last 10 minutes, I'm like, get me out of here.
02:05:22.740 Right. And we've actually done it that way on purpose because we kind of know that the way we
02:05:26.960 kind of run our sequences or filters together is that we've actually kind of want to get as much
02:05:31.600 information in such a way as possible. Yeah. You do the head first and that's not nearly as much
02:05:35.940 as doing the abdomen and thighs or probably where a ton of that heat gets generated, right? And it's
02:05:40.040 sort of knees to abdomen. Right. And so when you look at basically the overall blood flow, which is
02:05:44.520 what cools your body, well, the brain takes 20% of your cardiac output. So it's basically like this big
02:05:49.400 cool. It's this big heat sink, right? It's a, just cools everything away. Whereas when you get
02:05:54.180 down and lowered to the legs, which you're all muscle, it's going to heat that up. And so that's
02:05:58.420 why we figure out how to orient these and what organization to make, what plan of sequences to
02:06:03.320 make it not as uncomfortable. Commercially, what's the best off the shelf scanner that could come close
02:06:08.960 to producing the resolution you're producing, which is it fully isotropic?
02:06:14.040 Isotropic? It's isotropic in the brain, but in the rest of the body, we're actually doing
02:06:17.580 more conventional clinical images. Tell us what isotropic is. I'm sorry,
02:06:21.080 I shouldn't have clarified that. Sure. So what isotropic basically means is that
02:06:24.020 we're basically slicing you in cubes. So a one by one by one millimeter cube, for example.
02:06:29.320 And then the power of actually doing that one by one by one is that you can now look at things
02:06:32.980 again in three dimensions in any direction you want. The detail and resolution is perfect.
02:06:38.240 And so that's what isotropic means. Whereas MRI typically can't be done isotropically just because
02:06:44.360 of time. You want to cover as much as possible, but you want what we call in-plane resolution,
02:06:49.920 which is how you orient the first gradient to have the highest amount of detail. And then you
02:06:54.680 typically will take a perpendicular view. And that's why when you do these rotations off your
02:06:59.740 sagittal plane, the resolution deteriorates wildly in conventional scans, right?
02:07:04.680 Right. Exactly. And so the diffusions that we're doing are done isotropic,
02:07:08.520 but unconventional, not often.
02:07:10.720 So that's why when you rotate, and hopefully in the show notes, we'll be able to get some videos,
02:07:15.180 like we'll literally just show what it looks like. Cause I know this is a
02:07:18.400 kind of a difficult discussion to have without being able to kind of picture for us. It's easy,
02:07:23.200 but I think we want to make sure that the listener can see this. That's why you don't see any
02:07:26.860 distortion when you rotate the DWI. So is there a commercially available scanner that can do that?
02:07:31.400 Not yet. Someday, not yet.
02:07:33.260 And so basically your goal is just to be, I don't know how to put a timestamp on it. How
02:07:37.220 far are you ahead of what's happening conventionally? I mean, four years ago,
02:07:41.940 you were doing things that I still don't see any scanner doing in the country. And I see the
02:07:47.480 best scanners. Thank you. But, uh, well, for example, like when I have a patient that went to
02:07:53.240 one of the most famous hospitals in the country and had a dedicated prostate CT scan, it took 40 minutes
02:07:59.880 just to do the prostate. Dedicated prostate MRI, MRI, not CT. Yeah. So he had dedicated prostate
02:08:05.560 MRI took 40 minutes. It was on a three or four Tesla magnet. And so he spent two thirds of the
02:08:12.320 time to get a slightly inferior image by resolution, especially on the DWI was far inferior to what you
02:08:20.420 were doing on the whole body. It all comes down to basic engineering of signal to noise. If you can
02:08:25.800 make all the hardware that you have really sing, your signal to noise is so much better. And then
02:08:31.440 you can basically dial it to effectively where you want. So if you need more and more signal,
02:08:35.420 depending on your machines, I guess, horsepower and coil configuration just takes time. It's
02:08:40.740 always a balance between time and signal to noise. So where is machine learning going to come into
02:08:46.820 the fold here? You actually mentioned something to me recently that I had never thought of,
02:08:52.060 which is it's really hard to throw a whole body image at a machine and have it solve even the
02:08:59.360 simplest problem that we take for granted as a human, which is which one's the liver, which one's
02:09:03.660 the kidney. And whereas if you weren't doing a whole body, if you were just doing a liver image,
02:09:09.680 that's an easier problem to hand the machine because it already knows it's looking at liver.
02:09:14.420 So, I mean, how far are we away from a machine being able to help you do this?
02:09:18.420 I think that there's actually a lot of tools that actually still need to be written. So, for example,
02:09:23.080 part of that is to really kind of look at organs and isolate organs. Conventionally, most imaging
02:09:28.500 is done by body part. So head, neck, chest, abdomen, pelvis, and not connected together. And so when you
02:09:35.960 actually give a machine, okay, here's your brain, it's actually able to kind of go through that
02:09:40.260 relatively efficiently. But part of it really comes down to building the tools to actually analyze
02:09:45.760 whole body. Like even the software to view the whole body is exquisitely complex. But the difference
02:09:51.480 is that when you actually start to build these tools, it can actually start to help us narrow
02:09:54.960 down what's going on. And the goal is to really sort of have machines make radiologists more
02:09:59.780 efficient. And also more importantly, we never want to miss anything, right? And so, you know,
02:10:04.500 we can't have a second reader all the time. But if you have a machine being a second reader,
02:10:08.600 you wind up actually training that machine as you go along. And I think most people would be
02:10:12.340 comfortable with that. And that's what's actually done in mammography right now.
02:10:15.560 And so for, I mean, mammography obviously is like the tip of the iceberg, but you got to start
02:10:19.560 somewhere, right? It's very, I don't want to minimize because I couldn't read a mammogram to
02:10:23.860 save my life, but it's relative to what we're talking about. It's much simpler. It seems that
02:10:28.700 where the machine might first be able to make a dent in what you're doing is not the patient who gets
02:10:33.660 their first scan, but the one who gets the repeat scan. That seems to be paired T-test seems to be an
02:10:39.100 easier problem to solve. And an important problem to solve because a lot of times for us as radiologists,
02:10:44.000 like those studies, we still do things the same way when we review them. Whereas when you actually
02:10:49.880 go and you take like a paired T-test, like you said, and you actually do a subtraction where you're
02:10:53.460 looking for the difference or that delta, it can actually stand out and become very, very simple
02:10:57.900 and very obvious. And once that subtraction is done, and I think that's where machine learning will
02:11:02.660 actually really help make us more efficient. And at the end of the day, we just don't want to miss
02:11:06.740 anything. Well, Raj, I've monopolized more of your time today, and that means that there've been
02:11:11.780 probably three or four fewer patients that have been scanned today. So I really appreciate you
02:11:16.380 taking the time. And I appreciate just all the time you've spent over the last three or four years
02:11:20.260 educating me. You're incredibly generous with your insights. And I constantly lob questions at you,
02:11:25.960 and you've always got all the time in the world for me and by extension, my patients and all the people
02:11:30.940 that I hope to sort of try to educate with this. So thank you for the amazing work you're doing here,
02:11:35.280 and then also just for your generosity. Oh, thanks. It's a pleasure. Love it. I need to
02:11:39.420 visit more often. Yeah. Next time you come down to California. Sure. We have Uber.
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